Goals¶
At the end of the tutorial you will know:
- how to write likelihoods in terms of compressed parameters (e.g. based on forecasts), optionally with covariance between different measurements
- how to write full shape likelihoods, and emulate their theory
- how to run inference within desilike, or Cobaya, CosmoSIS, and MontePython.
For real-life examples, see application to mock Y1 cosmological inference.
This is the continuation of the first tutorial, accessible here: desilike tutorial #1.
Environment¶
Easiest is to use the cosmodesi environment at NERSC:
source /global/cfs/cdirs/desi/users/adematti/cosmodesi_environment.sh main # source the environment
${COSMODESIMODULES}/install_jupyter_kernel.sh main # this to be done once
NB: to remove the previous kernel:
rm -rf $HOME/.local/share/jupyter/kernels/cosmodesi-main
To see these slides in a browser, e.g.:
firefox desilike_bindings.slides.html
Compressed likelihoods¶
Let's first focus on compressed likelihoods = only depend on the cosmological model (nuisance = bias, stochastic and counterterms already marginalized out).
=> sampling of these likelihoods is typically fast enough that they do not need to be emulated.
BAO likelihood¶
BAO likelihoods are built from a "BAO observable", that compares a data vector to a theory, typically $\alpha_{\perp}$ and $\alpha_{\parallel}$ or $D_{M}/r_{d}$ and $D_{H}/r_{d}$.
In [2]:
import numpy as np
from desilike import utils, setup_logging
from desilike.likelihoods import ObservablesGaussianLikelihood
from desilike.observables.galaxy_clustering import BAOCompressionObservable
setup_logging()
# fiducial cosmology is DESI's by default
observable1 = BAOCompressionObservable(data=[1., 1.],
covariance=np.diag([0.01, 0.01]),
quantities=['qpar', 'qper'],
z=1.)
# Let's define the likelihood from this observable
likelihood = ObservablesGaussianLikelihood(observable1)
Reminder¶
In [3]:
# Likelihood parameters
print('varied likelihood parameters are', likelihood.varied_params.names())
# To evaluate the likelihood (return the logposterior)
print('logposterior is {:.3f}'.format(likelihood(Omega_m=0.29)))
[000000.16] [0/1] 07-02 10:22 BAOCompressionObservable INFO Found quantities ['qpar', 'qper']. varied likelihood parameters are ['Omega_m'] logposterior is -0.005
Why do we bother about "observables"?
... because we can join them in a likelihood!
In [4]:
# We want to share the same cosmological calculation among all observables
# so let's give it explicitly
from desilike.theories import Cosmoprimo
cosmo = Cosmoprimo(fiducial='DESI')
# Set Cosmoprimo calculator's parameters
cosmo.init.params = {'Omega_m': {'prior': {'limits': [0.1, 0.9]},
'ref': {'dist': 'norm', 'loc': 0.3, 'scale': 0.002},
'latex': '\Omega_m'}}
# Let's reuse the first observable we have defined, just updating the cosmo
observable1.init.update(cosmo=cosmo)
# Let's be fancy and rather define our observable in terms of DV_over_rd
# We provide a dictionary to "data": the theory vector will be generated automatically
observable2 = BAOCompressionObservable(data={}, quantities=['DV_over_rd'], z=1.5, cosmo=cosmo)
# Let's join the two observables, and provide the joint covariance
likelihood = ObservablesGaussianLikelihood([observable1, observable2], covariance=np.diag([0.01, 0.01, 1.]))
print('likelihood is {:.4f}'.format(likelihood()))
[000000.86] [0/1] 07-02 10:22 BAOCompressionObservable INFO Found quantities ['qpar', 'qper']. [000001.13] [0/1] 07-02 10:22 BAOCompressionObservable INFO Found quantities ['DV_over_rd']. likelihood is -0.0000
We can also sum (log-) likelihoods!
In [5]:
likelihood2 = likelihood + likelihood
likelihood(Omega_m=0.29)
likelihood2(Omega_m=0.29)
assert np.allclose(likelihood2.loglikelihood, 2. * likelihood.loglikelihood)
Bindings¶
To generate desilike bindings, let's start by writing a callable (~ "function") that returns the desilike likelihood.
In [6]:
def BAOLikelihood(cosmo='external'):
# cosmo = 'external' to tell desilike that cosmo will be provided externally
observable1 = BAOCompressionObservable(data=[1., 1.], quantities=['qpar', 'qper'], z=0.5, cosmo=cosmo)
observable2 = BAOCompressionObservable(data=[1.], quantities=['qiso'], z=1., cosmo=cosmo)
likelihood = ObservablesGaussianLikelihood([observable1, observable2],
covariance=np.diag([0.002, 0.002, 0.005]))
return likelihood
In [7]:
from desilike.bindings.cobaya import CobayaLikelihoodFactory
# CobayaBAOLikelihood is a Cobaya Likelihood object
CobayaBAOLikelihood = CobayaLikelihoodFactory(BAOLikelihood, params=True)
[000001.73] [0/1] 07-02 10:22 BAOCompressionObservable INFO Found quantities ['qpar', 'qper']. [000001.81] [0/1] 07-02 10:22 BAOCompressionObservable INFO Found quantities ['qiso']. [000002.03] [0/1] 07-02 10:22 numexpr.utils INFO NumExpr defaulting to 8 threads.
In [8]:
from cosmoprimo.fiducial import DESI
cosmo = DESI()
# No magic here, this is all Cobaya stuff
params = {'Omega_m': {'prior': {'min': 0.1, 'max': 1.},
'ref': {'dist': 'norm', 'loc': 0.3, 'scale': 0.01},
'latex': '\Omega_{m}'},
'omega_b': cosmo['omega_b'],
'H0': cosmo['H0'],
'A_s': cosmo['A_s'],
'n_s': cosmo['n_s'],
'tau_reio': cosmo['tau_reio']}
info = {'params': params,
'likelihood': {'bao_likelihood': CobayaBAOLikelihood},
'theory': {'classy': {'extra_args': {'N_ncdm': cosmo['N_ncdm'], 'N_ur': cosmo['N_ur']}}}}
from cobaya.model import get_model
model = get_model(info)
model.logposterior({'Omega_m': cosmo['Omega_m']})
[000002.27] [0/1] 07-02 10:22 classy INFO `classy` module loaded successfully from /home/adematti/anaconda3/envs/cosmodesi/lib/python3.9/site-packages/classy-3.2.0-py3.9-linux-x86_64.egg [000002.35] [0/1] 07-02 10:22 BAOCompressionObservable INFO Found quantities ['qpar', 'qper']. [000002.44] [0/1] 07-02 10:22 BAOCompressionObservable INFO Found quantities ['qiso'].
Out[8]:
LogPosterior(logpost=0.10471144781489061, logpriors=[0.10536051565782628], loglikes=array([-0.00064907]), derived=[], finite=False)
In [9]:
# Let's run MCMC!
info_sampler = {'mcmc': {'Rminus1_stop': 0.02}}
from cobaya.sampler import get_sampler
mcmc = get_sampler(info_sampler, model=model)
mcmc.run()
[000007.45] [0/1] 07-02 10:22 mcmc INFO Getting initial point... (this may take a few seconds)
[000007.54] [0/1] 07-02 10:22 model INFO Measuring speeds... (this may take a few seconds)
[000007.79] [0/1] 07-02 10:22 model INFO Setting measured speeds (per sec): {bao_likelihood: 399.0, classy: 12.5}
[000007.79] [0/1] 07-02 10:22 mcmc INFO Initial point: Omega_m:0.3151184
[000007.79] [0/1] 07-02 10:22 mcmc INFO Covariance matrix not present. We will start learning the covariance of the proposal earlier: R-1 = 30 (would be 2 if all params loaded).
[000007.79] [0/1] 07-02 10:22 mcmc INFO Sampling!
[000007.88] [0/1] 07-02 10:22 mcmc INFO Progress @ 2023-07-02 10:22:39 : 1 steps taken, and 0 accepted.
[000011.29] [0/1] 07-02 10:22 mcmc INFO Learn + convergence test @ 40 samples accepted.
[000011.30] [0/1] 07-02 10:22 mcmc INFO - Acceptance rate: 1.000
[000011.30] [0/1] 07-02 10:22 mcmc INFO - Convergence of means: R-1 = 2.029668 after 32 accepted steps
[000011.30] [0/1] 07-02 10:22 mcmc INFO - Updated covariance matrix of proposal pdf.
[000014.94] [0/1] 07-02 10:22 mcmc INFO Learn + convergence test @ 80 samples accepted.
[000014.95] [0/1] 07-02 10:22 mcmc INFO - Acceptance rate: 0.941
[000014.95] [0/1] 07-02 10:22 mcmc INFO - Convergence of means: R-1 = 2.293076 after 64 accepted steps
[000014.95] [0/1] 07-02 10:22 mcmc INFO - Updated covariance matrix of proposal pdf.
[000019.73] [0/1] 07-02 10:22 mcmc INFO Learn + convergence test @ 120 samples accepted.
[000019.74] [0/1] 07-02 10:22 mcmc INFO - Acceptance rate: 0.774
[000019.74] [0/1] 07-02 10:22 mcmc INFO - Convergence of means: R-1 = 0.646461 after 96 accepted steps
[000019.74] [0/1] 07-02 10:22 mcmc INFO - Updated covariance matrix of proposal pdf.
[000025.94] [0/1] 07-02 10:22 mcmc INFO Learn + convergence test @ 160 samples accepted.
[000025.95] [0/1] 07-02 10:22 mcmc INFO - Acceptance rate: 0.631
[000025.95] [0/1] 07-02 10:22 mcmc INFO - Convergence of means: R-1 = 0.194300 after 128 accepted steps
[000025.95] [0/1] 07-02 10:22 mcmc INFO - Updated covariance matrix of proposal pdf.
[000028.78] [0/1] 07-02 10:23 mcmc INFO Learn + convergence test @ 200 samples accepted.
[000028.79] [0/1] 07-02 10:23 mcmc INFO - Acceptance rate: 0.593
[000028.79] [0/1] 07-02 10:23 mcmc INFO - Convergence of means: R-1 = 0.651474 after 160 accepted steps
[000028.79] [0/1] 07-02 10:23 mcmc INFO - Updated covariance matrix of proposal pdf.
[000031.65] [0/1] 07-02 10:23 mcmc INFO Learn + convergence test @ 240 samples accepted.
[000031.66] [0/1] 07-02 10:23 mcmc INFO - Acceptance rate: 0.558
[000031.66] [0/1] 07-02 10:23 mcmc INFO - Convergence of means: R-1 = 0.089038 after 192 accepted steps
[000031.66] [0/1] 07-02 10:23 mcmc INFO - Updated covariance matrix of proposal pdf.
[000035.02] [0/1] 07-02 10:23 mcmc INFO Learn + convergence test @ 280 samples accepted.
[000035.02] [0/1] 07-02 10:23 mcmc INFO - Acceptance rate: 0.528
[000035.02] [0/1] 07-02 10:23 mcmc INFO - Convergence of means: R-1 = 0.011035 after 224 accepted steps
[000035.03] [0/1] 07-02 10:23 mcmc INFO - Updated covariance matrix of proposal pdf.
[000037.95] [0/1] 07-02 10:23 mcmc INFO Learn + convergence test @ 320 samples accepted.
[000037.95] [0/1] 07-02 10:23 mcmc INFO - Acceptance rate: 0.526
[000037.95] [0/1] 07-02 10:23 mcmc INFO - Convergence of means: R-1 = 0.090079 after 256 accepted steps
[000037.96] [0/1] 07-02 10:23 mcmc INFO - Updated covariance matrix of proposal pdf.
[000041.74] [0/1] 07-02 10:23 mcmc INFO Learn + convergence test @ 360 samples accepted.
[000041.74] [0/1] 07-02 10:23 mcmc INFO - Acceptance rate: 0.500
[000041.74] [0/1] 07-02 10:23 mcmc INFO - Convergence of means: R-1 = 0.015248 after 288 accepted steps
[000041.74] [0/1] 07-02 10:23 mcmc INFO - Updated covariance matrix of proposal pdf.
[000044.27] [0/1] 07-02 10:23 mcmc INFO Learn + convergence test @ 400 samples accepted.
[000044.28] [0/1] 07-02 10:23 mcmc INFO - Acceptance rate: 0.507
[000044.28] [0/1] 07-02 10:23 mcmc INFO - Convergence of means: R-1 = 0.070305 after 320 accepted steps
[000044.28] [0/1] 07-02 10:23 mcmc INFO - Updated covariance matrix of proposal pdf.
[000047.24] [0/1] 07-02 10:23 mcmc INFO Learn + convergence test @ 440 samples accepted.
[000047.24] [0/1] 07-02 10:23 mcmc INFO - Acceptance rate: 0.506
[000047.24] [0/1] 07-02 10:23 mcmc INFO - Convergence of means: R-1 = 0.043942 after 352 accepted steps
[000047.24] [0/1] 07-02 10:23 mcmc INFO - Updated covariance matrix of proposal pdf.
[000050.36] [0/1] 07-02 10:23 mcmc INFO Learn + convergence test @ 480 samples accepted.
[000050.37] [0/1] 07-02 10:23 mcmc INFO - Acceptance rate: 0.496
[000050.37] [0/1] 07-02 10:23 mcmc INFO - Convergence of means: R-1 = 0.004447 after 384 accepted steps
[000050.37] [0/1] 07-02 10:23 mcmc INFO - Updated covariance matrix of proposal pdf.
[000054.13] [0/1] 07-02 10:23 mcmc INFO Learn + convergence test @ 520 samples accepted.
[000054.13] [0/1] 07-02 10:23 mcmc INFO - Acceptance rate: 0.478
[000054.14] [0/1] 07-02 10:23 mcmc INFO - Convergence of means: R-1 = 0.016915 after 416 accepted steps
[000054.15] [0/1] 07-02 10:23 mcmc INFO - Convergence of bounds: R-1 = 0.097983 after 520 accepted steps
[000054.15] [0/1] 07-02 10:23 mcmc INFO The run has converged!
[000054.15] [0/1] 07-02 10:23 mcmc INFO Sampling complete after 520 accepted steps.
In [10]:
from getdist.mcsamples import MCSamplesFromCobaya
samples_bao_cobaya = mcmc.samples(combined=True, skip_samples=0.5, to_getdist=True).copy(label='cobaya')
from getdist import plots
g = plots.get_subplot_plotter()
g.triangle_plot(samples_bao_cobaya, params=['Omega_m'], markers={'Omega_m': cosmo['Omega_m']})
[000054.16] [0/1] 07-02 10:23 root WARNING outlier fraction 0.08076923076923077
Interlude: let's do the same within desilike¶
In [11]:
from desilike.samplers import MCMCSampler
from desilike.theories import Cosmoprimo
cosmo = Cosmoprimo(fiducial='DESI')
# Set Cosmoprimo calculator's parameters
cosmo.init.params = {'Omega_m': {'prior': {'limits': [0.1, 1.]},
'ref': {'dist': 'norm', 'loc': 0.3, 'scale': 0.01},
'latex': '\Omega_m'}}
sampler = MCMCSampler(BAOLikelihood(cosmo=cosmo), seed=42)
chains = sampler.run(check={'max_eigen_gr': 0.03, 'stable_over': 2}, check_every=40)
# do help(chains[0]) to get info on the available methods!
samples_bao_desilike = chains[0].remove_burnin(0.5).to_getdist(label='desilike')
[000054.78] [0/1] 07-02 10:23 BAOCompressionObservable INFO Found quantities ['qpar', 'qper']. [000054.84] [0/1] 07-02 10:23 BAOCompressionObservable INFO Found quantities ['qiso']. [000054.96] [0/1] 07-02 10:23 MCMCSampler INFO Varied parameters: ['Omega_m']. [000055.50] [0/1] 07-02 10:23 BasePipeline INFO Found speeds: [000055.50] [0/1] 07-02 10:23 BasePipeline INFO - <desilike.theories.primordial_cosmology.Cosmoprimo object at 0x7f1829effb20>: 1157.94 iterations / second [000055.50] [0/1] 07-02 10:23 BasePipeline INFO - <desilike.theories.galaxy_clustering.power_template.BAOExtractor object at 0x7f1829e91370>: 22.03 iterations / second [000055.51] [0/1] 07-02 10:23 BasePipeline INFO - <desilike.observables.galaxy_clustering.compression.BAOCompressionObservable object at 0x7f1829ea7ca0>: 4391.94 iterations / second [000055.51] [0/1] 07-02 10:23 BasePipeline INFO - <desilike.theories.galaxy_clustering.power_template.BAOExtractor object at 0x7f1829e91700>: 12531.53 iterations / second [000055.51] [0/1] 07-02 10:23 BasePipeline INFO - <desilike.observables.galaxy_clustering.compression.BAOCompressionObservable object at 0x7f1829ea75e0>: 9226.36 iterations / second [000055.51] [0/1] 07-02 10:23 BasePipeline INFO - <desilike.likelihoods.base.ObservablesGaussianLikelihood object at 0x7f1829e8b2b0>: 4640.23 iterations / second [000057.76] [0/1] 07-02 10:23 MCMCSampler INFO Diagnostics: [000057.76] [0/1] 07-02 10:23 MCMCSampler INFO - max eigen Gelman-Rubin - 1 is 1.6; not < 0.03. [000057.76] [0/1] 07-02 10:23 MCMCSampler INFO - max diag Gelman-Rubin - 1 is 1.6. [000057.78] [0/1] 07-02 10:23 MCMCSampler INFO - max diag Gelman-Rubin - 1 at 1.0 sigmas is 2.04. [000057.78] [0/1] 07-02 10:23 MCMCSampler INFO - max Geweke is nan. [000057.78] [0/1] 07-02 10:23 MCMCSampler INFO - Geweke p-value is nan. [000057.78] [0/1] 07-02 10:23 MCMCSampler INFO - (20 iterations / integrated autocorrelation time) is 32.5. [000057.84] [0/1] 07-02 10:23 MCMCSampler INFO Updating proposal covariance. [000060.64] [0/1] 07-02 10:23 MCMCSampler INFO Diagnostics: [000060.65] [0/1] 07-02 10:23 MCMCSampler INFO - max eigen Gelman-Rubin - 1 is 1.07; not < 0.03. [000060.65] [0/1] 07-02 10:23 MCMCSampler INFO - max diag Gelman-Rubin - 1 is 1.07. [000060.66] [0/1] 07-02 10:23 MCMCSampler INFO - max diag Gelman-Rubin - 1 at 1.0 sigmas is 3.79. [000060.66] [0/1] 07-02 10:23 MCMCSampler INFO - max Geweke is nan. [000060.66] [0/1] 07-02 10:23 MCMCSampler INFO - Geweke p-value is nan. [000060.66] [0/1] 07-02 10:23 MCMCSampler INFO - (40 iterations / integrated autocorrelation time) is 13.7. [000060.66] [0/1] 07-02 10:23 MCMCSampler INFO - max variation of integrated autocorrelation time is 0.789. [000060.73] [0/1] 07-02 10:23 MCMCSampler INFO Updating proposal covariance. [000064.27] [0/1] 07-02 10:23 MCMCSampler INFO Diagnostics: [000064.27] [0/1] 07-02 10:23 MCMCSampler INFO - max eigen Gelman-Rubin - 1 is 0.0663; not < 0.03. [000064.27] [0/1] 07-02 10:23 MCMCSampler INFO - max diag Gelman-Rubin - 1 is 0.0663. [000064.29] [0/1] 07-02 10:23 MCMCSampler INFO - max diag Gelman-Rubin - 1 at 1.0 sigmas is 0.776. [000064.29] [0/1] 07-02 10:23 MCMCSampler INFO - max Geweke is 3.28. [000064.29] [0/1] 07-02 10:23 MCMCSampler INFO - Geweke p-value is nan. [000064.29] [0/1] 07-02 10:23 MCMCSampler INFO - (60 iterations / integrated autocorrelation time) (reliable) is 557. [000064.29] [0/1] 07-02 10:23 MCMCSampler INFO - max variation of integrated autocorrelation time is 26.1. [000064.35] [0/1] 07-02 10:23 MCMCSampler INFO Updating proposal covariance. [000067.87] [0/1] 07-02 10:23 MCMCSampler INFO Diagnostics: [000067.88] [0/1] 07-02 10:23 MCMCSampler INFO - max eigen Gelman-Rubin - 1 is 0.165; not < 0.03. [000067.88] [0/1] 07-02 10:23 MCMCSampler INFO - max diag Gelman-Rubin - 1 is 0.165. [000067.90] [0/1] 07-02 10:23 MCMCSampler INFO - max diag Gelman-Rubin - 1 at 1.0 sigmas is 0.439. [000067.90] [0/1] 07-02 10:23 MCMCSampler INFO - max Geweke is 2.38. [000067.90] [0/1] 07-02 10:23 MCMCSampler INFO - Geweke p-value is nan. [000067.90] [0/1] 07-02 10:23 MCMCSampler INFO - (80 iterations / integrated autocorrelation time) (reliable) is 115. [000067.90] [0/1] 07-02 10:23 MCMCSampler INFO - max variation of integrated autocorrelation time is 0.846. [000067.96] [0/1] 07-02 10:23 MCMCSampler INFO Updating proposal covariance. [000071.53] [0/1] 07-02 10:23 MCMCSampler INFO Diagnostics: [000071.53] [0/1] 07-02 10:23 MCMCSampler INFO - max eigen Gelman-Rubin - 1 is 0.0549; not < 0.03. [000071.53] [0/1] 07-02 10:23 MCMCSampler INFO - max diag Gelman-Rubin - 1 is 0.0549. [000071.55] [0/1] 07-02 10:23 MCMCSampler INFO - max diag Gelman-Rubin - 1 at 1.0 sigmas is 0.128. [000071.55] [0/1] 07-02 10:23 MCMCSampler INFO - max Geweke is 1.35. [000071.55] [0/1] 07-02 10:23 MCMCSampler INFO - Geweke p-value is nan. [000071.55] [0/1] 07-02 10:23 MCMCSampler INFO - (100 iterations / integrated autocorrelation time) is 45.4. [000071.55] [0/1] 07-02 10:23 MCMCSampler INFO - max variation of integrated autocorrelation time is 0.684. [000071.61] [0/1] 07-02 10:23 MCMCSampler INFO Updating proposal covariance. [000075.51] [0/1] 07-02 10:23 MCMCSampler INFO Diagnostics: [000075.52] [0/1] 07-02 10:23 MCMCSampler INFO - max eigen Gelman-Rubin - 1 is 0.0152; < 0.03. [000075.52] [0/1] 07-02 10:23 MCMCSampler INFO - max diag Gelman-Rubin - 1 is 0.0152. [000075.54] [0/1] 07-02 10:23 MCMCSampler INFO - max diag Gelman-Rubin - 1 at 1.0 sigmas is 0.104. [000075.54] [0/1] 07-02 10:23 MCMCSampler INFO - max Geweke is 0.609. [000075.54] [0/1] 07-02 10:23 MCMCSampler INFO - Geweke p-value is nan. [000075.54] [0/1] 07-02 10:23 MCMCSampler INFO - (120 iterations / integrated autocorrelation time) (reliable) is 154. [000075.54] [0/1] 07-02 10:23 MCMCSampler INFO - max variation of integrated autocorrelation time is 1.83. [000075.61] [0/1] 07-02 10:23 MCMCSampler INFO Updating proposal covariance. [000079.50] [0/1] 07-02 10:23 MCMCSampler INFO Diagnostics: [000079.50] [0/1] 07-02 10:23 MCMCSampler INFO - max eigen Gelman-Rubin - 1 is 0.0706; not < 0.03. [000079.51] [0/1] 07-02 10:23 MCMCSampler INFO - max diag Gelman-Rubin - 1 is 0.0706. [000079.52] [0/1] 07-02 10:23 MCMCSampler INFO - max diag Gelman-Rubin - 1 at 1.0 sigmas is 0.103. [000079.53] [0/1] 07-02 10:23 MCMCSampler INFO - max Geweke is 0.606. [000079.53] [0/1] 07-02 10:23 MCMCSampler INFO - Geweke p-value is nan. [000079.53] [0/1] 07-02 10:23 MCMCSampler INFO - (140 iterations / integrated autocorrelation time) (reliable) is 130. [000079.53] [0/1] 07-02 10:23 MCMCSampler INFO - max variation of integrated autocorrelation time is 0.276. [000079.59] [0/1] 07-02 10:23 MCMCSampler INFO Updating proposal covariance. [000083.07] [0/1] 07-02 10:23 MCMCSampler INFO Diagnostics: [000083.07] [0/1] 07-02 10:23 MCMCSampler INFO - max eigen Gelman-Rubin - 1 is 0.0264; < 0.03. [000083.08] [0/1] 07-02 10:23 MCMCSampler INFO - max diag Gelman-Rubin - 1 is 0.0264. [000083.09] [0/1] 07-02 10:23 MCMCSampler INFO - max diag Gelman-Rubin - 1 at 1.0 sigmas is 0.0624. [000083.10] [0/1] 07-02 10:23 MCMCSampler INFO - max Geweke is 0.43. [000083.10] [0/1] 07-02 10:23 MCMCSampler INFO - Geweke p-value is nan. [000083.10] [0/1] 07-02 10:23 MCMCSampler INFO - (160 iterations / integrated autocorrelation time) (reliable) is 160. [000083.10] [0/1] 07-02 10:23 MCMCSampler INFO - max variation of integrated autocorrelation time is 0.0771. [000083.16] [0/1] 07-02 10:23 MCMCSampler INFO Updating proposal covariance. [000086.97] [0/1] 07-02 10:23 MCMCSampler INFO Diagnostics: [000086.97] [0/1] 07-02 10:23 MCMCSampler INFO - max eigen Gelman-Rubin - 1 is 0.0308; not < 0.03. [000086.97] [0/1] 07-02 10:23 MCMCSampler INFO - max diag Gelman-Rubin - 1 is 0.0308. [000086.99] [0/1] 07-02 10:23 MCMCSampler INFO - max diag Gelman-Rubin - 1 at 1.0 sigmas is 0.177. [000087.00] [0/1] 07-02 10:23 MCMCSampler INFO - max Geweke is 2.62. [000087.00] [0/1] 07-02 10:23 MCMCSampler INFO - Geweke p-value is nan. [000087.00] [0/1] 07-02 10:23 MCMCSampler INFO - (180 iterations / integrated autocorrelation time) (reliable) is 177. [000087.00] [0/1] 07-02 10:23 MCMCSampler INFO - max variation of integrated autocorrelation time is 0.0201. [000087.05] [0/1] 07-02 10:23 MCMCSampler INFO Updating proposal covariance. [000091.36] [0/1] 07-02 10:24 MCMCSampler INFO Diagnostics: [000091.36] [0/1] 07-02 10:24 MCMCSampler INFO - max eigen Gelman-Rubin - 1 is 0.015; < 0.03. [000091.37] [0/1] 07-02 10:24 MCMCSampler INFO - max diag Gelman-Rubin - 1 is 0.015. [000091.39] [0/1] 07-02 10:24 MCMCSampler INFO - max diag Gelman-Rubin - 1 at 1.0 sigmas is 0.103. [000091.39] [0/1] 07-02 10:24 MCMCSampler INFO - max Geweke is 0.747. [000091.39] [0/1] 07-02 10:24 MCMCSampler INFO - Geweke p-value is nan. [000091.39] [0/1] 07-02 10:24 MCMCSampler INFO - (200 iterations / integrated autocorrelation time) (reliable) is 207. [000091.39] [0/1] 07-02 10:24 MCMCSampler INFO - max variation of integrated autocorrelation time is 0.0558. [000091.45] [0/1] 07-02 10:24 MCMCSampler INFO Updating proposal covariance. [000095.19] [0/1] 07-02 10:24 MCMCSampler INFO Diagnostics: [000095.20] [0/1] 07-02 10:24 MCMCSampler INFO - max eigen Gelman-Rubin - 1 is 0.0264; < 0.03. [000095.20] [0/1] 07-02 10:24 MCMCSampler INFO - max diag Gelman-Rubin - 1 is 0.0264. [000095.22] [0/1] 07-02 10:24 MCMCSampler INFO - max diag Gelman-Rubin - 1 at 1.0 sigmas is 0.118. [000095.23] [0/1] 07-02 10:24 MCMCSampler INFO - max Geweke is 0.548. [000095.23] [0/1] 07-02 10:24 MCMCSampler INFO - Geweke p-value is nan. [000095.23] [0/1] 07-02 10:24 MCMCSampler INFO - (220 iterations / integrated autocorrelation time) (reliable) is 159. [000095.23] [0/1] 07-02 10:24 MCMCSampler INFO - max variation of integrated autocorrelation time is 0.3. [000095.23] [0/1] 07-02 10:24 root WARNING outlier fraction 0.11363636363636363
In [12]:
g = plots.get_subplot_plotter()
g.triangle_plot([samples_bao_cobaya, samples_bao_desilike],
params=['Omega_m'], markers={'Omega_m': cosmo['Omega_m']})
'Static' bindings¶
Other inference codes (CosmoSIS, MontePython) typically require the likelihood to be written down in a file, such that it is imported by the code. Let's illustrate this, still with Cobaya.
In [15]:
%%file _tests/bao_likelihood.py
dirname = '.'
def BAOLikelihood(cosmo='external'):
import numpy as np
from desilike.observables.galaxy_clustering import BAOCompressionObservable
from desilike.likelihoods import ObservablesGaussianLikelihood
# cosmo = 'external' to tell desilike that cosmo will be provided externally
observable1 = BAOCompressionObservable(data=[1., 1.], quantities=['qpar', 'qper'], z=0.5, cosmo=cosmo)
observable2 = BAOCompressionObservable(data=[1.], quantities=['qiso'], z=1., cosmo=cosmo)
likelihood = ObservablesGaussianLikelihood([observable1, observable2],
covariance=np.diag([0.002, 0.002, 0.005]))
return likelihood
if __name__ == '__main__':
from desilike.bindings import CobayaLikelihoodGenerator
# We could provide a list of Likelihoods, which will all be written at once
CobayaLikelihoodGenerator(dirname=dirname)([BAOLikelihood], kw_like={'cosmo': 'external'})
Writing _tests/bao_likelihood.py
Let's generate the static bindings by calling the above Python script
In [16]:
%%bash
cd _tests/
python bao_likelihood.py
bash: /home/adematti/anaconda3/envs/cosmodesi/lib/libtinfo.so.6: no version information available (required by bash) WARNING:absl:No GPU/TPU found, falling back to CPU. (Set TF_CPP_MIN_LOG_LEVEL=0 and rerun for more info.)
Let's take a look at the generated files:
- the Python module containing the Cobaya likelihood:
bao_likelihood.py - imported in the
__init__.py - the
.yamlconfig file containing the nuisance parameters (none in this case)
In [17]:
!ls -la _tests/cobaya
/bin/bash: /home/adematti/anaconda3/envs/cosmodesi/lib/libtinfo.so.6: no version information available (required by /bin/bash) total 20 drwxr-xr-x 2 adematti idphp 4096 juil. 2 10:24 . drwxr-xr-x 3 adematti idphp 4096 juil. 2 10:24 .. -rw-r--r-- 1 adematti idphp 477 juil. 2 10:24 bao_likelihood.py -rw-r--r-- 1 adematti idphp 31 juil. 2 10:24 BAOLikelihood.yaml -rw-r--r-- 1 adematti idphp 30 juil. 2 10:24 __init__.py
In [19]:
# %load _tests/cobaya/my_likelihood.py
# NOTE: This code has been automatically generated by desilike.bindings.cobaya.factory.CobayaLikelihoodGenerator
from desilike.bindings.cobaya.factory import CobayaLikelihoodFactory
from desilike.bindings.base import load_from_file
BAOLikelihood = load_from_file('/home/adematti/Bureau/DESI/NERSC/cosmodesi/desilike-tutorials/_tests/bao_likelihood.py', 'BAOLikelihood')
BAOLikelihood = CobayaLikelihoodFactory(BAOLikelihood, 'BAOLikelihood',
{'cosmo': 'external'}, __name__)
Now let's write the config file to run inference. This is pure Cobaya.
In [20]:
%%file _tests/config_bao.yaml
theory:
classy:
extra_args:
N_ncdm: 1
N_ur: 2.0328
likelihood:
bao_likelihood.BAOLikelihood:
python_path: _tests/cobaya
params:
Omega_m:
prior:
min: 0.1
max: 1.
ref:
dist: norm
loc: 0.3
scale: 0.01
latex: \Omega_{m}
omega_b: 0.02237
H0: 67.36
As: 2.083e-09
n_s: 0.9649
tau_reio: 0.0544
sampler:
mcmc:
Rminus1_stop: 0.02
debug: True
output: _tests/chains_bao_cobaya/chain
Writing _tests/config_bao.yaml
Let's sample!
In [21]:
!cobaya-run _tests/config_bao.yaml
/bin/bash: /home/adematti/anaconda3/envs/cosmodesi/lib/libtinfo.so.6: no version information available (required by /bin/bash)
2023-07-02 10:24:11,168 [output] Creating output folder '_tests/chains_bao_cobaya'
2023-07-02 10:24:11,168 [output] Output to be read-from/written-into folder '_tests/chains_bao_cobaya', with prefix 'chain'
2023-07-02 10:24:14,042 [root] Initializing MLIR with module: _mlirRegisterEverything
2023-07-02 10:24:14,042 [root] Registering dialects from initializer <module 'jaxlib.mlir._mlir_libs._mlirRegisterEverything' from '/home/adematti/anaconda3/envs/cosmodesi/lib/python3.9/site-packages/jaxlib/mlir/_mlir_libs/_mlirRegisterEverything.so'>
2023-07-02 10:24:14,212 [absl] Finished tracing + transforming prim_fun for jit in 0.00026226043701171875 sec
2023-07-02 10:24:14,212 [absl] Initializing backend 'interpreter'
2023-07-02 10:24:14,213 [absl] Backend 'interpreter' initialized
2023-07-02 10:24:14,213 [absl] Initializing backend 'cpu'
2023-07-02 10:24:14,214 [absl] Backend 'cpu' initialized
2023-07-02 10:24:14,214 [absl] Initializing backend 'tpu_driver'
2023-07-02 10:24:14,215 [absl] Unable to initialize backend 'tpu_driver': NOT_FOUND: Unable to find driver in registry given worker:
2023-07-02 10:24:14,215 [absl] Initializing backend 'cuda'
2023-07-02 10:24:14,215 [absl] Unable to initialize backend 'cuda': module 'jaxlib.xla_extension' has no attribute 'GpuAllocatorConfig'
2023-07-02 10:24:14,215 [absl] Initializing backend 'rocm'
2023-07-02 10:24:14,215 [absl] Unable to initialize backend 'rocm': module 'jaxlib.xla_extension' has no attribute 'GpuAllocatorConfig'
2023-07-02 10:24:14,215 [absl] Initializing backend 'tpu'
2023-07-02 10:24:14,216 [absl] Unable to initialize backend 'tpu': INVALID_ARGUMENT: TpuPlatform is not available.
2023-07-02 10:24:14,216 [absl] *WARNING* No GPU/TPU found, falling back to CPU. (Set TF_CPP_MIN_LOG_LEVEL=0 and rerun for more info.)
2023-07-02 10:24:14,216 [absl] Compiling prim_fun (139946428465856 for args (ShapedArray(int64[]),).
2023-07-02 10:24:14,227 [absl] Finished XLA compilation of convert_element_type in 0.008483171463012695 sec
2023-07-02 10:24:14,517 [classy] Attempting global import (no `path` or Cobaya installation path given).
2023-07-02 10:24:14,519 [classy] `classy` module loaded successfully from /home/adematti/anaconda3/envs/cosmodesi/lib/python3.9/site-packages/classy-3.2.0-py3.9-linux-x86_64.egg
2023-07-02 10:24:14,585 [BAOCompressionObservable] Found quantities ['qpar', 'qper'].
2023-07-02 10:24:14,640 [BAOCompressionObservable] Found quantities ['qiso'].
2023-07-02 10:24:14,807 [model] Parameters were assigned as follows:
2023-07-02 10:24:14,807 [model] - bao_likelihood.BAOLikelihood:
2023-07-02 10:24:14,807 [model] Input: []
2023-07-02 10:24:14,807 [model] Output: []
2023-07-02 10:24:14,807 [model] - classy:
2023-07-02 10:24:14,807 [model] Input: ['Omega_m', 'omega_b', 'H0', 'As', 'n_s', 'tau_reio']
2023-07-02 10:24:14,807 [model] Output: []
2023-07-02 10:24:14,809 [model] Components will be computed in the order:
2023-07-02 10:24:14,809 [model] - [classy, bao_likelihood.BAOLikelihood]
2023-07-02 10:24:14,809 [model] Requirements will be calculated by these components:
2023-07-02 10:24:14,809 [model] - rdrag: classy
2023-07-02 10:24:14,809 [model] - Hubble: classy
2023-07-02 10:24:14,809 [model] - angular_diameter_distance: classy
2023-07-02 10:24:14,814 [mcmc] Initializing
2023-07-02 10:24:14,817 [mcmc] Getting initial point... (this may take a few seconds)
2023-07-02 10:24:14,817 [prior] Evaluating prior at array([0.30227319])
2023-07-02 10:24:14,817 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:14,817 [model] Posterior to be computed for parameters {'Omega_m': 0.302273186715765}
2023-07-02 10:24:14,817 [prior] Evaluating prior at array([0.30227319])
2023-07-02 10:24:14,818 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:14,818 [model] Got input parameters: {'Omega_m': 0.302273186715765, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:14,818 [classy] Got parameters {'Omega_m': 0.302273186715765, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:14,818 [classy] Computing new state
2023-07-02 10:24:14,818 [classy] Setting parameters: {'Omega_m': 0.302273186715765, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:14,869 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.5068711292102}
2023-07-02 10:24:14,869 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:14,870 [absl] Finished tracing + transforming prim_fun for jit in 0.0002644062042236328 sec
2023-07-02 10:24:14,871 [absl] Finished tracing + transforming prim_fun for jit in 0.00018143653869628906 sec
2023-07-02 10:24:14,871 [absl] Finished tracing + transforming prim_fun for jit in 0.00018143653869628906 sec
2023-07-02 10:24:14,872 [absl] Compiling prim_fun (139946281779584 for args (ShapedArray(float64[2]), ShapedArray(float64[1])).
2023-07-02 10:24:14,883 [absl] Finished XLA compilation of concatenate in 0.008332014083862305 sec
2023-07-02 10:24:14,884 [absl] Finished tracing + transforming <lambda> for jit in 0.0003628730773925781 sec
2023-07-02 10:24:14,884 [absl] Compiling <lambda> (139945829539904 for args (ShapedArray(float64[3]), ShapedArray(float64[3])).
2023-07-02 10:24:14,895 [absl] Finished XLA compilation of <lambda> in 0.008444547653198242 sec
2023-07-02 10:24:14,898 [absl] Finished tracing + transforming dot for jit in 0.0008070468902587891 sec
2023-07-02 10:24:14,898 [absl] Compiling dot (139945829539984 for args (ShapedArray(float64[3]), ShapedArray(float64[3,3])).
2023-07-02 10:24:14,918 [absl] Finished XLA compilation of dot in 0.015986919403076172 sec
2023-07-02 10:24:14,921 [absl] Finished tracing + transforming dot for jit in 0.0007879734039306641 sec
2023-07-02 10:24:14,921 [absl] Compiling dot (139945829540384 for args (ShapedArray(float64[3]), ShapedArray(float64[3])).
2023-07-02 10:24:14,941 [absl] Finished XLA compilation of dot in 0.012113094329833984 sec
2023-07-02 10:24:14,942 [absl] Finished tracing + transforming fn for jit in 0.0004296302795410156 sec
2023-07-02 10:24:14,943 [absl] Compiling fn (139945829540064 for args (ShapedArray(float64[], weak_type=True), ShapedArray(float64[])).
2023-07-02 10:24:14,952 [absl] Finished XLA compilation of fn in 0.006169557571411133 sec
2023-07-02 10:24:14,953 [absl] Finished tracing + transforming fn for jit in 0.0004942417144775391 sec
2023-07-02 10:24:14,953 [absl] Compiling fn (139945829540224 for args (ShapedArray(float64[]), ShapedArray(float64[], weak_type=True)).
2023-07-02 10:24:14,962 [absl] Finished XLA compilation of fn in 0.0065000057220458984 sec
2023-07-02 10:24:14,964 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00676172
2023-07-02 10:24:14,964 [model] Computed derived parameters: {}
2023-07-02 10:24:14,964 [model] Measuring speeds... (this may take a few seconds)
2023-07-02 10:24:14,964 [prior] Evaluating prior at array([0.2995852])
2023-07-02 10:24:14,964 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:14,964 [model] Got input parameters: {'Omega_m': 0.29958519951716434, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:14,964 [classy] Got parameters {'Omega_m': 0.29958519951716434, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:14,964 [classy] Computing new state
2023-07-02 10:24:14,964 [classy] Setting parameters: {'Omega_m': 0.29958519951716434, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:15,015 [classy] First evaluation time: 0.0505338 s
2023-07-02 10:24:15,015 [classy] Average evaluation time: 0.0505338 s
2023-07-02 10:24:15,015 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.84123435525387}
2023-07-02 10:24:15,015 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:15,017 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0107415
2023-07-02 10:24:15,017 [bao_likelihood.baolikelihood] First evaluation time: 0.00203782 s
2023-07-02 10:24:15,017 [bao_likelihood.baolikelihood] Average evaluation time: 0.00203782 s
2023-07-02 10:24:15,017 [model] Computed derived parameters: {}
2023-07-02 10:24:15,017 [prior] Evaluating prior at array([0.32097431])
2023-07-02 10:24:15,018 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:15,018 [model] Got input parameters: {'Omega_m': 0.32097431344246147, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:15,018 [classy] Got parameters {'Omega_m': 0.32097431344246147, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:15,018 [classy] Computing new state
2023-07-02 10:24:15,018 [classy] Setting parameters: {'Omega_m': 0.32097431344246147, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:15,073 [classy] Average evaluation time: 0.0555832 s
2023-07-02 10:24:15,073 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.25067556440436}
2023-07-02 10:24:15,074 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:15,076 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00453072
2023-07-02 10:24:15,076 [bao_likelihood.baolikelihood] Average evaluation time: 0.00288756 s
2023-07-02 10:24:15,076 [model] Computed derived parameters: {}
2023-07-02 10:24:15,077 [prior] Evaluating prior at array([0.30121144])
2023-07-02 10:24:15,077 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:15,077 [model] Got input parameters: {'Omega_m': 0.30121144035944686, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:15,077 [classy] Got parameters {'Omega_m': 0.30121144035944686, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:15,077 [classy] Computing new state
2023-07-02 10:24:15,077 [classy] Setting parameters: {'Omega_m': 0.30121144035944686, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:15,134 [classy] Average evaluation time: 0.0561591 s
2023-07-02 10:24:15,134 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.6386245798302}
2023-07-02 10:24:15,134 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:15,136 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00821818
2023-07-02 10:24:15,136 [bao_likelihood.baolikelihood] Average evaluation time: 0.00237307 s
2023-07-02 10:24:15,136 [model] Computed derived parameters: {}
2023-07-02 10:24:15,136 [model] Computed 3 points to measure speeds.
2023-07-02 10:24:15,136 [model] Setting measured speeds (per sec): {bao_likelihood.BAOLikelihood: 421.0, classy: 17.8}
2023-07-02 10:24:15,136 [mcmc] Initial point: Omega_m:0.3022732
2023-07-02 10:24:15,136 [model] Cost, oversampling factor and parameters per block, in optimal order:
2023-07-02 10:24:15,136 [model] * 0.0591324 : 1 : ['Omega_m']
2023-07-02 10:24:15,136 [mcmc] Cycle length in steps: 1
2023-07-02 10:24:15,137 [mcmc] Covariance matrix not present. We will start learning the covariance of the proposal earlier: R-1 = 30 (would be 2 if all params loaded).
2023-07-02 10:24:15,138 [mcmc] Sampling with covmat:
Omega_m
Omega_m 0.000025
2023-07-02 10:24:15,148 [mcmc] Dumped checkpoint and progress info, and current covmat.
2023-07-02 10:24:15,153 [mcmc] Sampling!
2023-07-02 10:24:15,153 [model] Posterior to be computed for parameters {'Omega_m': 0.3007991086649757}
2023-07-02 10:24:15,153 [prior] Evaluating prior at array([0.30079911])
2023-07-02 10:24:15,153 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:15,153 [model] Got input parameters: {'Omega_m': 0.3007991086649757, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:15,153 [classy] Got parameters {'Omega_m': 0.3007991086649757, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:15,153 [classy] Computing new state
2023-07-02 10:24:15,153 [classy] Setting parameters: {'Omega_m': 0.3007991086649757, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:15,205 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.689900976284}
2023-07-02 10:24:15,206 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:15,207 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00882428
2023-07-02 10:24:15,208 [model] Computed derived parameters: {}
2023-07-02 10:24:15,208 [mcmc] Burn-in sample:
Omega_m:0.3022732
2023-07-02 10:24:15,208 [mcmc] Progress @ 2023-07-02 10:24:15 : 1 steps taken, and 0 accepted.
2023-07-02 10:24:15,208 [model] Posterior to be computed for parameters {'Omega_m': 0.32315842225220176}
2023-07-02 10:24:15,208 [prior] Evaluating prior at array([0.32315842])
2023-07-02 10:24:15,208 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:15,208 [model] Got input parameters: {'Omega_m': 0.32315842225220176, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:15,208 [classy] Got parameters {'Omega_m': 0.32315842225220176, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:15,208 [classy] Computing new state
2023-07-02 10:24:15,208 [classy] Setting parameters: {'Omega_m': 0.32315842225220176, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:15,264 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.99485620641119}
2023-07-02 10:24:15,264 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:15,267 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00700766
2023-07-02 10:24:15,268 [model] Computed derived parameters: {}
2023-07-02 10:24:15,268 [mcmc] New sample, #1:
Omega_m:0.3007991
2023-07-02 10:24:15,268 [model] Posterior to be computed for parameters {'Omega_m': 0.33789596472574496}
2023-07-02 10:24:15,268 [prior] Evaluating prior at array([0.33789596])
2023-07-02 10:24:15,268 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:15,268 [model] Got input parameters: {'Omega_m': 0.33789596472574496, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:15,268 [classy] Got parameters {'Omega_m': 0.33789596472574496, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:15,268 [classy] Computing new state
2023-07-02 10:24:15,268 [classy] Setting parameters: {'Omega_m': 0.33789596472574496, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:15,331 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.3082409272329}
2023-07-02 10:24:15,331 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:15,333 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0374296
2023-07-02 10:24:15,333 [model] Computed derived parameters: {}
2023-07-02 10:24:15,333 [mcmc] New sample, #2:
Omega_m:0.3231584
2023-07-02 10:24:15,333 [model] Posterior to be computed for parameters {'Omega_m': 0.32413007886776585}
2023-07-02 10:24:15,333 [prior] Evaluating prior at array([0.32413008])
2023-07-02 10:24:15,333 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:15,333 [model] Got input parameters: {'Omega_m': 0.32413007886776585, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:15,333 [classy] Got parameters {'Omega_m': 0.32413007886776585, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:15,333 [classy] Computing new state
2023-07-02 10:24:15,333 [classy] Setting parameters: {'Omega_m': 0.32413007886776585, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:15,384 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.8815414956248}
2023-07-02 10:24:15,384 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:15,386 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00828395
2023-07-02 10:24:15,386 [model] Computed derived parameters: {}
2023-07-02 10:24:15,386 [mcmc] New sample, #3:
Omega_m:0.337896
2023-07-02 10:24:15,386 [model] Posterior to be computed for parameters {'Omega_m': 0.33083201785663213}
2023-07-02 10:24:15,386 [prior] Evaluating prior at array([0.33083202])
2023-07-02 10:24:15,386 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:15,386 [model] Got input parameters: {'Omega_m': 0.33083201785663213, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:15,386 [classy] Got parameters {'Omega_m': 0.33083201785663213, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:15,386 [classy] Computing new state
2023-07-02 10:24:15,386 [classy] Setting parameters: {'Omega_m': 0.33083201785663213, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:15,438 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.1081750507962}
2023-07-02 10:24:15,438 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:15,440 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0199404
2023-07-02 10:24:15,440 [model] Computed derived parameters: {}
2023-07-02 10:24:15,440 [mcmc] New sample, #4:
Omega_m:0.3241301
2023-07-02 10:24:15,441 [model] Posterior to be computed for parameters {'Omega_m': 0.33607200100876394}
2023-07-02 10:24:15,441 [prior] Evaluating prior at array([0.336072])
2023-07-02 10:24:15,441 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:15,441 [model] Got input parameters: {'Omega_m': 0.33607200100876394, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:15,441 [classy] Got parameters {'Omega_m': 0.33607200100876394, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:15,441 [classy] Computing new state
2023-07-02 10:24:15,441 [classy] Setting parameters: {'Omega_m': 0.33607200100876394, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:15,496 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.51333283236454}
2023-07-02 10:24:15,497 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:15,498 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0324167
2023-07-02 10:24:15,498 [model] Computed derived parameters: {}
2023-07-02 10:24:15,499 [mcmc] New sample, #5:
Omega_m:0.330832
2023-07-02 10:24:15,499 [model] Posterior to be computed for parameters {'Omega_m': 0.33952887817032834}
2023-07-02 10:24:15,499 [prior] Evaluating prior at array([0.33952888])
2023-07-02 10:24:15,499 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:15,499 [model] Got input parameters: {'Omega_m': 0.33952887817032834, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:15,499 [classy] Got parameters {'Omega_m': 0.33952887817032834, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:15,499 [classy] Computing new state
2023-07-02 10:24:15,499 [classy] Setting parameters: {'Omega_m': 0.33952887817032834, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:15,566 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.1254797896763}
2023-07-02 10:24:15,567 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:15,569 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0422051
2023-07-02 10:24:15,569 [model] Computed derived parameters: {}
2023-07-02 10:24:15,570 [mcmc] New sample, #6:
Omega_m:0.336072
2023-07-02 10:24:15,570 [model] Posterior to be computed for parameters {'Omega_m': 0.342473331012135}
2023-07-02 10:24:15,570 [prior] Evaluating prior at array([0.34247333])
2023-07-02 10:24:15,570 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:15,570 [model] Got input parameters: {'Omega_m': 0.342473331012135, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:15,570 [classy] Got parameters {'Omega_m': 0.342473331012135, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:15,570 [classy] Computing new state
2023-07-02 10:24:15,570 [classy] Setting parameters: {'Omega_m': 0.342473331012135, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:15,618 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.79792805596563}
2023-07-02 10:24:15,619 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:15,620 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0514925
2023-07-02 10:24:15,620 [model] Computed derived parameters: {}
2023-07-02 10:24:15,621 [mcmc] New sample, #7:
Omega_m:0.3395289
2023-07-02 10:24:15,621 [model] Posterior to be computed for parameters {'Omega_m': 0.3215200632916294}
2023-07-02 10:24:15,621 [prior] Evaluating prior at array([0.32152006])
2023-07-02 10:24:15,621 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:15,621 [model] Got input parameters: {'Omega_m': 0.3215200632916294, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:15,621 [classy] Got parameters {'Omega_m': 0.3215200632916294, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:15,621 [classy] Computing new state
2023-07-02 10:24:15,621 [classy] Setting parameters: {'Omega_m': 0.3215200632916294, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:15,681 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.18660752848703}
2023-07-02 10:24:15,681 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:15,683 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0050985
2023-07-02 10:24:15,683 [model] Computed derived parameters: {}
2023-07-02 10:24:15,683 [mcmc] New sample, #8:
Omega_m:0.3424733
2023-07-02 10:24:15,683 [model] Posterior to be computed for parameters {'Omega_m': 0.3117036623357385}
2023-07-02 10:24:15,683 [prior] Evaluating prior at array([0.31170366])
2023-07-02 10:24:15,683 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:15,683 [model] Got input parameters: {'Omega_m': 0.3117036623357385, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:15,683 [classy] Got parameters {'Omega_m': 0.3117036623357385, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:15,683 [classy] Computing new state
2023-07-02 10:24:15,683 [classy] Setting parameters: {'Omega_m': 0.3117036623357385, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:15,743 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.35412871793827}
2023-07-02 10:24:15,743 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:15,745 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00023978
2023-07-02 10:24:15,745 [model] Computed derived parameters: {}
2023-07-02 10:24:15,745 [mcmc] New sample, #9:
Omega_m:0.3215201
2023-07-02 10:24:15,745 [model] Posterior to be computed for parameters {'Omega_m': 0.3123373924246803}
2023-07-02 10:24:15,745 [prior] Evaluating prior at array([0.31233739])
2023-07-02 10:24:15,745 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:15,745 [model] Got input parameters: {'Omega_m': 0.3123373924246803, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:15,745 [classy] Got parameters {'Omega_m': 0.3123373924246803, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:15,745 [classy] Computing new state
2023-07-02 10:24:15,745 [classy] Setting parameters: {'Omega_m': 0.3123373924246803, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:15,796 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.27777077091875}
2023-07-02 10:24:15,796 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:15,798 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000203686
2023-07-02 10:24:15,798 [model] Computed derived parameters: {}
2023-07-02 10:24:15,798 [mcmc] New sample, #10:
Omega_m:0.3117037
2023-07-02 10:24:15,798 [model] Posterior to be computed for parameters {'Omega_m': 0.2932204999145311}
2023-07-02 10:24:15,799 [prior] Evaluating prior at array([0.2932205])
2023-07-02 10:24:15,799 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:15,799 [model] Got input parameters: {'Omega_m': 0.2932204999145311, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:15,799 [classy] Got parameters {'Omega_m': 0.2932204999145311, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:15,799 [classy] Computing new state
2023-07-02 10:24:15,799 [classy] Setting parameters: {'Omega_m': 0.2932204999145311, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:15,849 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.6435741385667}
2023-07-02 10:24:15,849 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:15,851 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0240966
2023-07-02 10:24:15,851 [model] Computed derived parameters: {}
2023-07-02 10:24:15,851 [mcmc] New sample, #11:
Omega_m:0.3123374
2023-07-02 10:24:15,851 [model] Posterior to be computed for parameters {'Omega_m': 0.29947916769934524}
2023-07-02 10:24:15,851 [prior] Evaluating prior at array([0.29947917])
2023-07-02 10:24:15,851 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:15,851 [model] Got input parameters: {'Omega_m': 0.29947916769934524, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:15,851 [classy] Got parameters {'Omega_m': 0.29947916769934524, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:15,851 [classy] Computing new state
2023-07-02 10:24:15,851 [classy] Setting parameters: {'Omega_m': 0.29947916769934524, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:15,901 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.85447580462787}
2023-07-02 10:24:15,901 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:15,902 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0109183
2023-07-02 10:24:15,903 [model] Computed derived parameters: {}
2023-07-02 10:24:15,903 [mcmc] New sample, #12:
Omega_m:0.2932205
2023-07-02 10:24:15,903 [model] Posterior to be computed for parameters {'Omega_m': 0.2900981027279275}
2023-07-02 10:24:15,903 [prior] Evaluating prior at array([0.2900981])
2023-07-02 10:24:15,903 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:15,903 [model] Got input parameters: {'Omega_m': 0.2900981027279275, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:15,903 [classy] Got parameters {'Omega_m': 0.2900981027279275, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:15,903 [classy] Computing new state
2023-07-02 10:24:15,903 [classy] Setting parameters: {'Omega_m': 0.2900981027279275, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:15,953 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.0427302927278}
2023-07-02 10:24:15,953 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:15,955 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0327323
2023-07-02 10:24:15,955 [model] Computed derived parameters: {}
2023-07-02 10:24:15,955 [mcmc] New sample, #13:
Omega_m:0.2994792
2023-07-02 10:24:15,955 [model] Posterior to be computed for parameters {'Omega_m': 0.2691868700159219}
2023-07-02 10:24:15,955 [prior] Evaluating prior at array([0.26918687])
2023-07-02 10:24:15,955 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:15,955 [model] Got input parameters: {'Omega_m': 0.2691868700159219, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:15,955 [classy] Got parameters {'Omega_m': 0.2691868700159219, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:15,955 [classy] Computing new state
2023-07-02 10:24:15,955 [classy] Setting parameters: {'Omega_m': 0.2691868700159219, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:16,015 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.8156274119291}
2023-07-02 10:24:16,015 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:16,017 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.128845
2023-07-02 10:24:16,017 [model] Computed derived parameters: {}
2023-07-02 10:24:16,017 [model] Posterior to be computed for parameters {'Omega_m': 0.280471289320419}
2023-07-02 10:24:16,017 [prior] Evaluating prior at array([0.28047129])
2023-07-02 10:24:16,017 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:16,017 [model] Got input parameters: {'Omega_m': 0.280471289320419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:16,017 [classy] Got parameters {'Omega_m': 0.280471289320419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:16,017 [classy] Computing new state
2023-07-02 10:24:16,017 [classy] Setting parameters: {'Omega_m': 0.280471289320419, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:16,064 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.29724526202205}
2023-07-02 10:24:16,064 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:16,066 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0684299
2023-07-02 10:24:16,066 [model] Computed derived parameters: {}
2023-07-02 10:24:16,066 [mcmc] New sample, #14:
Omega_m:0.2900981
2023-07-02 10:24:16,067 [model] Posterior to be computed for parameters {'Omega_m': 0.2912250387630257}
2023-07-02 10:24:16,067 [prior] Evaluating prior at array([0.29122504])
2023-07-02 10:24:16,067 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:16,067 [model] Got input parameters: {'Omega_m': 0.2912250387630257, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:16,067 [classy] Got parameters {'Omega_m': 0.2912250387630257, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:16,067 [classy] Computing new state
2023-07-02 10:24:16,067 [classy] Setting parameters: {'Omega_m': 0.2912250387630257, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:16,116 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.89823836186707}
2023-07-02 10:24:16,116 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:16,118 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0294539
2023-07-02 10:24:16,118 [model] Computed derived parameters: {}
2023-07-02 10:24:16,118 [mcmc] New sample, #15:
Omega_m:0.2804713
2023-07-02 10:24:16,118 [model] Posterior to be computed for parameters {'Omega_m': 0.27609166145454084}
2023-07-02 10:24:16,118 [prior] Evaluating prior at array([0.27609166])
2023-07-02 10:24:16,118 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:16,118 [model] Got input parameters: {'Omega_m': 0.27609166145454084, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:16,118 [classy] Got parameters {'Omega_m': 0.27609166145454084, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:16,118 [classy] Computing new state
2023-07-02 10:24:16,118 [classy] Setting parameters: {'Omega_m': 0.27609166145454084, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:16,167 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.88025221398976}
2023-07-02 10:24:16,167 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:16,169 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0894095
2023-07-02 10:24:16,169 [model] Computed derived parameters: {}
2023-07-02 10:24:16,169 [mcmc] New sample, #16:
Omega_m:0.291225
2023-07-02 10:24:16,170 [model] Posterior to be computed for parameters {'Omega_m': 0.29479639688293596}
2023-07-02 10:24:16,170 [prior] Evaluating prior at array([0.2947964])
2023-07-02 10:24:16,170 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:16,170 [model] Got input parameters: {'Omega_m': 0.29479639688293596, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:16,170 [classy] Got parameters {'Omega_m': 0.29479639688293596, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:16,170 [classy] Computing new state
2023-07-02 10:24:16,170 [classy] Setting parameters: {'Omega_m': 0.29479639688293596, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:16,218 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.4435138141882}
2023-07-02 10:24:16,218 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:16,220 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0202653
2023-07-02 10:24:16,220 [model] Computed derived parameters: {}
2023-07-02 10:24:16,220 [mcmc] New sample, #17:
Omega_m:0.2760917
2023-07-02 10:24:16,220 [model] Posterior to be computed for parameters {'Omega_m': 0.29865588582998637}
2023-07-02 10:24:16,220 [prior] Evaluating prior at array([0.29865589])
2023-07-02 10:24:16,220 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:16,220 [model] Got input parameters: {'Omega_m': 0.29865588582998637, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:16,220 [classy] Got parameters {'Omega_m': 0.29865588582998637, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:16,220 [classy] Computing new state
2023-07-02 10:24:16,220 [classy] Setting parameters: {'Omega_m': 0.29865588582998637, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:16,271 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.9574512028558}
2023-07-02 10:24:16,271 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:16,274 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0123437
2023-07-02 10:24:16,274 [model] Computed derived parameters: {}
2023-07-02 10:24:16,275 [mcmc] New sample, #18:
Omega_m:0.2947964
2023-07-02 10:24:16,275 [model] Posterior to be computed for parameters {'Omega_m': 0.29723500560955995}
2023-07-02 10:24:16,275 [prior] Evaluating prior at array([0.29723501])
2023-07-02 10:24:16,276 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:16,276 [model] Got input parameters: {'Omega_m': 0.29723500560955995, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:16,276 [classy] Got parameters {'Omega_m': 0.29723500560955995, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:16,276 [classy] Computing new state
2023-07-02 10:24:16,276 [classy] Setting parameters: {'Omega_m': 0.29723500560955995, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:16,324 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.13575844311157}
2023-07-02 10:24:16,324 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:16,326 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0150211
2023-07-02 10:24:16,327 [model] Computed derived parameters: {}
2023-07-02 10:24:16,327 [mcmc] New sample, #19:
Omega_m:0.2986559
2023-07-02 10:24:16,327 [model] Posterior to be computed for parameters {'Omega_m': 0.28305010515806117}
2023-07-02 10:24:16,327 [prior] Evaluating prior at array([0.28305011])
2023-07-02 10:24:16,327 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:16,327 [model] Got input parameters: {'Omega_m': 0.28305010515806117, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:16,327 [classy] Got parameters {'Omega_m': 0.28305010515806117, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:16,327 [classy] Computing new state
2023-07-02 10:24:16,327 [classy] Setting parameters: {'Omega_m': 0.28305010515806117, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:16,378 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.95758563130443}
2023-07-02 10:24:16,378 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:16,381 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0574878
2023-07-02 10:24:16,381 [model] Computed derived parameters: {}
2023-07-02 10:24:16,381 [mcmc] New sample, #20:
Omega_m:0.297235
2023-07-02 10:24:16,381 [model] Posterior to be computed for parameters {'Omega_m': 0.28073149980625695}
2023-07-02 10:24:16,381 [prior] Evaluating prior at array([0.2807315])
2023-07-02 10:24:16,381 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:16,381 [model] Got input parameters: {'Omega_m': 0.28073149980625695, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:16,381 [classy] Got parameters {'Omega_m': 0.28073149980625695, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:16,381 [classy] Computing new state
2023-07-02 10:24:16,381 [classy] Setting parameters: {'Omega_m': 0.28073149980625695, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:16,433 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.26285158142838}
2023-07-02 10:24:16,433 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:16,436 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.067279
2023-07-02 10:24:16,436 [model] Computed derived parameters: {}
2023-07-02 10:24:16,436 [mcmc] New sample, #21:
Omega_m:0.2830501
2023-07-02 10:24:16,436 [model] Posterior to be computed for parameters {'Omega_m': 0.29223660116766337}
2023-07-02 10:24:16,436 [prior] Evaluating prior at array([0.2922366])
2023-07-02 10:24:16,437 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:16,437 [model] Got input parameters: {'Omega_m': 0.29223660116766337, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:16,437 [classy] Got parameters {'Omega_m': 0.29223660116766337, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:16,437 [classy] Computing new state
2023-07-02 10:24:16,437 [classy] Setting parameters: {'Omega_m': 0.29223660116766337, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:16,488 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.7689546038691}
2023-07-02 10:24:16,488 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:16,490 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0266671
2023-07-02 10:24:16,490 [model] Computed derived parameters: {}
2023-07-02 10:24:16,490 [mcmc] New sample, #22:
Omega_m:0.2807315
2023-07-02 10:24:16,490 [model] Posterior to be computed for parameters {'Omega_m': 0.2969693279596925}
2023-07-02 10:24:16,490 [prior] Evaluating prior at array([0.29696933])
2023-07-02 10:24:16,490 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:16,490 [model] Got input parameters: {'Omega_m': 0.2969693279596925, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:16,490 [classy] Got parameters {'Omega_m': 0.2969693279596925, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:16,490 [classy] Computing new state
2023-07-02 10:24:16,490 [classy] Setting parameters: {'Omega_m': 0.2969693279596925, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:16,541 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.1691800298089}
2023-07-02 10:24:16,542 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:16,546 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0155525
2023-07-02 10:24:16,546 [model] Computed derived parameters: {}
2023-07-02 10:24:16,546 [mcmc] New sample, #23:
Omega_m:0.2922366
2023-07-02 10:24:16,546 [model] Posterior to be computed for parameters {'Omega_m': 0.297233934750986}
2023-07-02 10:24:16,546 [prior] Evaluating prior at array([0.29723393])
2023-07-02 10:24:16,547 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:16,547 [model] Got input parameters: {'Omega_m': 0.297233934750986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:16,547 [classy] Got parameters {'Omega_m': 0.297233934750986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:16,547 [classy] Computing new state
2023-07-02 10:24:16,547 [classy] Setting parameters: {'Omega_m': 0.297233934750986, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:16,598 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.1358969285858}
2023-07-02 10:24:16,598 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:16,600 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0150234
2023-07-02 10:24:16,600 [model] Computed derived parameters: {}
2023-07-02 10:24:16,600 [mcmc] New sample, #24:
Omega_m:0.2969693
2023-07-02 10:24:16,600 [model] Posterior to be computed for parameters {'Omega_m': 0.3499030775936966}
2023-07-02 10:24:16,600 [prior] Evaluating prior at array([0.34990308])
2023-07-02 10:24:16,601 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:16,601 [model] Got input parameters: {'Omega_m': 0.3499030775936966, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:16,601 [classy] Got parameters {'Omega_m': 0.3499030775936966, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:16,601 [classy] Computing new state
2023-07-02 10:24:16,601 [classy] Setting parameters: {'Omega_m': 0.3499030775936966, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:16,652 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.98276014896697}
2023-07-02 10:24:16,652 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:16,654 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.078679
2023-07-02 10:24:16,654 [model] Computed derived parameters: {}
2023-07-02 10:24:16,654 [mcmc] New sample, #25:
Omega_m:0.2972339
2023-07-02 10:24:16,654 [model] Posterior to be computed for parameters {'Omega_m': 0.34926691201517696}
2023-07-02 10:24:16,654 [prior] Evaluating prior at array([0.34926691])
2023-07-02 10:24:16,654 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:16,654 [model] Got input parameters: {'Omega_m': 0.34926691201517696, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:16,654 [classy] Got parameters {'Omega_m': 0.34926691201517696, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:16,654 [classy] Computing new state
2023-07-02 10:24:16,654 [classy] Setting parameters: {'Omega_m': 0.34926691201517696, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:16,708 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.0519341089871}
2023-07-02 10:24:16,708 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:16,710 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0761455
2023-07-02 10:24:16,710 [model] Computed derived parameters: {}
2023-07-02 10:24:16,710 [mcmc] New sample, #26:
Omega_m:0.3499031
2023-07-02 10:24:16,710 [model] Posterior to be computed for parameters {'Omega_m': 0.36342619528868847}
2023-07-02 10:24:16,710 [prior] Evaluating prior at array([0.3634262])
2023-07-02 10:24:16,710 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:16,710 [model] Got input parameters: {'Omega_m': 0.36342619528868847, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:16,710 [classy] Got parameters {'Omega_m': 0.36342619528868847, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:16,710 [classy] Computing new state
2023-07-02 10:24:16,711 [classy] Setting parameters: {'Omega_m': 0.36342619528868847, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:16,767 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.53901511391388}
2023-07-02 10:24:16,767 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:16,768 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.14121
2023-07-02 10:24:16,768 [model] Computed derived parameters: {}
2023-07-02 10:24:16,769 [mcmc] New sample, #27:
Omega_m:0.3492669
2023-07-02 10:24:16,769 [model] Posterior to be computed for parameters {'Omega_m': 0.35214122431692957}
2023-07-02 10:24:16,769 [prior] Evaluating prior at array([0.35214122])
2023-07-02 10:24:16,769 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:16,769 [model] Got input parameters: {'Omega_m': 0.35214122431692957, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:16,769 [classy] Got parameters {'Omega_m': 0.35214122431692957, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:16,769 [classy] Computing new state
2023-07-02 10:24:16,769 [classy] Setting parameters: {'Omega_m': 0.35214122431692957, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:16,823 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.74030408688444}
2023-07-02 10:24:16,823 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:16,826 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0878916
2023-07-02 10:24:16,826 [model] Computed derived parameters: {}
2023-07-02 10:24:16,826 [mcmc] New sample, #28:
Omega_m:0.3634262
2023-07-02 10:24:16,826 [model] Posterior to be computed for parameters {'Omega_m': 0.35016960846442663}
2023-07-02 10:24:16,826 [prior] Evaluating prior at array([0.35016961])
2023-07-02 10:24:16,827 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:16,827 [model] Got input parameters: {'Omega_m': 0.35016960846442663, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:16,827 [classy] Got parameters {'Omega_m': 0.35016960846442663, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:16,827 [classy] Computing new state
2023-07-02 10:24:16,827 [classy] Setting parameters: {'Omega_m': 0.35016960846442663, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:16,904 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.95381309063686}
2023-07-02 10:24:16,904 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:16,906 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0797516
2023-07-02 10:24:16,906 [model] Computed derived parameters: {}
2023-07-02 10:24:16,907 [mcmc] New sample, #29:
Omega_m:0.3521412
2023-07-02 10:24:16,907 [model] Posterior to be computed for parameters {'Omega_m': 0.33120937553814433}
2023-07-02 10:24:16,907 [prior] Evaluating prior at array([0.33120938])
2023-07-02 10:24:16,907 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:16,907 [model] Got input parameters: {'Omega_m': 0.33120937553814433, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:16,907 [classy] Got parameters {'Omega_m': 0.33120937553814433, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:16,907 [classy] Computing new state
2023-07-02 10:24:16,907 [classy] Setting parameters: {'Omega_m': 0.33120937553814433, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:16,967 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.0650540352797}
2023-07-02 10:24:16,967 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:16,969 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0207419
2023-07-02 10:24:16,969 [model] Computed derived parameters: {}
2023-07-02 10:24:16,969 [mcmc] New sample, #30:
Omega_m:0.3501696
2023-07-02 10:24:16,969 [model] Posterior to be computed for parameters {'Omega_m': 0.34391059230924237}
2023-07-02 10:24:16,969 [prior] Evaluating prior at array([0.34391059])
2023-07-02 10:24:16,969 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:16,969 [model] Got input parameters: {'Omega_m': 0.34391059230924237, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:16,969 [classy] Got parameters {'Omega_m': 0.34391059230924237, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:16,969 [classy] Computing new state
2023-07-02 10:24:16,969 [classy] Setting parameters: {'Omega_m': 0.34391059230924237, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:17,033 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.6389719980835}
2023-07-02 10:24:17,034 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:17,035 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0563373
2023-07-02 10:24:17,035 [model] Computed derived parameters: {}
2023-07-02 10:24:17,036 [mcmc] New sample, #31:
Omega_m:0.3312094
2023-07-02 10:24:17,036 [model] Posterior to be computed for parameters {'Omega_m': 0.3333248644244746}
2023-07-02 10:24:17,036 [prior] Evaluating prior at array([0.33332486])
2023-07-02 10:24:17,036 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:17,036 [model] Got input parameters: {'Omega_m': 0.3333248644244746, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:17,036 [classy] Got parameters {'Omega_m': 0.3333248644244746, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:17,036 [classy] Computing new state
2023-07-02 10:24:17,036 [classy] Setting parameters: {'Omega_m': 0.3333248644244746, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:17,086 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.82413574460827}
2023-07-02 10:24:17,086 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:17,090 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0255157
2023-07-02 10:24:17,090 [model] Computed derived parameters: {}
2023-07-02 10:24:17,090 [mcmc] New sample, #32:
Omega_m:0.3439106
2023-07-02 10:24:17,090 [model] Posterior to be computed for parameters {'Omega_m': 0.3536732961125939}
2023-07-02 10:24:17,090 [prior] Evaluating prior at array([0.3536733])
2023-07-02 10:24:17,091 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:17,091 [model] Got input parameters: {'Omega_m': 0.3536732961125939, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:17,091 [classy] Got parameters {'Omega_m': 0.3536732961125939, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:17,091 [classy] Computing new state
2023-07-02 10:24:17,091 [classy] Setting parameters: {'Omega_m': 0.3536732961125939, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:17,147 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.57514870695294}
2023-07-02 10:24:17,147 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:17,149 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.094464
2023-07-02 10:24:17,149 [model] Computed derived parameters: {}
2023-07-02 10:24:17,149 [mcmc] New sample, #33:
Omega_m:0.3333249
2023-07-02 10:24:17,149 [model] Posterior to be computed for parameters {'Omega_m': 0.37045242206221485}
2023-07-02 10:24:17,149 [prior] Evaluating prior at array([0.37045242])
2023-07-02 10:24:17,150 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:17,150 [model] Got input parameters: {'Omega_m': 0.37045242206221485, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:17,150 [classy] Got parameters {'Omega_m': 0.37045242206221485, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:17,150 [classy] Computing new state
2023-07-02 10:24:17,150 [classy] Setting parameters: {'Omega_m': 0.37045242206221485, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:17,202 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.80842460608994}
2023-07-02 10:24:17,202 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:17,205 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.179922
2023-07-02 10:24:17,205 [model] Computed derived parameters: {}
2023-07-02 10:24:17,205 [mcmc] New sample, #34:
Omega_m:0.3536733
2023-07-02 10:24:17,205 [model] Posterior to be computed for parameters {'Omega_m': 0.36808450307191337}
2023-07-02 10:24:17,205 [prior] Evaluating prior at array([0.3680845])
2023-07-02 10:24:17,205 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:17,205 [model] Got input parameters: {'Omega_m': 0.36808450307191337, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:17,205 [classy] Got parameters {'Omega_m': 0.36808450307191337, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:17,205 [classy] Computing new state
2023-07-02 10:24:17,205 [classy] Setting parameters: {'Omega_m': 0.36808450307191337, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:17,270 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.05319593829313}
2023-07-02 10:24:17,270 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:17,272 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.166419
2023-07-02 10:24:17,272 [model] Computed derived parameters: {}
2023-07-02 10:24:17,272 [mcmc] New sample, #35:
Omega_m:0.3704524
2023-07-02 10:24:17,272 [model] Posterior to be computed for parameters {'Omega_m': 0.34620313501519584}
2023-07-02 10:24:17,272 [prior] Evaluating prior at array([0.34620314])
2023-07-02 10:24:17,272 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:17,272 [model] Got input parameters: {'Omega_m': 0.34620313501519584, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:17,272 [classy] Got parameters {'Omega_m': 0.34620313501519584, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:17,272 [classy] Computing new state
2023-07-02 10:24:17,272 [classy] Setting parameters: {'Omega_m': 0.34620313501519584, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:17,328 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.38669449399833}
2023-07-02 10:24:17,328 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:17,330 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0644796
2023-07-02 10:24:17,330 [model] Computed derived parameters: {}
2023-07-02 10:24:17,330 [mcmc] New sample, #36:
Omega_m:0.3680845
2023-07-02 10:24:17,330 [model] Posterior to be computed for parameters {'Omega_m': 0.34810138032190235}
2023-07-02 10:24:17,330 [prior] Evaluating prior at array([0.34810138])
2023-07-02 10:24:17,330 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:17,331 [model] Got input parameters: {'Omega_m': 0.34810138032190235, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:17,331 [classy] Got parameters {'Omega_m': 0.34810138032190235, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:17,331 [classy] Computing new state
2023-07-02 10:24:17,331 [classy] Setting parameters: {'Omega_m': 0.34810138032190235, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:17,384 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.178967779028}
2023-07-02 10:24:17,384 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:17,386 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0716027
2023-07-02 10:24:17,386 [model] Computed derived parameters: {}
2023-07-02 10:24:17,386 [mcmc] New sample, #37:
Omega_m:0.3462031
2023-07-02 10:24:17,387 [model] Posterior to be computed for parameters {'Omega_m': 0.3445511484616483}
2023-07-02 10:24:17,387 [prior] Evaluating prior at array([0.34455115])
2023-07-02 10:24:17,387 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:17,387 [model] Got input parameters: {'Omega_m': 0.3445511484616483, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:17,387 [classy] Got parameters {'Omega_m': 0.3445511484616483, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:17,387 [classy] Computing new state
2023-07-02 10:24:17,387 [classy] Setting parameters: {'Omega_m': 0.3445511484616483, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:17,442 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.5683228147591}
2023-07-02 10:24:17,442 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:17,445 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0585616
2023-07-02 10:24:17,445 [model] Computed derived parameters: {}
2023-07-02 10:24:17,445 [mcmc] New sample, #38:
Omega_m:0.3481014
2023-07-02 10:24:17,446 [model] Posterior to be computed for parameters {'Omega_m': 0.3468201565018789}
2023-07-02 10:24:17,446 [prior] Evaluating prior at array([0.34682016])
2023-07-02 10:24:17,446 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:17,446 [model] Got input parameters: {'Omega_m': 0.3468201565018789, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:17,446 [classy] Got parameters {'Omega_m': 0.3468201565018789, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:17,446 [classy] Computing new state
2023-07-02 10:24:17,446 [classy] Setting parameters: {'Omega_m': 0.3468201565018789, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:17,503 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.31905974738186}
2023-07-02 10:24:17,503 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:17,505 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0667573
2023-07-02 10:24:17,505 [model] Computed derived parameters: {}
2023-07-02 10:24:17,505 [mcmc] New sample, #39:
Omega_m:0.3445511
2023-07-02 10:24:17,505 [model] Posterior to be computed for parameters {'Omega_m': 0.35364803069707795}
2023-07-02 10:24:17,505 [prior] Evaluating prior at array([0.35364803])
2023-07-02 10:24:17,505 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:17,506 [model] Got input parameters: {'Omega_m': 0.35364803069707795, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:17,506 [classy] Got parameters {'Omega_m': 0.35364803069707795, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:17,506 [classy] Computing new state
2023-07-02 10:24:17,506 [classy] Setting parameters: {'Omega_m': 0.35364803069707795, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:17,570 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.57786789162083}
2023-07-02 10:24:17,570 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:17,571 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0943538
2023-07-02 10:24:17,572 [model] Computed derived parameters: {}
2023-07-02 10:24:17,572 [mcmc] New sample, #40:
Omega_m:0.3468202
2023-07-02 10:24:17,572 [mcmc] Learn + convergence test @ 40 samples accepted.
2023-07-02 10:24:17,572 [mcmc] Ready to check convergence and learn a new proposal covmat
2023-07-02 10:24:17,577 [mcmc] - Acceptance rate: 0.970
2023-07-02 10:24:17,578 [mcmc] - Condition number = 1
2023-07-02 10:24:17,578 [mcmc] - Eigenvalues = array([4.12433607])
2023-07-02 10:24:17,578 [mcmc] - Convergence of means: R-1 = 4.124336 after 32 accepted steps
2023-07-02 10:24:17,578 [mcmc] - Updated covariance matrix of proposal pdf.
2023-07-02 10:24:17,578 [mcmc] array([[0.00023226]])
2023-07-02 10:24:17,588 [mcmc] Dumped checkpoint and progress info, and current covmat.
2023-07-02 10:24:17,589 [model] Posterior to be computed for parameters {'Omega_m': 0.3434946484190942}
2023-07-02 10:24:17,589 [prior] Evaluating prior at array([0.34349465])
2023-07-02 10:24:17,589 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:17,589 [model] Got input parameters: {'Omega_m': 0.3434946484190942, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:17,589 [classy] Got parameters {'Omega_m': 0.3434946484190942, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:17,589 [classy] Computing new state
2023-07-02 10:24:17,589 [classy] Setting parameters: {'Omega_m': 0.3434946484190942, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:17,650 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.6849122336123}
2023-07-02 10:24:17,650 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:17,652 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0549144
2023-07-02 10:24:17,652 [model] Computed derived parameters: {}
2023-07-02 10:24:17,653 [mcmc] New sample, #41:
Omega_m:0.353648
2023-07-02 10:24:17,653 [model] Posterior to be computed for parameters {'Omega_m': 0.31164082741182497}
2023-07-02 10:24:17,653 [prior] Evaluating prior at array([0.31164083])
2023-07-02 10:24:17,653 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:17,653 [model] Got input parameters: {'Omega_m': 0.31164082741182497, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:17,653 [classy] Got parameters {'Omega_m': 0.31164082741182497, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:17,653 [classy] Computing new state
2023-07-02 10:24:17,653 [classy] Setting parameters: {'Omega_m': 0.31164082741182497, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:17,705 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.36170671916042}
2023-07-02 10:24:17,706 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:17,708 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000246056
2023-07-02 10:24:17,708 [model] Computed derived parameters: {}
2023-07-02 10:24:17,708 [mcmc] New sample, #42:
Omega_m:0.3434946
2023-07-02 10:24:17,708 [model] Posterior to be computed for parameters {'Omega_m': 0.35911874589211235}
2023-07-02 10:24:17,708 [prior] Evaluating prior at array([0.35911875])
2023-07-02 10:24:17,709 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:17,709 [model] Got input parameters: {'Omega_m': 0.35911874589211235, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:17,709 [classy] Got parameters {'Omega_m': 0.35911874589211235, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:17,709 [classy] Computing new state
2023-07-02 10:24:17,709 [classy] Setting parameters: {'Omega_m': 0.35911874589211235, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:17,765 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.99340735531325}
2023-07-02 10:24:17,765 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:17,767 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.119537
2023-07-02 10:24:17,767 [model] Computed derived parameters: {}
2023-07-02 10:24:17,767 [mcmc] New sample, #43:
Omega_m:0.3116408
2023-07-02 10:24:17,767 [model] Posterior to be computed for parameters {'Omega_m': 0.38438805590647795}
2023-07-02 10:24:17,767 [prior] Evaluating prior at array([0.38438806])
2023-07-02 10:24:17,767 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:17,767 [model] Got input parameters: {'Omega_m': 0.38438805590647795, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:17,767 [classy] Got parameters {'Omega_m': 0.38438805590647795, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:17,767 [classy] Computing new state
2023-07-02 10:24:17,767 [classy] Setting parameters: {'Omega_m': 0.38438805590647795, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:17,819 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 139.39689420537823}
2023-07-02 10:24:17,819 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:17,821 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.26832
2023-07-02 10:24:17,821 [model] Computed derived parameters: {}
2023-07-02 10:24:17,821 [mcmc] New sample, #44:
Omega_m:0.3591187
2023-07-02 10:24:17,821 [model] Posterior to be computed for parameters {'Omega_m': 0.29690913953196835}
2023-07-02 10:24:17,821 [prior] Evaluating prior at array([0.29690914])
2023-07-02 10:24:17,821 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:17,821 [model] Got input parameters: {'Omega_m': 0.29690913953196835, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:17,821 [classy] Got parameters {'Omega_m': 0.29690913953196835, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:17,821 [classy] Computing new state
2023-07-02 10:24:17,821 [classy] Setting parameters: {'Omega_m': 0.29690913953196835, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:17,881 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.1767559837437}
2023-07-02 10:24:17,881 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:17,883 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0156742
2023-07-02 10:24:17,883 [model] Computed derived parameters: {}
2023-07-02 10:24:17,883 [mcmc] New sample, #45:
Omega_m:0.3843881
2023-07-02 10:24:17,884 [model] Posterior to be computed for parameters {'Omega_m': 0.2742060636134438}
2023-07-02 10:24:17,884 [prior] Evaluating prior at array([0.27420606])
2023-07-02 10:24:17,884 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:17,884 [model] Got input parameters: {'Omega_m': 0.2742060636134438, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:17,884 [classy] Got parameters {'Omega_m': 0.2742060636134438, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:17,884 [classy] Computing new state
2023-07-02 10:24:17,884 [classy] Setting parameters: {'Omega_m': 0.2742060636134438, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:17,953 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.13368429248118}
2023-07-02 10:24:17,954 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:17,955 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0993925
2023-07-02 10:24:17,955 [model] Computed derived parameters: {}
2023-07-02 10:24:17,956 [mcmc] New sample, #46:
Omega_m:0.2969091
2023-07-02 10:24:17,956 [model] Posterior to be computed for parameters {'Omega_m': 0.2900212166496125}
2023-07-02 10:24:17,956 [prior] Evaluating prior at array([0.29002122])
2023-07-02 10:24:17,956 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:17,956 [model] Got input parameters: {'Omega_m': 0.2900212166496125, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:17,956 [classy] Got parameters {'Omega_m': 0.2900212166496125, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:17,956 [classy] Computing new state
2023-07-02 10:24:17,956 [classy] Setting parameters: {'Omega_m': 0.2900212166496125, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:18,014 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.05260420907697}
2023-07-02 10:24:18,015 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:18,017 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0329626
2023-07-02 10:24:18,017 [model] Computed derived parameters: {}
2023-07-02 10:24:18,017 [mcmc] New sample, #47:
Omega_m:0.2742061
2023-07-02 10:24:18,017 [model] Posterior to be computed for parameters {'Omega_m': 0.34614081995542817}
2023-07-02 10:24:18,017 [prior] Evaluating prior at array([0.34614082])
2023-07-02 10:24:18,017 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:18,017 [model] Got input parameters: {'Omega_m': 0.34614081995542817, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:18,017 [classy] Got parameters {'Omega_m': 0.34614081995542817, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:18,017 [classy] Computing new state
2023-07-02 10:24:18,017 [classy] Setting parameters: {'Omega_m': 0.34614081995542817, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:18,077 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.3935323776795}
2023-07-02 10:24:18,077 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:18,080 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0642516
2023-07-02 10:24:18,080 [model] Computed derived parameters: {}
2023-07-02 10:24:18,080 [mcmc] New sample, #48:
Omega_m:0.2900212
2023-07-02 10:24:18,080 [model] Posterior to be computed for parameters {'Omega_m': 0.4159224670621742}
2023-07-02 10:24:18,080 [prior] Evaluating prior at array([0.41592247])
2023-07-02 10:24:18,080 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:18,080 [model] Got input parameters: {'Omega_m': 0.4159224670621742, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:18,080 [classy] Got parameters {'Omega_m': 0.4159224670621742, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:18,080 [classy] Computing new state
2023-07-02 10:24:18,080 [classy] Setting parameters: {'Omega_m': 0.4159224670621742, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:18,136 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 136.37354777840756}
2023-07-02 10:24:18,136 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:18,139 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.518985
2023-07-02 10:24:18,139 [model] Computed derived parameters: {}
2023-07-02 10:24:18,139 [mcmc] New sample, #49:
Omega_m:0.3461408
2023-07-02 10:24:18,139 [model] Posterior to be computed for parameters {'Omega_m': 0.4020603874371157}
2023-07-02 10:24:18,139 [prior] Evaluating prior at array([0.40206039])
2023-07-02 10:24:18,139 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:18,139 [model] Got input parameters: {'Omega_m': 0.4020603874371157, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:18,139 [classy] Got parameters {'Omega_m': 0.4020603874371157, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:18,139 [classy] Computing new state
2023-07-02 10:24:18,139 [classy] Setting parameters: {'Omega_m': 0.4020603874371157, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:18,186 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 137.67469055425212}
2023-07-02 10:24:18,186 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:18,188 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.400756
2023-07-02 10:24:18,188 [model] Computed derived parameters: {}
2023-07-02 10:24:18,188 [mcmc] New sample, #50:
Omega_m:0.4159225
2023-07-02 10:24:18,188 [model] Posterior to be computed for parameters {'Omega_m': 0.34875742041024865}
2023-07-02 10:24:18,188 [prior] Evaluating prior at array([0.34875742])
2023-07-02 10:24:18,189 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:18,189 [model] Got input parameters: {'Omega_m': 0.34875742041024865, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:18,189 [classy] Got parameters {'Omega_m': 0.34875742041024865, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:18,189 [classy] Computing new state
2023-07-02 10:24:18,189 [classy] Setting parameters: {'Omega_m': 0.34875742041024865, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:18,235 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.10741653786135}
2023-07-02 10:24:18,235 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:18,237 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.074144
2023-07-02 10:24:18,237 [model] Computed derived parameters: {}
2023-07-02 10:24:18,237 [mcmc] New sample, #51:
Omega_m:0.4020604
2023-07-02 10:24:18,237 [model] Posterior to be computed for parameters {'Omega_m': 0.3790102593223994}
2023-07-02 10:24:18,237 [prior] Evaluating prior at array([0.37901026])
2023-07-02 10:24:18,238 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:18,238 [model] Got input parameters: {'Omega_m': 0.3790102593223994, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:18,238 [classy] Got parameters {'Omega_m': 0.3790102593223994, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:18,238 [classy] Computing new state
2023-07-02 10:24:18,238 [classy] Setting parameters: {'Omega_m': 0.3790102593223994, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:18,284 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 139.93582436747081}
2023-07-02 10:24:18,284 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:18,286 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.232443
2023-07-02 10:24:18,286 [model] Computed derived parameters: {}
2023-07-02 10:24:18,286 [mcmc] New sample, #52:
Omega_m:0.3487574
2023-07-02 10:24:18,286 [model] Posterior to be computed for parameters {'Omega_m': 0.34278955423758845}
2023-07-02 10:24:18,286 [prior] Evaluating prior at array([0.34278955])
2023-07-02 10:24:18,286 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:18,286 [model] Got input parameters: {'Omega_m': 0.34278955423758845, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:18,286 [classy] Got parameters {'Omega_m': 0.34278955423758845, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:18,286 [classy] Computing new state
2023-07-02 10:24:18,286 [classy] Setting parameters: {'Omega_m': 0.34278955423758845, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:18,332 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.76290375337732}
2023-07-02 10:24:18,332 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:18,334 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.052541
2023-07-02 10:24:18,334 [model] Computed derived parameters: {}
2023-07-02 10:24:18,334 [mcmc] New sample, #53:
Omega_m:0.3790103
2023-07-02 10:24:18,334 [model] Posterior to be computed for parameters {'Omega_m': 0.36758932131026517}
2023-07-02 10:24:18,334 [prior] Evaluating prior at array([0.36758932])
2023-07-02 10:24:18,334 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:18,334 [model] Got input parameters: {'Omega_m': 0.36758932131026517, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:18,334 [classy] Got parameters {'Omega_m': 0.36758932131026517, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:18,334 [classy] Computing new state
2023-07-02 10:24:18,334 [classy] Setting parameters: {'Omega_m': 0.36758932131026517, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:18,380 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.10456555513295}
2023-07-02 10:24:18,380 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:18,382 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.163654
2023-07-02 10:24:18,382 [model] Computed derived parameters: {}
2023-07-02 10:24:18,382 [mcmc] New sample, #54:
Omega_m:0.3427896
2023-07-02 10:24:18,382 [model] Posterior to be computed for parameters {'Omega_m': 0.3755426516112474}
2023-07-02 10:24:18,382 [prior] Evaluating prior at array([0.37554265])
2023-07-02 10:24:18,382 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:18,382 [model] Got input parameters: {'Omega_m': 0.3755426516112474, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:18,382 [classy] Got parameters {'Omega_m': 0.3755426516112474, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:18,382 [classy] Computing new state
2023-07-02 10:24:18,382 [classy] Setting parameters: {'Omega_m': 0.3755426516112474, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:18,429 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.28713173771578}
2023-07-02 10:24:18,429 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:18,431 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.210474
2023-07-02 10:24:18,431 [model] Computed derived parameters: {}
2023-07-02 10:24:18,431 [mcmc] New sample, #55:
Omega_m:0.3675893
2023-07-02 10:24:18,431 [model] Posterior to be computed for parameters {'Omega_m': 0.42315655758688553}
2023-07-02 10:24:18,431 [prior] Evaluating prior at array([0.42315656])
2023-07-02 10:24:18,431 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:18,431 [model] Got input parameters: {'Omega_m': 0.42315655758688553, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:18,431 [classy] Got parameters {'Omega_m': 0.42315655758688553, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:18,431 [classy] Computing new state
2023-07-02 10:24:18,431 [classy] Setting parameters: {'Omega_m': 0.42315655758688553, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:18,479 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 135.71096115013347}
2023-07-02 10:24:18,480 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:18,481 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.585277
2023-07-02 10:24:18,481 [model] Computed derived parameters: {}
2023-07-02 10:24:18,482 [mcmc] New sample, #56:
Omega_m:0.3755427
2023-07-02 10:24:18,482 [model] Posterior to be computed for parameters {'Omega_m': 0.4744200609223728}
2023-07-02 10:24:18,482 [prior] Evaluating prior at array([0.47442006])
2023-07-02 10:24:18,482 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:18,482 [model] Got input parameters: {'Omega_m': 0.4744200609223728, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:18,482 [classy] Got parameters {'Omega_m': 0.4744200609223728, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:18,482 [classy] Computing new state
2023-07-02 10:24:18,482 [classy] Setting parameters: {'Omega_m': 0.4744200609223728, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:18,529 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 131.30962418964663}
2023-07-02 10:24:18,529 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:18,531 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.13203
2023-07-02 10:24:18,531 [model] Computed derived parameters: {}
2023-07-02 10:24:18,531 [model] Posterior to be computed for parameters {'Omega_m': 0.4524392402008138}
2023-07-02 10:24:18,531 [prior] Evaluating prior at array([0.45243924])
2023-07-02 10:24:18,531 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:18,531 [model] Got input parameters: {'Omega_m': 0.4524392402008138, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:18,531 [classy] Got parameters {'Omega_m': 0.4524392402008138, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:18,531 [classy] Computing new state
2023-07-02 10:24:18,531 [classy] Setting parameters: {'Omega_m': 0.4524392402008138, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:18,579 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 133.13674000765212}
2023-07-02 10:24:18,579 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:18,581 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.882354
2023-07-02 10:24:18,581 [model] Computed derived parameters: {}
2023-07-02 10:24:18,581 [mcmc] New sample, #57:
Omega_m:0.4231566
2023-07-02 10:24:18,581 [model] Posterior to be computed for parameters {'Omega_m': 0.4683741499572768}
2023-07-02 10:24:18,581 [prior] Evaluating prior at array([0.46837415])
2023-07-02 10:24:18,581 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:18,581 [model] Got input parameters: {'Omega_m': 0.4683741499572768, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:18,581 [classy] Got parameters {'Omega_m': 0.4683741499572768, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:18,581 [classy] Computing new state
2023-07-02 10:24:18,581 [classy] Setting parameters: {'Omega_m': 0.4683741499572768, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:18,629 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 131.8037069741478}
2023-07-02 10:24:18,629 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:18,631 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.06129
2023-07-02 10:24:18,631 [model] Computed derived parameters: {}
2023-07-02 10:24:18,631 [mcmc] New sample, #58:
Omega_m:0.4524392
2023-07-02 10:24:18,631 [model] Posterior to be computed for parameters {'Omega_m': 0.44475293665972726}
2023-07-02 10:24:18,631 [prior] Evaluating prior at array([0.44475294])
2023-07-02 10:24:18,631 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:18,631 [model] Got input parameters: {'Omega_m': 0.44475293665972726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:18,631 [classy] Got parameters {'Omega_m': 0.44475293665972726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:18,631 [classy] Computing new state
2023-07-02 10:24:18,631 [classy] Setting parameters: {'Omega_m': 0.44475293665972726, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:18,679 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 133.79633866775825}
2023-07-02 10:24:18,679 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:18,681 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.80019
2023-07-02 10:24:18,681 [model] Computed derived parameters: {}
2023-07-02 10:24:18,681 [mcmc] New sample, #59:
Omega_m:0.4683741
2023-07-02 10:24:18,681 [model] Posterior to be computed for parameters {'Omega_m': 0.5118120402734262}
2023-07-02 10:24:18,681 [prior] Evaluating prior at array([0.51181204])
2023-07-02 10:24:18,682 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:18,682 [model] Got input parameters: {'Omega_m': 0.5118120402734262, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:18,682 [classy] Got parameters {'Omega_m': 0.5118120402734262, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:18,682 [classy] Computing new state
2023-07-02 10:24:18,682 [classy] Setting parameters: {'Omega_m': 0.5118120402734262, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:18,729 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 128.3871102237813}
2023-07-02 10:24:18,729 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:18,731 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.60008
2023-07-02 10:24:18,731 [model] Computed derived parameters: {}
2023-07-02 10:24:18,731 [model] Posterior to be computed for parameters {'Omega_m': 0.4238646743502005}
2023-07-02 10:24:18,731 [prior] Evaluating prior at array([0.42386467])
2023-07-02 10:24:18,731 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:18,731 [model] Got input parameters: {'Omega_m': 0.4238646743502005, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:18,731 [classy] Got parameters {'Omega_m': 0.4238646743502005, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:18,732 [classy] Computing new state
2023-07-02 10:24:18,732 [classy] Setting parameters: {'Omega_m': 0.4238646743502005, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:18,779 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 135.64668691149058}
2023-07-02 10:24:18,779 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:18,781 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.591928
2023-07-02 10:24:18,781 [model] Computed derived parameters: {}
2023-07-02 10:24:18,781 [mcmc] New sample, #60:
Omega_m:0.4447529
2023-07-02 10:24:18,781 [model] Posterior to be computed for parameters {'Omega_m': 0.3436429875295004}
2023-07-02 10:24:18,781 [prior] Evaluating prior at array([0.34364299])
2023-07-02 10:24:18,781 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:18,781 [model] Got input parameters: {'Omega_m': 0.3436429875295004, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:18,781 [classy] Got parameters {'Omega_m': 0.3436429875295004, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:18,781 [classy] Computing new state
2023-07-02 10:24:18,782 [classy] Setting parameters: {'Omega_m': 0.3436429875295004, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:18,829 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.6685221758994}
2023-07-02 10:24:18,829 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:18,830 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0554199
2023-07-02 10:24:18,830 [model] Computed derived parameters: {}
2023-07-02 10:24:18,831 [mcmc] New sample, #61:
Omega_m:0.4238647
2023-07-02 10:24:18,831 [model] Posterior to be computed for parameters {'Omega_m': 0.3133760423111451}
2023-07-02 10:24:18,831 [prior] Evaluating prior at array([0.31337604])
2023-07-02 10:24:18,831 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:18,831 [model] Got input parameters: {'Omega_m': 0.3133760423111451, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:18,831 [classy] Got parameters {'Omega_m': 0.3133760423111451, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:18,831 [classy] Computing new state
2023-07-02 10:24:18,831 [classy] Setting parameters: {'Omega_m': 0.3133760423111451, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:18,879 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.15291895172206}
2023-07-02 10:24:18,879 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:18,881 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000251081
2023-07-02 10:24:18,881 [model] Computed derived parameters: {}
2023-07-02 10:24:18,881 [mcmc] New sample, #62:
Omega_m:0.343643
2023-07-02 10:24:18,881 [model] Posterior to be computed for parameters {'Omega_m': 0.29645416731960006}
2023-07-02 10:24:18,881 [prior] Evaluating prior at array([0.29645417])
2023-07-02 10:24:18,881 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:18,881 [model] Got input parameters: {'Omega_m': 0.29645416731960006, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:18,881 [classy] Got parameters {'Omega_m': 0.29645416731960006, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:18,881 [classy] Computing new state
2023-07-02 10:24:18,881 [classy] Setting parameters: {'Omega_m': 0.29645416731960006, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:18,928 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.23406218474446}
2023-07-02 10:24:18,928 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:18,930 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0166106
2023-07-02 10:24:18,930 [model] Computed derived parameters: {}
2023-07-02 10:24:18,930 [mcmc] New sample, #63:
Omega_m:0.313376
2023-07-02 10:24:18,930 [model] Posterior to be computed for parameters {'Omega_m': 0.29042647734846566}
2023-07-02 10:24:18,930 [prior] Evaluating prior at array([0.29042648])
2023-07-02 10:24:18,930 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:18,930 [model] Got input parameters: {'Omega_m': 0.29042647734846566, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:18,930 [classy] Got parameters {'Omega_m': 0.29042647734846566, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:18,930 [classy] Computing new state
2023-07-02 10:24:18,930 [classy] Setting parameters: {'Omega_m': 0.29042647734846566, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:18,978 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.00057898317326}
2023-07-02 10:24:18,978 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:18,979 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0317581
2023-07-02 10:24:18,979 [model] Computed derived parameters: {}
2023-07-02 10:24:18,980 [mcmc] New sample, #64:
Omega_m:0.2964542
2023-07-02 10:24:18,980 [model] Posterior to be computed for parameters {'Omega_m': 0.3222866627095768}
2023-07-02 10:24:18,980 [prior] Evaluating prior at array([0.32228666])
2023-07-02 10:24:18,980 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:18,980 [model] Got input parameters: {'Omega_m': 0.3222866627095768, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:18,980 [classy] Got parameters {'Omega_m': 0.3222866627095768, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:18,980 [classy] Computing new state
2023-07-02 10:24:18,980 [classy] Setting parameters: {'Omega_m': 0.3222866627095768, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:19,034 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.09677624267084}
2023-07-02 10:24:19,034 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:19,036 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00595374
2023-07-02 10:24:19,036 [model] Computed derived parameters: {}
2023-07-02 10:24:19,036 [mcmc] New sample, #65:
Omega_m:0.2904265
2023-07-02 10:24:19,036 [model] Posterior to be computed for parameters {'Omega_m': 0.22225349294669922}
2023-07-02 10:24:19,036 [prior] Evaluating prior at array([0.22225349])
2023-07-02 10:24:19,036 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:19,036 [model] Got input parameters: {'Omega_m': 0.22225349294669922, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:19,036 [classy] Got parameters {'Omega_m': 0.22225349294669922, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:19,036 [classy] Computing new state
2023-07-02 10:24:19,036 [classy] Setting parameters: {'Omega_m': 0.22225349294669922, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:19,084 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 159.76268707085174}
2023-07-02 10:24:19,084 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:19,086 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.639244
2023-07-02 10:24:19,086 [model] Computed derived parameters: {}
2023-07-02 10:24:19,086 [model] Posterior to be computed for parameters {'Omega_m': 0.309050007723876}
2023-07-02 10:24:19,086 [prior] Evaluating prior at array([0.30905001])
2023-07-02 10:24:19,086 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:19,086 [model] Got input parameters: {'Omega_m': 0.309050007723876, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:19,086 [classy] Got parameters {'Omega_m': 0.309050007723876, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:19,086 [classy] Computing new state
2023-07-02 10:24:19,086 [classy] Setting parameters: {'Omega_m': 0.309050007723876, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:19,133 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.67536190596553}
2023-07-02 10:24:19,133 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:19,135 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00093177
2023-07-02 10:24:19,135 [model] Computed derived parameters: {}
2023-07-02 10:24:19,135 [mcmc] New sample, #66:
Omega_m:0.3222867
2023-07-02 10:24:19,135 [model] Posterior to be computed for parameters {'Omega_m': 0.30009599369395673}
2023-07-02 10:24:19,135 [prior] Evaluating prior at array([0.30009599])
2023-07-02 10:24:19,135 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:19,135 [model] Got input parameters: {'Omega_m': 0.30009599369395673, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:19,135 [classy] Got parameters {'Omega_m': 0.30009599369395673, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:19,135 [classy] Computing new state
2023-07-02 10:24:19,135 [classy] Setting parameters: {'Omega_m': 0.30009599369395673, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:19,183 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.77748660867425}
2023-07-02 10:24:19,183 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:19,184 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0099105
2023-07-02 10:24:19,185 [model] Computed derived parameters: {}
2023-07-02 10:24:19,185 [mcmc] New sample, #67:
Omega_m:0.30905
2023-07-02 10:24:19,185 [model] Posterior to be computed for parameters {'Omega_m': 0.3964570899636888}
2023-07-02 10:24:19,185 [prior] Evaluating prior at array([0.39645709])
2023-07-02 10:24:19,185 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:19,185 [model] Got input parameters: {'Omega_m': 0.3964570899636888, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:19,185 [classy] Got parameters {'Omega_m': 0.3964570899636888, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:19,185 [classy] Computing new state
2023-07-02 10:24:19,185 [classy] Setting parameters: {'Omega_m': 0.3964570899636888, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:19,232 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 138.21283551583468}
2023-07-02 10:24:19,232 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:19,234 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.356447
2023-07-02 10:24:19,234 [model] Computed derived parameters: {}
2023-07-02 10:24:19,234 [mcmc] New sample, #68:
Omega_m:0.300096
2023-07-02 10:24:19,234 [model] Posterior to be computed for parameters {'Omega_m': 0.3665539146960622}
2023-07-02 10:24:19,234 [prior] Evaluating prior at array([0.36655391])
2023-07-02 10:24:19,235 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:19,235 [model] Got input parameters: {'Omega_m': 0.3665539146960622, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:19,235 [classy] Got parameters {'Omega_m': 0.3665539146960622, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:19,235 [classy] Computing new state
2023-07-02 10:24:19,235 [classy] Setting parameters: {'Omega_m': 0.3665539146960622, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:19,283 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.21219013189292}
2023-07-02 10:24:19,283 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:19,284 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.157937
2023-07-02 10:24:19,284 [model] Computed derived parameters: {}
2023-07-02 10:24:19,285 [mcmc] New sample, #69:
Omega_m:0.3964571
2023-07-02 10:24:19,285 [model] Posterior to be computed for parameters {'Omega_m': 0.367761724113744}
2023-07-02 10:24:19,285 [prior] Evaluating prior at array([0.36776172])
2023-07-02 10:24:19,285 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:19,285 [model] Got input parameters: {'Omega_m': 0.367761724113744, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:19,285 [classy] Got parameters {'Omega_m': 0.367761724113744, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:19,285 [classy] Computing new state
2023-07-02 10:24:19,285 [classy] Setting parameters: {'Omega_m': 0.367761724113744, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:19,332 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.08667295805708}
2023-07-02 10:24:19,332 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:19,334 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.164615
2023-07-02 10:24:19,334 [model] Computed derived parameters: {}
2023-07-02 10:24:19,334 [mcmc] New sample, #70:
Omega_m:0.3665539
2023-07-02 10:24:19,334 [model] Posterior to be computed for parameters {'Omega_m': 0.3311413174185863}
2023-07-02 10:24:19,334 [prior] Evaluating prior at array([0.33114132])
2023-07-02 10:24:19,334 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:19,334 [model] Got input parameters: {'Omega_m': 0.3311413174185863, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:19,334 [classy] Got parameters {'Omega_m': 0.3311413174185863, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:19,334 [classy] Computing new state
2023-07-02 10:24:19,334 [classy] Setting parameters: {'Omega_m': 0.3311413174185863, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:19,382 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.07282729431478}
2023-07-02 10:24:19,382 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:19,384 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0205962
2023-07-02 10:24:19,384 [model] Computed derived parameters: {}
2023-07-02 10:24:19,384 [mcmc] New sample, #71:
Omega_m:0.3677617
2023-07-02 10:24:19,384 [model] Posterior to be computed for parameters {'Omega_m': 0.3653226599934083}
2023-07-02 10:24:19,384 [prior] Evaluating prior at array([0.36532266])
2023-07-02 10:24:19,384 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:19,384 [model] Got input parameters: {'Omega_m': 0.3653226599934083, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:19,384 [classy] Got parameters {'Omega_m': 0.3653226599934083, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:19,384 [classy] Computing new state
2023-07-02 10:24:19,384 [classy] Setting parameters: {'Omega_m': 0.3653226599934083, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:19,432 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.34053925364174}
2023-07-02 10:24:19,432 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:19,433 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.151254
2023-07-02 10:24:19,433 [model] Computed derived parameters: {}
2023-07-02 10:24:19,434 [mcmc] New sample, #72:
Omega_m:0.3311413
2023-07-02 10:24:19,434 [model] Posterior to be computed for parameters {'Omega_m': 0.36248148250931017}
2023-07-02 10:24:19,434 [prior] Evaluating prior at array([0.36248148])
2023-07-02 10:24:19,434 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:19,434 [model] Got input parameters: {'Omega_m': 0.36248148250931017, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:19,434 [classy] Got parameters {'Omega_m': 0.36248148250931017, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:19,434 [classy] Computing new state
2023-07-02 10:24:19,434 [classy] Setting parameters: {'Omega_m': 0.36248148250931017, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:19,481 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.63824196425236}
2023-07-02 10:24:19,481 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:19,483 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.136321
2023-07-02 10:24:19,483 [model] Computed derived parameters: {}
2023-07-02 10:24:19,483 [mcmc] New sample, #73:
Omega_m:0.3653227
2023-07-02 10:24:19,483 [model] Posterior to be computed for parameters {'Omega_m': 0.3608741839193422}
2023-07-02 10:24:19,483 [prior] Evaluating prior at array([0.36087418])
2023-07-02 10:24:19,483 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:19,483 [model] Got input parameters: {'Omega_m': 0.3608741839193422, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:19,483 [classy] Got parameters {'Omega_m': 0.3608741839193422, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:19,483 [classy] Computing new state
2023-07-02 10:24:19,483 [classy] Setting parameters: {'Omega_m': 0.3608741839193422, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:19,530 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.80761446141827}
2023-07-02 10:24:19,530 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:19,531 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.128177
2023-07-02 10:24:19,531 [model] Computed derived parameters: {}
2023-07-02 10:24:19,532 [mcmc] New sample, #74:
Omega_m:0.3624815
2023-07-02 10:24:19,532 [model] Posterior to be computed for parameters {'Omega_m': 0.37099817135952673}
2023-07-02 10:24:19,532 [prior] Evaluating prior at array([0.37099817])
2023-07-02 10:24:19,532 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:19,532 [model] Got input parameters: {'Omega_m': 0.37099817135952673, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:19,532 [classy] Got parameters {'Omega_m': 0.37099817135952673, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:19,532 [classy] Computing new state
2023-07-02 10:24:19,532 [classy] Setting parameters: {'Omega_m': 0.37099817135952673, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:19,579 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.7522166942065}
2023-07-02 10:24:19,579 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:19,580 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.183098
2023-07-02 10:24:19,580 [model] Computed derived parameters: {}
2023-07-02 10:24:19,581 [mcmc] New sample, #75:
Omega_m:0.3608742
2023-07-02 10:24:19,581 [model] Posterior to be computed for parameters {'Omega_m': 0.3471817922820753}
2023-07-02 10:24:19,581 [prior] Evaluating prior at array([0.34718179])
2023-07-02 10:24:19,581 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:19,581 [model] Got input parameters: {'Omega_m': 0.3471817922820753, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:19,581 [classy] Got parameters {'Omega_m': 0.3471817922820753, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:19,581 [classy] Computing new state
2023-07-02 10:24:19,581 [classy] Setting parameters: {'Omega_m': 0.3471817922820753, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:19,628 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.27946936789536}
2023-07-02 10:24:19,629 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:19,630 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0681091
2023-07-02 10:24:19,630 [model] Computed derived parameters: {}
2023-07-02 10:24:19,630 [mcmc] New sample, #76:
Omega_m:0.3709982
2023-07-02 10:24:19,630 [model] Posterior to be computed for parameters {'Omega_m': 0.3564838863913796}
2023-07-02 10:24:19,630 [prior] Evaluating prior at array([0.35648389])
2023-07-02 10:24:19,631 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:19,631 [model] Got input parameters: {'Omega_m': 0.3564838863913796, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:19,631 [classy] Got parameters {'Omega_m': 0.3564838863913796, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:19,631 [classy] Computing new state
2023-07-02 10:24:19,631 [classy] Setting parameters: {'Omega_m': 0.3564838863913796, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:19,678 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.27387042810247}
2023-07-02 10:24:19,678 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:19,680 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.107075
2023-07-02 10:24:19,680 [model] Computed derived parameters: {}
2023-07-02 10:24:19,680 [mcmc] New sample, #77:
Omega_m:0.3471818
2023-07-02 10:24:19,680 [model] Posterior to be computed for parameters {'Omega_m': 0.33435946501735225}
2023-07-02 10:24:19,680 [prior] Evaluating prior at array([0.33435947])
2023-07-02 10:24:19,680 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:19,680 [model] Got input parameters: {'Omega_m': 0.33435946501735225, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:19,680 [classy] Got parameters {'Omega_m': 0.33435946501735225, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:19,680 [classy] Computing new state
2023-07-02 10:24:19,680 [classy] Setting parameters: {'Omega_m': 0.33435946501735225, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:19,726 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.70681382533994}
2023-07-02 10:24:19,726 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:19,728 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0280223
2023-07-02 10:24:19,728 [model] Computed derived parameters: {}
2023-07-02 10:24:19,728 [mcmc] New sample, #78:
Omega_m:0.3564839
2023-07-02 10:24:19,729 [model] Posterior to be computed for parameters {'Omega_m': 0.2582444406099313}
2023-07-02 10:24:19,729 [prior] Evaluating prior at array([0.25824444])
2023-07-02 10:24:19,729 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:19,729 [model] Got input parameters: {'Omega_m': 0.2582444406099313, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:19,729 [classy] Got parameters {'Omega_m': 0.2582444406099313, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:19,729 [classy] Computing new state
2023-07-02 10:24:19,729 [classy] Setting parameters: {'Omega_m': 0.2582444406099313, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:19,774 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 154.34032164324853}
2023-07-02 10:24:19,774 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:19,777 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.208246
2023-07-02 10:24:19,777 [model] Computed derived parameters: {}
2023-07-02 10:24:19,777 [mcmc] New sample, #79:
Omega_m:0.3343595
2023-07-02 10:24:19,777 [model] Posterior to be computed for parameters {'Omega_m': 0.26137194392774193}
2023-07-02 10:24:19,777 [prior] Evaluating prior at array([0.26137194])
2023-07-02 10:24:19,778 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:19,778 [model] Got input parameters: {'Omega_m': 0.26137194392774193, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:19,778 [classy] Got parameters {'Omega_m': 0.26137194392774193, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:19,778 [classy] Computing new state
2023-07-02 10:24:19,778 [classy] Setting parameters: {'Omega_m': 0.26137194392774193, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:19,824 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.89909479233503}
2023-07-02 10:24:19,824 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:19,827 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.183352
2023-07-02 10:24:19,827 [model] Computed derived parameters: {}
2023-07-02 10:24:19,827 [mcmc] New sample, #80:
Omega_m:0.2582444
2023-07-02 10:24:19,827 [mcmc] Learn + convergence test @ 80 samples accepted.
2023-07-02 10:24:19,827 [mcmc] Ready to check convergence and learn a new proposal covmat
2023-07-02 10:24:19,832 [mcmc] - Acceptance rate: 0.955
2023-07-02 10:24:19,832 [mcmc] - Condition number = 1
2023-07-02 10:24:19,832 [mcmc] - Eigenvalues = array([0.94182869])
2023-07-02 10:24:19,832 [mcmc] - Convergence of means: R-1 = 0.941829 after 64 accepted steps
2023-07-02 10:24:19,832 [mcmc] - Updated covariance matrix of proposal pdf.
2023-07-02 10:24:19,833 [mcmc] array([[0.00120268]])
2023-07-02 10:24:19,842 [mcmc] Dumped checkpoint and progress info, and current covmat.
2023-07-02 10:24:19,843 [model] Posterior to be computed for parameters {'Omega_m': 0.32542810755875745}
2023-07-02 10:24:19,843 [prior] Evaluating prior at array([0.32542811])
2023-07-02 10:24:19,843 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:19,843 [model] Got input parameters: {'Omega_m': 0.32542810755875745, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:19,843 [classy] Got parameters {'Omega_m': 0.32542810755875745, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:19,843 [classy] Computing new state
2023-07-02 10:24:19,843 [classy] Setting parameters: {'Omega_m': 0.32542810755875745, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:19,890 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.7306416384166}
2023-07-02 10:24:19,890 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:19,892 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0101545
2023-07-02 10:24:19,892 [model] Computed derived parameters: {}
2023-07-02 10:24:19,892 [mcmc] New sample, #81:
Omega_m:0.2613719
2023-07-02 10:24:19,892 [model] Posterior to be computed for parameters {'Omega_m': 0.3457700613203705}
2023-07-02 10:24:19,892 [prior] Evaluating prior at array([0.34577006])
2023-07-02 10:24:19,892 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:19,892 [model] Got input parameters: {'Omega_m': 0.3457700613203705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:19,892 [classy] Got parameters {'Omega_m': 0.3457700613203705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:19,892 [classy] Computing new state
2023-07-02 10:24:19,892 [classy] Setting parameters: {'Omega_m': 0.3457700613203705, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:19,939 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.43423342247658}
2023-07-02 10:24:19,939 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:19,941 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0629027
2023-07-02 10:24:19,941 [model] Computed derived parameters: {}
2023-07-02 10:24:19,941 [mcmc] New sample, #82:
Omega_m:0.3254281
2023-07-02 10:24:19,941 [model] Posterior to be computed for parameters {'Omega_m': 0.33183721574281244}
2023-07-02 10:24:19,941 [prior] Evaluating prior at array([0.33183722])
2023-07-02 10:24:19,941 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:19,941 [model] Got input parameters: {'Omega_m': 0.33183721574281244, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:19,942 [classy] Got parameters {'Omega_m': 0.33183721574281244, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:19,942 [classy] Computing new state
2023-07-02 10:24:19,942 [classy] Setting parameters: {'Omega_m': 0.33183721574281244, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:19,988 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.99340982655661}
2023-07-02 10:24:19,988 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:19,990 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0221091
2023-07-02 10:24:19,990 [model] Computed derived parameters: {}
2023-07-02 10:24:19,990 [mcmc] New sample, #83:
Omega_m:0.3457701
2023-07-02 10:24:19,990 [model] Posterior to be computed for parameters {'Omega_m': 0.3324193586031656}
2023-07-02 10:24:19,990 [prior] Evaluating prior at array([0.33241936])
2023-07-02 10:24:19,990 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:19,990 [model] Got input parameters: {'Omega_m': 0.3324193586031656, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:19,990 [classy] Got parameters {'Omega_m': 0.3324193586031656, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:19,990 [classy] Computing new state
2023-07-02 10:24:19,990 [classy] Setting parameters: {'Omega_m': 0.3324193586031656, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:20,038 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.92708801426514}
2023-07-02 10:24:20,038 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:20,040 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0234143
2023-07-02 10:24:20,040 [model] Computed derived parameters: {}
2023-07-02 10:24:20,040 [mcmc] New sample, #84:
Omega_m:0.3318372
2023-07-02 10:24:20,040 [model] Posterior to be computed for parameters {'Omega_m': 0.31960736699763315}
2023-07-02 10:24:20,040 [prior] Evaluating prior at array([0.31960737])
2023-07-02 10:24:20,040 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:20,040 [model] Got input parameters: {'Omega_m': 0.31960736699763315, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:20,041 [classy] Got parameters {'Omega_m': 0.31960736699763315, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:20,041 [classy] Computing new state
2023-07-02 10:24:20,041 [classy] Setting parameters: {'Omega_m': 0.31960736699763315, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:20,088 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.41157702715816}
2023-07-02 10:24:20,088 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:20,090 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00325939
2023-07-02 10:24:20,090 [model] Computed derived parameters: {}
2023-07-02 10:24:20,090 [mcmc] New sample, #85:
Omega_m:0.3324194
2023-07-02 10:24:20,090 [model] Posterior to be computed for parameters {'Omega_m': 0.29390568502253234}
2023-07-02 10:24:20,090 [prior] Evaluating prior at array([0.29390569])
2023-07-02 10:24:20,090 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:20,090 [model] Got input parameters: {'Omega_m': 0.29390568502253234, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:20,090 [classy] Got parameters {'Omega_m': 0.29390568502253234, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:20,090 [classy] Computing new state
2023-07-02 10:24:20,091 [classy] Setting parameters: {'Omega_m': 0.29390568502253234, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:20,137 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.55647482745402}
2023-07-02 10:24:20,137 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:20,139 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0223877
2023-07-02 10:24:20,139 [model] Computed derived parameters: {}
2023-07-02 10:24:20,139 [mcmc] New sample, #86:
Omega_m:0.3196074
2023-07-02 10:24:20,139 [model] Posterior to be computed for parameters {'Omega_m': 0.19149637836383487}
2023-07-02 10:24:20,140 [prior] Evaluating prior at array([0.19149638])
2023-07-02 10:24:20,140 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:20,140 [model] Got input parameters: {'Omega_m': 0.19149637836383487, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:20,140 [classy] Got parameters {'Omega_m': 0.19149637836383487, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:20,140 [classy] Computing new state
2023-07-02 10:24:20,140 [classy] Setting parameters: {'Omega_m': 0.19149637836383487, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:20,186 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 164.97863300954097}
2023-07-02 10:24:20,186 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:20,189 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.26568
2023-07-02 10:24:20,189 [model] Computed derived parameters: {}
2023-07-02 10:24:20,189 [model] Posterior to be computed for parameters {'Omega_m': 0.37944327789657617}
2023-07-02 10:24:20,189 [prior] Evaluating prior at array([0.37944328])
2023-07-02 10:24:20,189 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:20,189 [model] Got input parameters: {'Omega_m': 0.37944327789657617, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:20,189 [classy] Got parameters {'Omega_m': 0.37944327789657617, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:20,189 [classy] Computing new state
2023-07-02 10:24:20,189 [classy] Setting parameters: {'Omega_m': 0.37944327789657617, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:20,236 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 139.8921658789699}
2023-07-02 10:24:20,236 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:20,238 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.235251
2023-07-02 10:24:20,238 [model] Computed derived parameters: {}
2023-07-02 10:24:20,238 [mcmc] New sample, #87:
Omega_m:0.2939057
2023-07-02 10:24:20,239 [model] Posterior to be computed for parameters {'Omega_m': 0.5860772124878907}
2023-07-02 10:24:20,239 [prior] Evaluating prior at array([0.58607721])
2023-07-02 10:24:20,239 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:20,239 [model] Got input parameters: {'Omega_m': 0.5860772124878907, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:20,239 [classy] Got parameters {'Omega_m': 0.5860772124878907, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:20,239 [classy] Computing new state
2023-07-02 10:24:20,239 [classy] Setting parameters: {'Omega_m': 0.5860772124878907, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:20,285 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 123.17651197891021}
2023-07-02 10:24:20,285 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:20,287 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.65186
2023-07-02 10:24:20,287 [model] Computed derived parameters: {}
2023-07-02 10:24:20,287 [model] Posterior to be computed for parameters {'Omega_m': 0.34098361597985255}
2023-07-02 10:24:20,287 [prior] Evaluating prior at array([0.34098362])
2023-07-02 10:24:20,287 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:20,287 [model] Got input parameters: {'Omega_m': 0.34098361597985255, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:20,287 [classy] Got parameters {'Omega_m': 0.34098361597985255, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:20,287 [classy] Computing new state
2023-07-02 10:24:20,288 [classy] Setting parameters: {'Omega_m': 0.34098361597985255, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:20,335 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.96332848611638}
2023-07-02 10:24:20,335 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:20,336 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0466857
2023-07-02 10:24:20,336 [model] Computed derived parameters: {}
2023-07-02 10:24:20,336 [mcmc] New sample, #88:
Omega_m:0.3794433
2023-07-02 10:24:20,337 [model] Posterior to be computed for parameters {'Omega_m': 0.3536749304546155}
2023-07-02 10:24:20,337 [prior] Evaluating prior at array([0.35367493])
2023-07-02 10:24:20,337 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:20,337 [model] Got input parameters: {'Omega_m': 0.3536749304546155, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:20,337 [classy] Got parameters {'Omega_m': 0.3536749304546155, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:20,337 [classy] Computing new state
2023-07-02 10:24:20,337 [classy] Setting parameters: {'Omega_m': 0.3536749304546155, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:20,383 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.5749708267815}
2023-07-02 10:24:20,383 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:20,385 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0944713
2023-07-02 10:24:20,385 [model] Computed derived parameters: {}
2023-07-02 10:24:20,385 [mcmc] New sample, #89:
Omega_m:0.3409836
2023-07-02 10:24:20,385 [model] Posterior to be computed for parameters {'Omega_m': 0.3551905003976208}
2023-07-02 10:24:20,385 [prior] Evaluating prior at array([0.3551905])
2023-07-02 10:24:20,385 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:20,385 [model] Got input parameters: {'Omega_m': 0.3551905003976208, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:20,385 [classy] Got parameters {'Omega_m': 0.3551905003976208, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:20,385 [classy] Computing new state
2023-07-02 10:24:20,385 [classy] Setting parameters: {'Omega_m': 0.3551905003976208, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:20,432 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.41224135889237}
2023-07-02 10:24:20,432 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:20,434 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.101183
2023-07-02 10:24:20,434 [model] Computed derived parameters: {}
2023-07-02 10:24:20,434 [mcmc] New sample, #90:
Omega_m:0.3536749
2023-07-02 10:24:20,434 [model] Posterior to be computed for parameters {'Omega_m': 0.38523073417392883}
2023-07-02 10:24:20,434 [prior] Evaluating prior at array([0.38523073])
2023-07-02 10:24:20,434 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:20,434 [model] Got input parameters: {'Omega_m': 0.38523073417392883, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:20,434 [classy] Got parameters {'Omega_m': 0.38523073417392883, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:20,434 [classy] Computing new state
2023-07-02 10:24:20,434 [classy] Setting parameters: {'Omega_m': 0.38523073417392883, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:20,481 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 139.31308953242507}
2023-07-02 10:24:20,481 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:20,483 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.274136
2023-07-02 10:24:20,483 [model] Computed derived parameters: {}
2023-07-02 10:24:20,483 [mcmc] New sample, #91:
Omega_m:0.3551905
2023-07-02 10:24:20,483 [model] Posterior to be computed for parameters {'Omega_m': 0.37130300838940666}
2023-07-02 10:24:20,483 [prior] Evaluating prior at array([0.37130301])
2023-07-02 10:24:20,483 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:20,483 [model] Got input parameters: {'Omega_m': 0.37130300838940666, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:20,483 [classy] Got parameters {'Omega_m': 0.37130300838940666, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:20,483 [classy] Computing new state
2023-07-02 10:24:20,483 [classy] Setting parameters: {'Omega_m': 0.37130300838940666, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:20,530 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.72085199319577}
2023-07-02 10:24:20,530 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:20,532 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.184883
2023-07-02 10:24:20,532 [model] Computed derived parameters: {}
2023-07-02 10:24:20,532 [mcmc] New sample, #92:
Omega_m:0.3852307
2023-07-02 10:24:20,532 [model] Posterior to be computed for parameters {'Omega_m': 0.1631398791071817}
2023-07-02 10:24:20,532 [prior] Evaluating prior at array([0.16313988])
2023-07-02 10:24:20,532 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:20,532 [model] Got input parameters: {'Omega_m': 0.1631398791071817, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:20,532 [classy] Got parameters {'Omega_m': 0.1631398791071817, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:20,532 [classy] Computing new state
2023-07-02 10:24:20,532 [classy] Setting parameters: {'Omega_m': 0.1631398791071817, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:20,578 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 170.37469504569316}
2023-07-02 10:24:20,578 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:20,580 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.12325
2023-07-02 10:24:20,580 [model] Computed derived parameters: {}
2023-07-02 10:24:20,581 [model] Posterior to be computed for parameters {'Omega_m': 0.3267299874396019}
2023-07-02 10:24:20,581 [prior] Evaluating prior at array([0.32672999])
2023-07-02 10:24:20,581 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:20,581 [model] Got input parameters: {'Omega_m': 0.3267299874396019, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:20,581 [classy] Got parameters {'Omega_m': 0.3267299874396019, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:20,581 [classy] Computing new state
2023-07-02 10:24:20,581 [classy] Setting parameters: {'Omega_m': 0.3267299874396019, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:20,627 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.57983036946771}
2023-07-02 10:24:20,627 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:20,629 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0122194
2023-07-02 10:24:20,629 [model] Computed derived parameters: {}
2023-07-02 10:24:20,629 [mcmc] New sample, #93:
Omega_m:0.371303
2023-07-02 10:24:20,629 [model] Posterior to be computed for parameters {'Omega_m': 0.4607339937525602}
2023-07-02 10:24:20,630 [prior] Evaluating prior at array([0.46073399])
2023-07-02 10:24:20,630 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:20,630 [model] Got input parameters: {'Omega_m': 0.4607339937525602, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:20,630 [classy] Got parameters {'Omega_m': 0.4607339937525602, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:20,630 [classy] Computing new state
2023-07-02 10:24:20,630 [classy] Setting parameters: {'Omega_m': 0.4607339937525602, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:20,679 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 132.43715218301216}
2023-07-02 10:24:20,679 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:20,682 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.974105
2023-07-02 10:24:20,682 [model] Computed derived parameters: {}
2023-07-02 10:24:20,682 [model] Posterior to be computed for parameters {'Omega_m': 0.377051598659586}
2023-07-02 10:24:20,682 [prior] Evaluating prior at array([0.3770516])
2023-07-02 10:24:20,682 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:20,682 [model] Got input parameters: {'Omega_m': 0.377051598659586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:20,682 [classy] Got parameters {'Omega_m': 0.377051598659586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:20,682 [classy] Computing new state
2023-07-02 10:24:20,682 [classy] Setting parameters: {'Omega_m': 0.377051598659586, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:20,730 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.13388886584093}
2023-07-02 10:24:20,731 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:20,732 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.219919
2023-07-02 10:24:20,732 [model] Computed derived parameters: {}
2023-07-02 10:24:20,733 [mcmc] New sample, #94:
Omega_m:0.32673
2023-07-02 10:24:20,733 [model] Posterior to be computed for parameters {'Omega_m': 0.35422236570857696}
2023-07-02 10:24:20,733 [prior] Evaluating prior at array([0.35422237])
2023-07-02 10:24:20,733 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:20,733 [model] Got input parameters: {'Omega_m': 0.35422236570857696, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:20,733 [classy] Got parameters {'Omega_m': 0.35422236570857696, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:20,733 [classy] Computing new state
2023-07-02 10:24:20,733 [classy] Setting parameters: {'Omega_m': 0.35422236570857696, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:20,778 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.51611974504237}
2023-07-02 10:24:20,778 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:20,780 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0968715
2023-07-02 10:24:20,781 [model] Computed derived parameters: {}
2023-07-02 10:24:20,781 [mcmc] New sample, #95:
Omega_m:0.3770516
2023-07-02 10:24:20,781 [model] Posterior to be computed for parameters {'Omega_m': 0.6461783449436684}
2023-07-02 10:24:20,781 [prior] Evaluating prior at array([0.64617834])
2023-07-02 10:24:20,781 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:20,781 [model] Got input parameters: {'Omega_m': 0.6461783449436684, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:20,781 [classy] Got parameters {'Omega_m': 0.6461783449436684, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:20,781 [classy] Computing new state
2023-07-02 10:24:20,781 [classy] Setting parameters: {'Omega_m': 0.6461783449436684, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:20,826 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 119.43955990522315}
2023-07-02 10:24:20,826 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:20,828 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.58528
2023-07-02 10:24:20,828 [model] Computed derived parameters: {}
2023-07-02 10:24:20,828 [mcmc] New sample, #96:
Omega_m:0.3542224
2023-07-02 10:24:20,828 [model] Posterior to be computed for parameters {'Omega_m': 0.7278821175440413}
2023-07-02 10:24:20,828 [prior] Evaluating prior at array([0.72788212])
2023-07-02 10:24:20,828 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:20,829 [model] Got input parameters: {'Omega_m': 0.7278821175440413, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:20,829 [classy] Got parameters {'Omega_m': 0.7278821175440413, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:20,829 [classy] Computing new state
2023-07-02 10:24:20,829 [classy] Setting parameters: {'Omega_m': 0.7278821175440413, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:20,873 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 114.91387472642691}
2023-07-02 10:24:20,873 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:20,875 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.92667
2023-07-02 10:24:20,875 [model] Computed derived parameters: {}
2023-07-02 10:24:20,875 [mcmc] New sample, #97:
Omega_m:0.6461783
2023-07-02 10:24:20,875 [model] Posterior to be computed for parameters {'Omega_m': 0.7227308727852103}
2023-07-02 10:24:20,875 [prior] Evaluating prior at array([0.72273087])
2023-07-02 10:24:20,875 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:20,875 [model] Got input parameters: {'Omega_m': 0.7227308727852103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:20,876 [classy] Got parameters {'Omega_m': 0.7227308727852103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:20,876 [classy] Computing new state
2023-07-02 10:24:20,876 [classy] Setting parameters: {'Omega_m': 0.7227308727852103, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:20,921 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 115.182645547493}
2023-07-02 10:24:20,921 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:20,923 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.84033
2023-07-02 10:24:20,923 [model] Computed derived parameters: {}
2023-07-02 10:24:20,923 [mcmc] New sample, #98:
Omega_m:0.7278821
2023-07-02 10:24:20,923 [model] Posterior to be computed for parameters {'Omega_m': 0.7644760241456}
2023-07-02 10:24:20,923 [prior] Evaluating prior at array([0.76447602])
2023-07-02 10:24:20,923 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:20,923 [model] Got input parameters: {'Omega_m': 0.7644760241456, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:20,923 [classy] Got parameters {'Omega_m': 0.7644760241456, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:20,923 [classy] Computing new state
2023-07-02 10:24:20,923 [classy] Setting parameters: {'Omega_m': 0.7644760241456, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:20,969 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 113.06243018594267}
2023-07-02 10:24:20,969 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:20,970 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.54479
2023-07-02 10:24:20,971 [model] Computed derived parameters: {}
2023-07-02 10:24:20,971 [model] Posterior to be computed for parameters {'Omega_m': 0.8284890662465013}
2023-07-02 10:24:20,971 [prior] Evaluating prior at array([0.82848907])
2023-07-02 10:24:20,971 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:20,971 [model] Got input parameters: {'Omega_m': 0.8284890662465013, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:20,971 [classy] Got parameters {'Omega_m': 0.8284890662465013, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:20,971 [classy] Computing new state
2023-07-02 10:24:20,971 [classy] Setting parameters: {'Omega_m': 0.8284890662465013, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:21,017 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 110.04678782018938}
2023-07-02 10:24:21,017 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:21,019 [bao_likelihood.baolikelihood] Computed log-likelihood = -6.64127
2023-07-02 10:24:21,019 [model] Computed derived parameters: {}
2023-07-02 10:24:21,019 [model] Posterior to be computed for parameters {'Omega_m': 0.783053075147835}
2023-07-02 10:24:21,019 [prior] Evaluating prior at array([0.78305308])
2023-07-02 10:24:21,019 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:21,019 [model] Got input parameters: {'Omega_m': 0.783053075147835, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:21,019 [classy] Got parameters {'Omega_m': 0.783053075147835, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:21,019 [classy] Computing new state
2023-07-02 10:24:21,020 [classy] Setting parameters: {'Omega_m': 0.783053075147835, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:21,065 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 112.15936018924137}
2023-07-02 10:24:21,065 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:21,067 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.86135
2023-07-02 10:24:21,067 [model] Computed derived parameters: {}
2023-07-02 10:24:21,067 [mcmc] New sample, #99:
Omega_m:0.7227309
2023-07-02 10:24:21,067 [model] Posterior to be computed for parameters {'Omega_m': 1.1694945245795805}
2023-07-02 10:24:21,067 [prior] Evaluating prior at array([1.16949452])
2023-07-02 10:24:21,067 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:21,067 [model] Posterior to be computed for parameters {'Omega_m': 0.7729589770581474}
2023-07-02 10:24:21,068 [prior] Evaluating prior at array([0.77295898])
2023-07-02 10:24:21,068 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:21,068 [model] Got input parameters: {'Omega_m': 0.7729589770581474, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:21,068 [classy] Got parameters {'Omega_m': 0.7729589770581474, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:21,068 [classy] Computing new state
2023-07-02 10:24:21,068 [classy] Setting parameters: {'Omega_m': 0.7729589770581474, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:21,113 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 112.64708186328386}
2023-07-02 10:24:21,114 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:21,115 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.68915
2023-07-02 10:24:21,115 [model] Computed derived parameters: {}
2023-07-02 10:24:21,115 [mcmc] New sample, #100:
Omega_m:0.7830531
2023-07-02 10:24:21,115 [model] Posterior to be computed for parameters {'Omega_m': 0.5502608978661879}
2023-07-02 10:24:21,115 [prior] Evaluating prior at array([0.5502609])
2023-07-02 10:24:21,116 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:21,116 [model] Got input parameters: {'Omega_m': 0.5502608978661879, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:21,116 [classy] Got parameters {'Omega_m': 0.5502608978661879, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:21,116 [classy] Computing new state
2023-07-02 10:24:21,116 [classy] Setting parameters: {'Omega_m': 0.5502608978661879, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:21,163 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 125.59910230588486}
2023-07-02 10:24:21,163 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:21,165 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.1275
2023-07-02 10:24:21,165 [model] Computed derived parameters: {}
2023-07-02 10:24:21,165 [mcmc] New sample, #101:
Omega_m:0.772959
2023-07-02 10:24:21,165 [model] Posterior to be computed for parameters {'Omega_m': 0.550306699150419}
2023-07-02 10:24:21,165 [prior] Evaluating prior at array([0.5503067])
2023-07-02 10:24:21,166 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:21,166 [model] Got input parameters: {'Omega_m': 0.550306699150419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:21,166 [classy] Got parameters {'Omega_m': 0.550306699150419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:21,166 [classy] Computing new state
2023-07-02 10:24:21,166 [classy] Setting parameters: {'Omega_m': 0.550306699150419, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:21,212 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 125.59590136295017}
2023-07-02 10:24:21,212 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:21,214 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.12815
2023-07-02 10:24:21,214 [model] Computed derived parameters: {}
2023-07-02 10:24:21,214 [mcmc] New sample, #102:
Omega_m:0.5502609
2023-07-02 10:24:21,214 [model] Posterior to be computed for parameters {'Omega_m': 0.4009189150853601}
2023-07-02 10:24:21,214 [prior] Evaluating prior at array([0.40091892])
2023-07-02 10:24:21,214 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:21,214 [model] Got input parameters: {'Omega_m': 0.4009189150853601, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:21,214 [classy] Got parameters {'Omega_m': 0.4009189150853601, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:21,214 [classy] Computing new state
2023-07-02 10:24:21,214 [classy] Setting parameters: {'Omega_m': 0.4009189150853601, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:21,261 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 137.78373744380585}
2023-07-02 10:24:21,261 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:21,262 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.391561
2023-07-02 10:24:21,262 [model] Computed derived parameters: {}
2023-07-02 10:24:21,262 [mcmc] New sample, #103:
Omega_m:0.5503067
2023-07-02 10:24:21,263 [model] Posterior to be computed for parameters {'Omega_m': 0.4814450421490043}
2023-07-02 10:24:21,263 [prior] Evaluating prior at array([0.48144504])
2023-07-02 10:24:21,263 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:21,263 [model] Got input parameters: {'Omega_m': 0.4814450421490043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:21,263 [classy] Got parameters {'Omega_m': 0.4814450421490043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:21,263 [classy] Computing new state
2023-07-02 10:24:21,263 [classy] Setting parameters: {'Omega_m': 0.4814450421490043, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:21,310 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.74337788323268}
2023-07-02 10:24:21,310 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:21,312 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.21606
2023-07-02 10:24:21,312 [model] Computed derived parameters: {}
2023-07-02 10:24:21,312 [model] Posterior to be computed for parameters {'Omega_m': 0.3238356064504956}
2023-07-02 10:24:21,312 [prior] Evaluating prior at array([0.32383561])
2023-07-02 10:24:21,312 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:21,312 [model] Got input parameters: {'Omega_m': 0.3238356064504956, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:21,312 [classy] Got parameters {'Omega_m': 0.3238356064504956, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:21,312 [classy] Computing new state
2023-07-02 10:24:21,312 [classy] Setting parameters: {'Omega_m': 0.3238356064504956, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:21,360 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.91585043328428}
2023-07-02 10:24:21,360 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:21,362 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00788591
2023-07-02 10:24:21,362 [model] Computed derived parameters: {}
2023-07-02 10:24:21,362 [mcmc] New sample, #104:
Omega_m:0.4009189
2023-07-02 10:24:21,362 [model] Posterior to be computed for parameters {'Omega_m': 0.2827052887679717}
2023-07-02 10:24:21,362 [prior] Evaluating prior at array([0.28270529])
2023-07-02 10:24:21,362 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:21,362 [model] Got input parameters: {'Omega_m': 0.2827052887679717, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:21,362 [classy] Got parameters {'Omega_m': 0.2827052887679717, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:21,362 [classy] Computing new state
2023-07-02 10:24:21,362 [classy] Setting parameters: {'Omega_m': 0.2827052887679717, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:21,410 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.002847417495}
2023-07-02 10:24:21,410 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:21,412 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0588913
2023-07-02 10:24:21,412 [model] Computed derived parameters: {}
2023-07-02 10:24:21,412 [mcmc] New sample, #105:
Omega_m:0.3238356
2023-07-02 10:24:21,412 [model] Posterior to be computed for parameters {'Omega_m': 0.43645950344663065}
2023-07-02 10:24:21,412 [prior] Evaluating prior at array([0.4364595])
2023-07-02 10:24:21,412 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:21,412 [model] Got input parameters: {'Omega_m': 0.43645950344663065, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:21,412 [classy] Got parameters {'Omega_m': 0.43645950344663065, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:21,412 [classy] Computing new state
2023-07-02 10:24:21,412 [classy] Setting parameters: {'Omega_m': 0.43645950344663065, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:21,460 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 134.5206726093113}
2023-07-02 10:24:21,460 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:21,462 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.714777
2023-07-02 10:24:21,462 [model] Computed derived parameters: {}
2023-07-02 10:24:21,462 [model] Posterior to be computed for parameters {'Omega_m': 0.26269599480400374}
2023-07-02 10:24:21,462 [prior] Evaluating prior at array([0.26269599])
2023-07-02 10:24:21,462 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:21,462 [model] Got input parameters: {'Omega_m': 0.26269599480400374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:21,462 [classy] Got parameters {'Omega_m': 0.26269599480400374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:21,462 [classy] Computing new state
2023-07-02 10:24:21,462 [classy] Setting parameters: {'Omega_m': 0.26269599480400374, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:21,510 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.71363448145135}
2023-07-02 10:24:21,510 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:21,511 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.173353
2023-07-02 10:24:21,512 [model] Computed derived parameters: {}
2023-07-02 10:24:21,512 [mcmc] New sample, #106:
Omega_m:0.2827053
2023-07-02 10:24:21,512 [model] Posterior to be computed for parameters {'Omega_m': 0.23330859700781822}
2023-07-02 10:24:21,512 [prior] Evaluating prior at array([0.2333086])
2023-07-02 10:24:21,512 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:21,512 [model] Got input parameters: {'Omega_m': 0.23330859700781822, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:21,512 [classy] Got parameters {'Omega_m': 0.23330859700781822, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:21,512 [classy] Computing new state
2023-07-02 10:24:21,512 [classy] Setting parameters: {'Omega_m': 0.23330859700781822, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:21,560 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 158.0257544704451}
2023-07-02 10:24:21,560 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:21,562 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.476286
2023-07-02 10:24:21,562 [model] Computed derived parameters: {}
2023-07-02 10:24:21,562 [mcmc] New sample, #107:
Omega_m:0.262696
2023-07-02 10:24:21,562 [model] Posterior to be computed for parameters {'Omega_m': 0.223108250031336}
2023-07-02 10:24:21,562 [prior] Evaluating prior at array([0.22310825])
2023-07-02 10:24:21,562 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:21,562 [model] Got input parameters: {'Omega_m': 0.223108250031336, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:21,562 [classy] Got parameters {'Omega_m': 0.223108250031336, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:21,562 [classy] Computing new state
2023-07-02 10:24:21,562 [classy] Setting parameters: {'Omega_m': 0.223108250031336, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:21,610 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 159.62597526601968}
2023-07-02 10:24:21,610 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:21,611 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.62558
2023-07-02 10:24:21,611 [model] Computed derived parameters: {}
2023-07-02 10:24:21,611 [mcmc] New sample, #108:
Omega_m:0.2333086
2023-07-02 10:24:21,612 [model] Posterior to be computed for parameters {'Omega_m': 0.18301431251518846}
2023-07-02 10:24:21,612 [prior] Evaluating prior at array([0.18301431])
2023-07-02 10:24:21,612 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:21,612 [model] Got input parameters: {'Omega_m': 0.18301431251518846, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:21,612 [classy] Got parameters {'Omega_m': 0.18301431251518846, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:21,612 [classy] Computing new state
2023-07-02 10:24:21,612 [classy] Setting parameters: {'Omega_m': 0.18301431251518846, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:21,660 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 166.52807996718136}
2023-07-02 10:24:21,660 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:21,662 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.4905
2023-07-02 10:24:21,662 [model] Computed derived parameters: {}
2023-07-02 10:24:21,662 [model] Posterior to be computed for parameters {'Omega_m': 0.26142035989498996}
2023-07-02 10:24:21,662 [prior] Evaluating prior at array([0.26142036])
2023-07-02 10:24:21,662 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:21,662 [model] Got input parameters: {'Omega_m': 0.26142035989498996, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:21,663 [classy] Got parameters {'Omega_m': 0.26142035989498996, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:21,663 [classy] Computing new state
2023-07-02 10:24:21,663 [classy] Setting parameters: {'Omega_m': 0.26142035989498996, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:21,710 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.8923003116362}
2023-07-02 10:24:21,710 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:21,712 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.182981
2023-07-02 10:24:21,712 [model] Computed derived parameters: {}
2023-07-02 10:24:21,712 [mcmc] New sample, #109:
Omega_m:0.2231083
2023-07-02 10:24:21,712 [model] Posterior to be computed for parameters {'Omega_m': 0.2842301996994825}
2023-07-02 10:24:21,712 [prior] Evaluating prior at array([0.2842302])
2023-07-02 10:24:21,712 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:21,712 [model] Got input parameters: {'Omega_m': 0.2842301996994825, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:21,712 [classy] Got parameters {'Omega_m': 0.2842301996994825, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:21,712 [classy] Computing new state
2023-07-02 10:24:21,712 [classy] Setting parameters: {'Omega_m': 0.2842301996994825, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:21,760 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.80303648186978}
2023-07-02 10:24:21,760 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:21,762 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.052822
2023-07-02 10:24:21,762 [model] Computed derived parameters: {}
2023-07-02 10:24:21,762 [mcmc] New sample, #110:
Omega_m:0.2614204
2023-07-02 10:24:21,762 [model] Posterior to be computed for parameters {'Omega_m': 0.3036936918666723}
2023-07-02 10:24:21,762 [prior] Evaluating prior at array([0.30369369])
2023-07-02 10:24:21,762 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:21,762 [model] Got input parameters: {'Omega_m': 0.3036936918666723, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:21,762 [classy] Got parameters {'Omega_m': 0.3036936918666723, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:21,762 [classy] Computing new state
2023-07-02 10:24:21,762 [classy] Setting parameters: {'Omega_m': 0.3036936918666723, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:21,810 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.3312278802238}
2023-07-02 10:24:21,810 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:21,812 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00504624
2023-07-02 10:24:21,812 [model] Computed derived parameters: {}
2023-07-02 10:24:21,812 [mcmc] New sample, #111:
Omega_m:0.2842302
2023-07-02 10:24:21,812 [model] Posterior to be computed for parameters {'Omega_m': 0.30484146752666286}
2023-07-02 10:24:21,812 [prior] Evaluating prior at array([0.30484147])
2023-07-02 10:24:21,812 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:21,812 [model] Got input parameters: {'Omega_m': 0.30484146752666286, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:21,812 [classy] Got parameters {'Omega_m': 0.30484146752666286, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:21,812 [classy] Computing new state
2023-07-02 10:24:21,812 [classy] Setting parameters: {'Omega_m': 0.30484146752666286, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:21,860 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.1898364580859}
2023-07-02 10:24:21,860 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:21,862 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00385336
2023-07-02 10:24:21,862 [model] Computed derived parameters: {}
2023-07-02 10:24:21,862 [mcmc] New sample, #112:
Omega_m:0.3036937
2023-07-02 10:24:21,862 [model] Posterior to be computed for parameters {'Omega_m': 0.2891974391020737}
2023-07-02 10:24:21,862 [prior] Evaluating prior at array([0.28919744])
2023-07-02 10:24:21,862 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:21,862 [model] Got input parameters: {'Omega_m': 0.2891974391020737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:21,862 [classy] Got parameters {'Omega_m': 0.2891974391020737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:21,862 [classy] Computing new state
2023-07-02 10:24:21,863 [classy] Setting parameters: {'Omega_m': 0.2891974391020737, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:21,910 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.15855523916892}
2023-07-02 10:24:21,910 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:21,912 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0354848
2023-07-02 10:24:21,912 [model] Computed derived parameters: {}
2023-07-02 10:24:21,912 [mcmc] New sample, #113:
Omega_m:0.3048415
2023-07-02 10:24:21,912 [model] Posterior to be computed for parameters {'Omega_m': 0.30566336299947927}
2023-07-02 10:24:21,912 [prior] Evaluating prior at array([0.30566336])
2023-07-02 10:24:21,912 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:21,912 [model] Got input parameters: {'Omega_m': 0.30566336299947927, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:21,912 [classy] Got parameters {'Omega_m': 0.30566336299947927, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:21,912 [classy] Computing new state
2023-07-02 10:24:21,912 [classy] Setting parameters: {'Omega_m': 0.30566336299947927, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:21,960 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.08887717484674}
2023-07-02 10:24:21,960 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:21,962 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00310436
2023-07-02 10:24:21,962 [model] Computed derived parameters: {}
2023-07-02 10:24:21,962 [mcmc] New sample, #114:
Omega_m:0.2891974
2023-07-02 10:24:21,962 [model] Posterior to be computed for parameters {'Omega_m': 0.0890050969170921}
2023-07-02 10:24:21,962 [prior] Evaluating prior at array([0.0890051])
2023-07-02 10:24:21,962 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:21,962 [model] Posterior to be computed for parameters {'Omega_m': 0.35162412565256884}
2023-07-02 10:24:21,962 [prior] Evaluating prior at array([0.35162413])
2023-07-02 10:24:21,962 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:21,962 [model] Got input parameters: {'Omega_m': 0.35162412565256884, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:21,962 [classy] Got parameters {'Omega_m': 0.35162412565256884, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:21,962 [classy] Computing new state
2023-07-02 10:24:21,962 [classy] Setting parameters: {'Omega_m': 0.35162412565256884, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:22,010 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.79619655141454}
2023-07-02 10:24:22,010 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:22,013 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0857218
2023-07-02 10:24:22,013 [model] Computed derived parameters: {}
2023-07-02 10:24:22,014 [mcmc] New sample, #115:
Omega_m:0.3056634
2023-07-02 10:24:22,014 [model] Posterior to be computed for parameters {'Omega_m': 0.4427614040795856}
2023-07-02 10:24:22,014 [prior] Evaluating prior at array([0.4427614])
2023-07-02 10:24:22,014 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:22,014 [model] Got input parameters: {'Omega_m': 0.4427614040795856, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:22,014 [classy] Got parameters {'Omega_m': 0.4427614040795856, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:22,014 [classy] Computing new state
2023-07-02 10:24:22,014 [classy] Setting parameters: {'Omega_m': 0.4427614040795856, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:22,063 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 133.96905594953483}
2023-07-02 10:24:22,063 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:22,065 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.779368
2023-07-02 10:24:22,065 [model] Computed derived parameters: {}
2023-07-02 10:24:22,065 [mcmc] New sample, #116:
Omega_m:0.3516241
2023-07-02 10:24:22,065 [model] Posterior to be computed for parameters {'Omega_m': 0.3935343636714861}
2023-07-02 10:24:22,066 [prior] Evaluating prior at array([0.39353436])
2023-07-02 10:24:22,066 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:22,066 [model] Got input parameters: {'Omega_m': 0.3935343636714861, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:22,066 [classy] Got parameters {'Omega_m': 0.3935343636714861, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:22,066 [classy] Computing new state
2023-07-02 10:24:22,066 [classy] Setting parameters: {'Omega_m': 0.3935343636714861, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:22,113 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 138.49639854759803}
2023-07-02 10:24:22,113 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:22,115 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.334174
2023-07-02 10:24:22,115 [model] Computed derived parameters: {}
2023-07-02 10:24:22,115 [mcmc] New sample, #117:
Omega_m:0.4427614
2023-07-02 10:24:22,115 [model] Posterior to be computed for parameters {'Omega_m': 0.3823420602657087}
2023-07-02 10:24:22,115 [prior] Evaluating prior at array([0.38234206])
2023-07-02 10:24:22,115 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:22,115 [model] Got input parameters: {'Omega_m': 0.3823420602657087, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:22,115 [classy] Got parameters {'Omega_m': 0.3823420602657087, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:22,115 [classy] Computing new state
2023-07-02 10:24:22,115 [classy] Setting parameters: {'Omega_m': 0.3823420602657087, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:22,164 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 139.6010943040304}
2023-07-02 10:24:22,164 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:22,166 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.254415
2023-07-02 10:24:22,166 [model] Computed derived parameters: {}
2023-07-02 10:24:22,166 [mcmc] New sample, #118:
Omega_m:0.3935344
2023-07-02 10:24:22,166 [model] Posterior to be computed for parameters {'Omega_m': 0.46741677759013117}
2023-07-02 10:24:22,166 [prior] Evaluating prior at array([0.46741678])
2023-07-02 10:24:22,166 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:22,166 [model] Got input parameters: {'Omega_m': 0.46741677759013117, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:22,166 [classy] Got parameters {'Omega_m': 0.46741677759013117, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:22,166 [classy] Computing new state
2023-07-02 10:24:22,166 [classy] Setting parameters: {'Omega_m': 0.46741677759013117, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:22,215 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 131.8825220726529}
2023-07-02 10:24:22,215 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:22,217 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.05023
2023-07-02 10:24:22,217 [model] Computed derived parameters: {}
2023-07-02 10:24:22,217 [model] Posterior to be computed for parameters {'Omega_m': 0.3622509917754513}
2023-07-02 10:24:22,217 [prior] Evaluating prior at array([0.36225099])
2023-07-02 10:24:22,217 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:22,217 [model] Got input parameters: {'Omega_m': 0.3622509917754513, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:22,217 [classy] Got parameters {'Omega_m': 0.3622509917754513, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:22,217 [classy] Computing new state
2023-07-02 10:24:22,217 [classy] Setting parameters: {'Omega_m': 0.3622509917754513, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:22,266 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.66248566384328}
2023-07-02 10:24:22,266 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:22,268 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.135139
2023-07-02 10:24:22,268 [model] Computed derived parameters: {}
2023-07-02 10:24:22,268 [mcmc] New sample, #119:
Omega_m:0.3823421
2023-07-02 10:24:22,268 [model] Posterior to be computed for parameters {'Omega_m': 0.3407912420860704}
2023-07-02 10:24:22,268 [prior] Evaluating prior at array([0.34079124])
2023-07-02 10:24:22,268 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:22,268 [model] Got input parameters: {'Omega_m': 0.3407912420860704, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:22,268 [classy] Got parameters {'Omega_m': 0.3407912420860704, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:22,268 [classy] Computing new state
2023-07-02 10:24:22,268 [classy] Setting parameters: {'Omega_m': 0.3407912420860704, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:22,315 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.98473571356905}
2023-07-02 10:24:22,316 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:22,318 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.046081
2023-07-02 10:24:22,318 [model] Computed derived parameters: {}
2023-07-02 10:24:22,318 [mcmc] New sample, #120:
Omega_m:0.362251
2023-07-02 10:24:22,318 [mcmc] Learn + convergence test @ 120 samples accepted.
2023-07-02 10:24:22,318 [mcmc] Ready to check convergence and learn a new proposal covmat
2023-07-02 10:24:22,325 [mcmc] - Acceptance rate: 0.865
2023-07-02 10:24:22,326 [mcmc] - Condition number = 1
2023-07-02 10:24:22,326 [mcmc] - Eigenvalues = array([0.19826185])
2023-07-02 10:24:22,326 [mcmc] - Convergence of means: R-1 = 0.198262 after 96 accepted steps
2023-07-02 10:24:22,326 [mcmc] - Updated covariance matrix of proposal pdf.
2023-07-02 10:24:22,326 [mcmc] array([[0.01064517]])
2023-07-02 10:24:22,337 [mcmc] Dumped checkpoint and progress info, and current covmat.
2023-07-02 10:24:22,337 [model] Posterior to be computed for parameters {'Omega_m': 0.14206225343130843}
2023-07-02 10:24:22,337 [prior] Evaluating prior at array([0.14206225])
2023-07-02 10:24:22,337 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:22,338 [model] Got input parameters: {'Omega_m': 0.14206225343130843, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:22,338 [classy] Got parameters {'Omega_m': 0.14206225343130843, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:22,338 [classy] Computing new state
2023-07-02 10:24:22,338 [classy] Setting parameters: {'Omega_m': 0.14206225343130843, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:22,385 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 174.82952700610903}
2023-07-02 10:24:22,385 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:22,387 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.9856
2023-07-02 10:24:22,387 [model] Computed derived parameters: {}
2023-07-02 10:24:22,387 [mcmc] New sample, #121:
Omega_m:0.3407912
2023-07-02 10:24:22,387 [model] Posterior to be computed for parameters {'Omega_m': -0.33651803915215794}
2023-07-02 10:24:22,387 [prior] Evaluating prior at array([-0.33651804])
2023-07-02 10:24:22,387 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:22,387 [model] Posterior to be computed for parameters {'Omega_m': 0.06128268951356944}
2023-07-02 10:24:22,387 [prior] Evaluating prior at array([0.06128269])
2023-07-02 10:24:22,387 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:22,387 [model] Posterior to be computed for parameters {'Omega_m': 0.4818798357930848}
2023-07-02 10:24:22,387 [prior] Evaluating prior at array([0.48187984])
2023-07-02 10:24:22,387 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:22,388 [model] Got input parameters: {'Omega_m': 0.4818798357930848, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:22,388 [classy] Got parameters {'Omega_m': 0.4818798357930848, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:22,388 [classy] Computing new state
2023-07-02 10:24:22,388 [classy] Setting parameters: {'Omega_m': 0.4818798357930848, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:22,435 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.70860136326027}
2023-07-02 10:24:22,435 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:22,437 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.22132
2023-07-02 10:24:22,437 [model] Computed derived parameters: {}
2023-07-02 10:24:22,437 [mcmc] New sample, #122:
Omega_m:0.1420623
2023-07-02 10:24:22,437 [model] Posterior to be computed for parameters {'Omega_m': 0.12258725916394797}
2023-07-02 10:24:22,437 [prior] Evaluating prior at array([0.12258726])
2023-07-02 10:24:22,437 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:22,437 [model] Got input parameters: {'Omega_m': 0.12258725916394797, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:22,437 [classy] Got parameters {'Omega_m': 0.12258725916394797, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:22,437 [classy] Computing new state
2023-07-02 10:24:22,437 [classy] Setting parameters: {'Omega_m': 0.12258725916394797, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:22,483 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 179.34986909166238}
2023-07-02 10:24:22,483 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:22,485 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.99807
2023-07-02 10:24:22,485 [model] Computed derived parameters: {}
2023-07-02 10:24:22,485 [model] Posterior to be computed for parameters {'Omega_m': 0.4677104717372182}
2023-07-02 10:24:22,485 [prior] Evaluating prior at array([0.46771047])
2023-07-02 10:24:22,486 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:22,486 [model] Got input parameters: {'Omega_m': 0.4677104717372182, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:22,486 [classy] Got parameters {'Omega_m': 0.4677104717372182, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:22,486 [classy] Computing new state
2023-07-02 10:24:22,486 [classy] Setting parameters: {'Omega_m': 0.4677104717372182, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:22,532 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 131.85832797726198}
2023-07-02 10:24:22,532 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:22,534 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.05362
2023-07-02 10:24:22,534 [model] Computed derived parameters: {}
2023-07-02 10:24:22,534 [mcmc] New sample, #123:
Omega_m:0.4818798
2023-07-02 10:24:22,534 [model] Posterior to be computed for parameters {'Omega_m': 0.7341476064363232}
2023-07-02 10:24:22,534 [prior] Evaluating prior at array([0.73414761])
2023-07-02 10:24:22,534 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:22,534 [model] Got input parameters: {'Omega_m': 0.7341476064363232, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:22,534 [classy] Got parameters {'Omega_m': 0.7341476064363232, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:22,534 [classy] Computing new state
2023-07-02 10:24:22,534 [classy] Setting parameters: {'Omega_m': 0.7341476064363232, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:22,580 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 114.58977454941673}
2023-07-02 10:24:22,580 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:22,582 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.0319
2023-07-02 10:24:22,582 [model] Computed derived parameters: {}
2023-07-02 10:24:22,582 [model] Posterior to be computed for parameters {'Omega_m': 0.2995549035460449}
2023-07-02 10:24:22,582 [prior] Evaluating prior at array([0.2995549])
2023-07-02 10:24:22,582 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:22,582 [model] Got input parameters: {'Omega_m': 0.2995549035460449, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:22,582 [classy] Got parameters {'Omega_m': 0.2995549035460449, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:22,582 [classy] Computing new state
2023-07-02 10:24:22,582 [classy] Setting parameters: {'Omega_m': 0.2995549035460449, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:22,630 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.8450191001144}
2023-07-02 10:24:22,630 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:22,631 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0107919
2023-07-02 10:24:22,631 [model] Computed derived parameters: {}
2023-07-02 10:24:22,631 [mcmc] New sample, #124:
Omega_m:0.4677105
2023-07-02 10:24:22,632 [model] Posterior to be computed for parameters {'Omega_m': 0.17212523664658047}
2023-07-02 10:24:22,632 [prior] Evaluating prior at array([0.17212524])
2023-07-02 10:24:22,632 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:22,632 [model] Got input parameters: {'Omega_m': 0.17212523664658047, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:22,632 [classy] Got parameters {'Omega_m': 0.17212523664658047, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:22,632 [classy] Computing new state
2023-07-02 10:24:22,632 [classy] Setting parameters: {'Omega_m': 0.17212523664658047, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:22,679 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 168.59629567843504}
2023-07-02 10:24:22,679 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:22,681 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.81762
2023-07-02 10:24:22,681 [model] Computed derived parameters: {}
2023-07-02 10:24:22,681 [model] Posterior to be computed for parameters {'Omega_m': 0.6178583464290346}
2023-07-02 10:24:22,681 [prior] Evaluating prior at array([0.61785835])
2023-07-02 10:24:22,682 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:22,682 [model] Got input parameters: {'Omega_m': 0.6178583464290346, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:22,682 [classy] Got parameters {'Omega_m': 0.6178583464290346, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:22,682 [classy] Computing new state
2023-07-02 10:24:22,682 [classy] Setting parameters: {'Omega_m': 0.6178583464290346, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:22,729 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 121.15268770890266}
2023-07-02 10:24:22,729 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:22,731 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.13828
2023-07-02 10:24:22,731 [model] Computed derived parameters: {}
2023-07-02 10:24:22,731 [model] Posterior to be computed for parameters {'Omega_m': 0.5425659347968598}
2023-07-02 10:24:22,731 [prior] Evaluating prior at array([0.54256593])
2023-07-02 10:24:22,731 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:22,731 [model] Got input parameters: {'Omega_m': 0.5425659347968598, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:22,731 [classy] Got parameters {'Omega_m': 0.5425659347968598, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:22,731 [classy] Computing new state
2023-07-02 10:24:22,731 [classy] Setting parameters: {'Omega_m': 0.5425659347968598, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:22,778 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 126.14081340246815}
2023-07-02 10:24:22,778 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:22,780 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.01872
2023-07-02 10:24:22,780 [model] Computed derived parameters: {}
2023-07-02 10:24:22,780 [model] Posterior to be computed for parameters {'Omega_m': 0.5006328308081452}
2023-07-02 10:24:22,780 [prior] Evaluating prior at array([0.50063283])
2023-07-02 10:24:22,781 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:22,781 [model] Got input parameters: {'Omega_m': 0.5006328308081452, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:22,781 [classy] Got parameters {'Omega_m': 0.5006328308081452, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:22,781 [classy] Computing new state
2023-07-02 10:24:22,781 [classy] Setting parameters: {'Omega_m': 0.5006328308081452, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:22,828 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 129.23779239091814}
2023-07-02 10:24:22,828 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:22,829 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.455
2023-07-02 10:24:22,829 [model] Computed derived parameters: {}
2023-07-02 10:24:22,830 [model] Posterior to be computed for parameters {'Omega_m': 0.03334462802441124}
2023-07-02 10:24:22,830 [prior] Evaluating prior at array([0.03334463])
2023-07-02 10:24:22,830 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:22,830 [model] Posterior to be computed for parameters {'Omega_m': -0.1589279775940718}
2023-07-02 10:24:22,830 [prior] Evaluating prior at array([-0.15892798])
2023-07-02 10:24:22,830 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:22,830 [model] Posterior to be computed for parameters {'Omega_m': 0.4259348139929615}
2023-07-02 10:24:22,830 [prior] Evaluating prior at array([0.42593481])
2023-07-02 10:24:22,830 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:22,830 [model] Got input parameters: {'Omega_m': 0.4259348139929615, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:22,830 [classy] Got parameters {'Omega_m': 0.4259348139929615, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:22,830 [classy] Computing new state
2023-07-02 10:24:22,830 [classy] Setting parameters: {'Omega_m': 0.4259348139929615, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:22,877 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 135.45940771058147}
2023-07-02 10:24:22,877 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:22,878 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.611526
2023-07-02 10:24:22,879 [model] Computed derived parameters: {}
2023-07-02 10:24:22,879 [mcmc] New sample, #125:
Omega_m:0.2995549
2023-07-02 10:24:22,879 [model] Posterior to be computed for parameters {'Omega_m': 0.4624401870941436}
2023-07-02 10:24:22,879 [prior] Evaluating prior at array([0.46244019])
2023-07-02 10:24:22,879 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:22,879 [model] Got input parameters: {'Omega_m': 0.4624401870941436, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:22,879 [classy] Got parameters {'Omega_m': 0.4624401870941436, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:22,879 [classy] Computing new state
2023-07-02 10:24:22,879 [classy] Setting parameters: {'Omega_m': 0.4624401870941436, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:22,926 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 132.2947996815878}
2023-07-02 10:24:22,926 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:22,928 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.993355
2023-07-02 10:24:22,928 [model] Computed derived parameters: {}
2023-07-02 10:24:22,928 [model] Posterior to be computed for parameters {'Omega_m': 0.24167661050146633}
2023-07-02 10:24:22,928 [prior] Evaluating prior at array([0.24167661])
2023-07-02 10:24:22,928 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:22,928 [model] Got input parameters: {'Omega_m': 0.24167661050146633, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:22,928 [classy] Got parameters {'Omega_m': 0.24167661050146633, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:22,928 [classy] Computing new state
2023-07-02 10:24:22,928 [classy] Setting parameters: {'Omega_m': 0.24167661050146633, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:22,976 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 156.75453153435635}
2023-07-02 10:24:22,976 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:22,978 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.371798
2023-07-02 10:24:22,978 [model] Computed derived parameters: {}
2023-07-02 10:24:22,978 [mcmc] New sample, #126:
Omega_m:0.4259348
2023-07-02 10:24:22,978 [model] Posterior to be computed for parameters {'Omega_m': -0.07734807144616312}
2023-07-02 10:24:22,978 [prior] Evaluating prior at array([-0.07734807])
2023-07-02 10:24:22,978 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:22,978 [model] Posterior to be computed for parameters {'Omega_m': -0.08855664694599208}
2023-07-02 10:24:22,978 [prior] Evaluating prior at array([-0.08855665])
2023-07-02 10:24:22,978 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:22,978 [model] Posterior to be computed for parameters {'Omega_m': 0.35576828245936876}
2023-07-02 10:24:22,978 [prior] Evaluating prior at array([0.35576828])
2023-07-02 10:24:22,979 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:22,979 [model] Got input parameters: {'Omega_m': 0.35576828245936876, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:22,979 [classy] Got parameters {'Omega_m': 0.35576828245936876, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:22,979 [classy] Computing new state
2023-07-02 10:24:22,979 [classy] Setting parameters: {'Omega_m': 0.35576828245936876, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:23,027 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.35037135446305}
2023-07-02 10:24:23,027 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:23,029 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.103797
2023-07-02 10:24:23,029 [model] Computed derived parameters: {}
2023-07-02 10:24:23,029 [mcmc] New sample, #127:
Omega_m:0.2416766
2023-07-02 10:24:23,029 [model] Posterior to be computed for parameters {'Omega_m': 0.3905998800715945}
2023-07-02 10:24:23,029 [prior] Evaluating prior at array([0.39059988])
2023-07-02 10:24:23,029 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:23,029 [model] Got input parameters: {'Omega_m': 0.3905998800715945, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:23,029 [classy] Got parameters {'Omega_m': 0.3905998800715945, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:23,029 [classy] Computing new state
2023-07-02 10:24:23,029 [classy] Setting parameters: {'Omega_m': 0.3905998800715945, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:23,076 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 138.7831249620747}
2023-07-02 10:24:23,076 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:23,078 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.312402
2023-07-02 10:24:23,078 [model] Computed derived parameters: {}
2023-07-02 10:24:23,078 [model] Posterior to be computed for parameters {'Omega_m': 0.4609250190800241}
2023-07-02 10:24:23,078 [prior] Evaluating prior at array([0.46092502])
2023-07-02 10:24:23,078 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:23,078 [model] Got input parameters: {'Omega_m': 0.4609250190800241, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:23,078 [classy] Got parameters {'Omega_m': 0.4609250190800241, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:23,079 [classy] Computing new state
2023-07-02 10:24:23,079 [classy] Setting parameters: {'Omega_m': 0.4609250190800241, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:23,128 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 132.42118883247076}
2023-07-02 10:24:23,129 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:23,130 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.976253
2023-07-02 10:24:23,130 [model] Computed derived parameters: {}
2023-07-02 10:24:23,131 [model] Posterior to be computed for parameters {'Omega_m': 0.5286028310987089}
2023-07-02 10:24:23,131 [prior] Evaluating prior at array([0.52860283])
2023-07-02 10:24:23,131 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:23,131 [model] Got input parameters: {'Omega_m': 0.5286028310987089, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:23,131 [classy] Got parameters {'Omega_m': 0.5286028310987089, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:23,131 [classy] Computing new state
2023-07-02 10:24:23,131 [classy] Setting parameters: {'Omega_m': 0.5286028310987089, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:23,179 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 127.14416363848744}
2023-07-02 10:24:23,179 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:23,181 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.82531
2023-07-02 10:24:23,181 [model] Computed derived parameters: {}
2023-07-02 10:24:23,181 [model] Posterior to be computed for parameters {'Omega_m': 0.32389924181819896}
2023-07-02 10:24:23,181 [prior] Evaluating prior at array([0.32389924])
2023-07-02 10:24:23,181 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:23,181 [model] Got input parameters: {'Omega_m': 0.32389924181819896, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:23,181 [classy] Got parameters {'Omega_m': 0.32389924181819896, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:23,181 [classy] Computing new state
2023-07-02 10:24:23,181 [classy] Setting parameters: {'Omega_m': 0.32389924181819896, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:23,229 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.90843369677927}
2023-07-02 10:24:23,229 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:23,231 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00797111
2023-07-02 10:24:23,231 [model] Computed derived parameters: {}
2023-07-02 10:24:23,231 [mcmc] New sample, #128:
Omega_m:0.3557683
2023-07-02 10:24:23,231 [model] Posterior to be computed for parameters {'Omega_m': 0.3382696126392587}
2023-07-02 10:24:23,231 [prior] Evaluating prior at array([0.33826961])
2023-07-02 10:24:23,231 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:23,231 [model] Got input parameters: {'Omega_m': 0.3382696126392587, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:23,231 [classy] Got parameters {'Omega_m': 0.3382696126392587, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:23,232 [classy] Computing new state
2023-07-02 10:24:23,232 [classy] Setting parameters: {'Omega_m': 0.3382696126392587, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:23,279 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.26635108854407}
2023-07-02 10:24:23,279 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:23,280 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0384985
2023-07-02 10:24:23,281 [model] Computed derived parameters: {}
2023-07-02 10:24:23,281 [mcmc] New sample, #129:
Omega_m:0.3238992
2023-07-02 10:24:23,281 [model] Posterior to be computed for parameters {'Omega_m': 0.05995848092867245}
2023-07-02 10:24:23,281 [prior] Evaluating prior at array([0.05995848])
2023-07-02 10:24:23,281 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:23,281 [model] Posterior to be computed for parameters {'Omega_m': 0.10088278595666456}
2023-07-02 10:24:23,281 [prior] Evaluating prior at array([0.10088279])
2023-07-02 10:24:23,281 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:23,281 [model] Got input parameters: {'Omega_m': 0.10088278595666456, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:23,281 [classy] Got parameters {'Omega_m': 0.10088278595666456, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:23,281 [classy] Computing new state
2023-07-02 10:24:23,281 [classy] Setting parameters: {'Omega_m': 0.10088278595666456, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:23,328 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 184.93669596313848}
2023-07-02 10:24:23,328 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:23,330 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.43355
2023-07-02 10:24:23,330 [model] Computed derived parameters: {}
2023-07-02 10:24:23,331 [model] Posterior to be computed for parameters {'Omega_m': 0.2084565679017576}
2023-07-02 10:24:23,331 [prior] Evaluating prior at array([0.20845657])
2023-07-02 10:24:23,331 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:23,331 [model] Got input parameters: {'Omega_m': 0.2084565679017576, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:23,331 [classy] Got parameters {'Omega_m': 0.2084565679017576, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:23,331 [classy] Computing new state
2023-07-02 10:24:23,331 [classy] Setting parameters: {'Omega_m': 0.2084565679017576, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:23,378 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 162.02879024975945}
2023-07-02 10:24:23,378 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:23,380 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.886402
2023-07-02 10:24:23,380 [model] Computed derived parameters: {}
2023-07-02 10:24:23,380 [model] Posterior to be computed for parameters {'Omega_m': 0.2221715877530942}
2023-07-02 10:24:23,380 [prior] Evaluating prior at array([0.22217159])
2023-07-02 10:24:23,380 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:23,380 [model] Got input parameters: {'Omega_m': 0.2221715877530942, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:23,380 [classy] Got parameters {'Omega_m': 0.2221715877530942, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:23,380 [classy] Computing new state
2023-07-02 10:24:23,380 [classy] Setting parameters: {'Omega_m': 0.2221715877530942, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:23,428 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 159.77581032256077}
2023-07-02 10:24:23,428 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:23,430 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.640563
2023-07-02 10:24:23,430 [model] Computed derived parameters: {}
2023-07-02 10:24:23,430 [model] Posterior to be computed for parameters {'Omega_m': 0.3884377383665991}
2023-07-02 10:24:23,430 [prior] Evaluating prior at array([0.38843774])
2023-07-02 10:24:23,431 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:23,431 [model] Got input parameters: {'Omega_m': 0.3884377383665991, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:23,431 [classy] Got parameters {'Omega_m': 0.3884377383665991, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:23,431 [classy] Computing new state
2023-07-02 10:24:23,431 [classy] Setting parameters: {'Omega_m': 0.3884377383665991, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:23,479 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 138.9957112674892}
2023-07-02 10:24:23,479 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:23,481 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.296744
2023-07-02 10:24:23,481 [model] Computed derived parameters: {}
2023-07-02 10:24:23,481 [mcmc] New sample, #130:
Omega_m:0.3382696
2023-07-02 10:24:23,481 [model] Posterior to be computed for parameters {'Omega_m': 0.36028096075323623}
2023-07-02 10:24:23,481 [prior] Evaluating prior at array([0.36028096])
2023-07-02 10:24:23,481 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:23,481 [model] Got input parameters: {'Omega_m': 0.36028096075323623, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:23,481 [classy] Got parameters {'Omega_m': 0.36028096075323623, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:23,481 [classy] Computing new state
2023-07-02 10:24:23,481 [classy] Setting parameters: {'Omega_m': 0.36028096075323623, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:23,528 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.87030108539744}
2023-07-02 10:24:23,528 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:23,530 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.125228
2023-07-02 10:24:23,530 [model] Computed derived parameters: {}
2023-07-02 10:24:23,530 [mcmc] New sample, #131:
Omega_m:0.3884377
2023-07-02 10:24:23,530 [model] Posterior to be computed for parameters {'Omega_m': 0.42634451615557567}
2023-07-02 10:24:23,530 [prior] Evaluating prior at array([0.42634452])
2023-07-02 10:24:23,530 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:23,530 [model] Got input parameters: {'Omega_m': 0.42634451615557567, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:23,530 [classy] Got parameters {'Omega_m': 0.42634451615557567, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:23,531 [classy] Computing new state
2023-07-02 10:24:23,531 [classy] Setting parameters: {'Omega_m': 0.42634451615557567, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:23,576 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 135.42244799335614}
2023-07-02 10:24:23,576 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:23,578 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.615433
2023-07-02 10:24:23,578 [model] Computed derived parameters: {}
2023-07-02 10:24:23,578 [model] Posterior to be computed for parameters {'Omega_m': 0.041735156496988224}
2023-07-02 10:24:23,578 [prior] Evaluating prior at array([0.04173516])
2023-07-02 10:24:23,578 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:23,578 [model] Posterior to be computed for parameters {'Omega_m': 0.16533821645096491}
2023-07-02 10:24:23,578 [prior] Evaluating prior at array([0.16533822])
2023-07-02 10:24:23,579 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:23,579 [model] Got input parameters: {'Omega_m': 0.16533821645096491, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:23,579 [classy] Got parameters {'Omega_m': 0.16533821645096491, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:23,579 [classy] Computing new state
2023-07-02 10:24:23,579 [classy] Setting parameters: {'Omega_m': 0.16533821645096491, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:23,624 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 169.9333502196603}
2023-07-02 10:24:23,624 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:23,627 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.04532
2023-07-02 10:24:23,627 [model] Computed derived parameters: {}
2023-07-02 10:24:23,627 [mcmc] New sample, #132:
Omega_m:0.360281
2023-07-02 10:24:23,627 [model] Posterior to be computed for parameters {'Omega_m': 0.06926126170119862}
2023-07-02 10:24:23,627 [prior] Evaluating prior at array([0.06926126])
2023-07-02 10:24:23,627 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:23,627 [model] Posterior to be computed for parameters {'Omega_m': 0.5741626817207262}
2023-07-02 10:24:23,627 [prior] Evaluating prior at array([0.57416268])
2023-07-02 10:24:23,628 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:23,628 [model] Got input parameters: {'Omega_m': 0.5741626817207262, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:23,628 [classy] Got parameters {'Omega_m': 0.5741626817207262, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:23,628 [classy] Computing new state
2023-07-02 10:24:23,628 [classy] Setting parameters: {'Omega_m': 0.5741626817207262, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:23,675 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 123.9649771753205}
2023-07-02 10:24:23,675 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:23,677 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.47434
2023-07-02 10:24:23,677 [model] Computed derived parameters: {}
2023-07-02 10:24:23,677 [model] Posterior to be computed for parameters {'Omega_m': 0.16579412026351453}
2023-07-02 10:24:23,678 [prior] Evaluating prior at array([0.16579412])
2023-07-02 10:24:23,678 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:23,678 [model] Got input parameters: {'Omega_m': 0.16579412026351453, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:23,678 [classy] Got parameters {'Omega_m': 0.16579412026351453, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:23,678 [classy] Computing new state
2023-07-02 10:24:23,678 [classy] Setting parameters: {'Omega_m': 0.16579412026351453, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:23,723 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 169.84233671992158}
2023-07-02 10:24:23,723 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:23,725 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.02942
2023-07-02 10:24:23,725 [model] Computed derived parameters: {}
2023-07-02 10:24:23,725 [mcmc] New sample, #133:
Omega_m:0.1653382
2023-07-02 10:24:23,725 [model] Posterior to be computed for parameters {'Omega_m': 0.46337149122354393}
2023-07-02 10:24:23,725 [prior] Evaluating prior at array([0.46337149])
2023-07-02 10:24:23,725 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:23,725 [model] Got input parameters: {'Omega_m': 0.46337149122354393, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:23,725 [classy] Got parameters {'Omega_m': 0.46337149122354393, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:23,725 [classy] Computing new state
2023-07-02 10:24:23,725 [classy] Setting parameters: {'Omega_m': 0.46337149122354393, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:23,771 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 132.21731539998035}
2023-07-02 10:24:23,772 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:23,774 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.00392
2023-07-02 10:24:23,774 [model] Computed derived parameters: {}
2023-07-02 10:24:23,774 [mcmc] New sample, #134:
Omega_m:0.1657941
2023-07-02 10:24:23,774 [model] Posterior to be computed for parameters {'Omega_m': 0.7655513096513915}
2023-07-02 10:24:23,774 [prior] Evaluating prior at array([0.76555131])
2023-07-02 10:24:23,774 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:23,774 [model] Got input parameters: {'Omega_m': 0.7655513096513915, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:23,774 [classy] Got parameters {'Omega_m': 0.7655513096513915, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:23,774 [classy] Computing new state
2023-07-02 10:24:23,774 [classy] Setting parameters: {'Omega_m': 0.7655513096513915, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:23,819 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 113.00950138015209}
2023-07-02 10:24:23,820 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:23,821 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.56307
2023-07-02 10:24:23,822 [model] Computed derived parameters: {}
2023-07-02 10:24:23,822 [model] Posterior to be computed for parameters {'Omega_m': 0.270789139040159}
2023-07-02 10:24:23,822 [prior] Evaluating prior at array([0.27078914])
2023-07-02 10:24:23,822 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:23,822 [model] Got input parameters: {'Omega_m': 0.270789139040159, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:23,822 [classy] Got parameters {'Omega_m': 0.270789139040159, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:23,822 [classy] Computing new state
2023-07-02 10:24:23,822 [classy] Setting parameters: {'Omega_m': 0.270789139040159, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:23,868 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.5967610910096}
2023-07-02 10:24:23,868 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:23,870 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.118981
2023-07-02 10:24:23,870 [model] Computed derived parameters: {}
2023-07-02 10:24:23,870 [mcmc] New sample, #135:
Omega_m:0.4633715
2023-07-02 10:24:23,870 [model] Posterior to be computed for parameters {'Omega_m': 0.6082507166716997}
2023-07-02 10:24:23,870 [prior] Evaluating prior at array([0.60825072])
2023-07-02 10:24:23,870 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:23,870 [model] Got input parameters: {'Omega_m': 0.6082507166716997, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:23,871 [classy] Got parameters {'Omega_m': 0.6082507166716997, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:23,871 [classy] Computing new state
2023-07-02 10:24:23,871 [classy] Setting parameters: {'Omega_m': 0.6082507166716997, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:23,917 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 121.75276112503566}
2023-07-02 10:24:23,917 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:23,919 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.9894
2023-07-02 10:24:23,919 [model] Computed derived parameters: {}
2023-07-02 10:24:23,919 [model] Posterior to be computed for parameters {'Omega_m': 0.5059672011936754}
2023-07-02 10:24:23,919 [prior] Evaluating prior at array([0.5059672])
2023-07-02 10:24:23,920 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:23,920 [model] Got input parameters: {'Omega_m': 0.5059672011936754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:23,920 [classy] Got parameters {'Omega_m': 0.5059672011936754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:23,920 [classy] Computing new state
2023-07-02 10:24:23,920 [classy] Setting parameters: {'Omega_m': 0.5059672011936754, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:23,966 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 128.82951290949086}
2023-07-02 10:24:23,966 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:23,968 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.52371
2023-07-02 10:24:23,968 [model] Computed derived parameters: {}
2023-07-02 10:24:23,968 [model] Posterior to be computed for parameters {'Omega_m': 0.4807708409920225}
2023-07-02 10:24:23,968 [prior] Evaluating prior at array([0.48077084])
2023-07-02 10:24:23,968 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:23,968 [model] Got input parameters: {'Omega_m': 0.4807708409920225, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:23,969 [classy] Got parameters {'Omega_m': 0.4807708409920225, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:23,969 [classy] Computing new state
2023-07-02 10:24:23,969 [classy] Setting parameters: {'Omega_m': 0.4807708409920225, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:24,015 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.7973630919621}
2023-07-02 10:24:24,015 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:24,017 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.20791
2023-07-02 10:24:24,017 [model] Computed derived parameters: {}
2023-07-02 10:24:24,017 [mcmc] New sample, #136:
Omega_m:0.2707891
2023-07-02 10:24:24,017 [model] Posterior to be computed for parameters {'Omega_m': 0.47910613365540666}
2023-07-02 10:24:24,017 [prior] Evaluating prior at array([0.47910613])
2023-07-02 10:24:24,017 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:24,017 [model] Got input parameters: {'Omega_m': 0.47910613365540666, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:24,017 [classy] Got parameters {'Omega_m': 0.47910613365540666, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:24,017 [classy] Computing new state
2023-07-02 10:24:24,017 [classy] Setting parameters: {'Omega_m': 0.47910613365540666, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:24,065 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.93098341594222}
2023-07-02 10:24:24,065 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:24,067 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.18787
2023-07-02 10:24:24,067 [model] Computed derived parameters: {}
2023-07-02 10:24:24,067 [mcmc] New sample, #137:
Omega_m:0.4807708
2023-07-02 10:24:24,067 [model] Posterior to be computed for parameters {'Omega_m': 0.6326607954686883}
2023-07-02 10:24:24,067 [prior] Evaluating prior at array([0.6326608])
2023-07-02 10:24:24,067 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:24,067 [model] Got input parameters: {'Omega_m': 0.6326607954686883, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:24,067 [classy] Got parameters {'Omega_m': 0.6326607954686883, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:24,067 [classy] Computing new state
2023-07-02 10:24:24,067 [classy] Setting parameters: {'Omega_m': 0.6326607954686883, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:24,112 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 120.24713523779305}
2023-07-02 10:24:24,112 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:24,114 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.37049
2023-07-02 10:24:24,114 [model] Computed derived parameters: {}
2023-07-02 10:24:24,114 [model] Posterior to be computed for parameters {'Omega_m': 0.305662828461555}
2023-07-02 10:24:24,114 [prior] Evaluating prior at array([0.30566283])
2023-07-02 10:24:24,115 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:24,115 [model] Got input parameters: {'Omega_m': 0.305662828461555, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:24,115 [classy] Got parameters {'Omega_m': 0.305662828461555, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:24,115 [classy] Computing new state
2023-07-02 10:24:24,115 [classy] Setting parameters: {'Omega_m': 0.305662828461555, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:24,162 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.08894363688228}
2023-07-02 10:24:24,162 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:24,163 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00310483
2023-07-02 10:24:24,164 [model] Computed derived parameters: {}
2023-07-02 10:24:24,164 [mcmc] New sample, #138:
Omega_m:0.4791061
2023-07-02 10:24:24,164 [model] Posterior to be computed for parameters {'Omega_m': 1.0771052795016534}
2023-07-02 10:24:24,164 [prior] Evaluating prior at array([1.07710528])
2023-07-02 10:24:24,164 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:24,164 [model] Posterior to be computed for parameters {'Omega_m': 0.2976259333085199}
2023-07-02 10:24:24,164 [prior] Evaluating prior at array([0.29762593])
2023-07-02 10:24:24,164 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:24,164 [model] Got input parameters: {'Omega_m': 0.2976259333085199, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:24,164 [classy] Got parameters {'Omega_m': 0.2976259333085199, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:24,164 [classy] Computing new state
2023-07-02 10:24:24,164 [classy] Setting parameters: {'Omega_m': 0.2976259333085199, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:24,211 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.08662803830572}
2023-07-02 10:24:24,211 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:24,213 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.014257
2023-07-02 10:24:24,213 [model] Computed derived parameters: {}
2023-07-02 10:24:24,213 [mcmc] New sample, #139:
Omega_m:0.3056628
2023-07-02 10:24:24,213 [model] Posterior to be computed for parameters {'Omega_m': 0.35859448483837464}
2023-07-02 10:24:24,213 [prior] Evaluating prior at array([0.35859448])
2023-07-02 10:24:24,213 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:24,214 [model] Got input parameters: {'Omega_m': 0.35859448483837464, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:24,214 [classy] Got parameters {'Omega_m': 0.35859448483837464, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:24,214 [classy] Computing new state
2023-07-02 10:24:24,214 [classy] Setting parameters: {'Omega_m': 0.35859448483837464, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:24,262 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.04905839839446}
2023-07-02 10:24:24,262 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:24,263 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.117009
2023-07-02 10:24:24,263 [model] Computed derived parameters: {}
2023-07-02 10:24:24,264 [mcmc] New sample, #140:
Omega_m:0.2976259
2023-07-02 10:24:24,264 [model] Posterior to be computed for parameters {'Omega_m': 0.005247977872464726}
2023-07-02 10:24:24,264 [prior] Evaluating prior at array([0.00524798])
2023-07-02 10:24:24,264 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:24,264 [model] Posterior to be computed for parameters {'Omega_m': 0.32056643279504426}
2023-07-02 10:24:24,264 [prior] Evaluating prior at array([0.32056643])
2023-07-02 10:24:24,264 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:24,264 [model] Got input parameters: {'Omega_m': 0.32056643279504426, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:24,264 [classy] Got parameters {'Omega_m': 0.32056643279504426, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:24,264 [classy] Computing new state
2023-07-02 10:24:24,264 [classy] Setting parameters: {'Omega_m': 0.32056643279504426, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:24,312 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.29862574019367}
2023-07-02 10:24:24,312 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:24,314 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00412868
2023-07-02 10:24:24,314 [model] Computed derived parameters: {}
2023-07-02 10:24:24,314 [mcmc] New sample, #141:
Omega_m:0.3585945
2023-07-02 10:24:24,314 [model] Posterior to be computed for parameters {'Omega_m': 0.6197586399129854}
2023-07-02 10:24:24,314 [prior] Evaluating prior at array([0.61975864])
2023-07-02 10:24:24,314 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:24,314 [model] Got input parameters: {'Omega_m': 0.6197586399129854, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:24,314 [classy] Got parameters {'Omega_m': 0.6197586399129854, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:24,314 [classy] Computing new state
2023-07-02 10:24:24,314 [classy] Setting parameters: {'Omega_m': 0.6197586399129854, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:24,362 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 121.03515687597314}
2023-07-02 10:24:24,362 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:24,363 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.16791
2023-07-02 10:24:24,363 [model] Computed derived parameters: {}
2023-07-02 10:24:24,364 [model] Posterior to be computed for parameters {'Omega_m': 0.03223708890050481}
2023-07-02 10:24:24,364 [prior] Evaluating prior at array([0.03223709])
2023-07-02 10:24:24,364 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:24,364 [model] Posterior to be computed for parameters {'Omega_m': 0.5573407947048554}
2023-07-02 10:24:24,364 [prior] Evaluating prior at array([0.55734079])
2023-07-02 10:24:24,364 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:24,364 [model] Got input parameters: {'Omega_m': 0.5573407947048554, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:24,364 [classy] Got parameters {'Omega_m': 0.5573407947048554, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:24,364 [classy] Computing new state
2023-07-02 10:24:24,364 [classy] Setting parameters: {'Omega_m': 0.5573407947048554, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:24,412 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 125.10755005544335}
2023-07-02 10:24:24,412 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:24,413 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.22886
2023-07-02 10:24:24,413 [model] Computed derived parameters: {}
2023-07-02 10:24:24,414 [model] Posterior to be computed for parameters {'Omega_m': 0.2946949033424985}
2023-07-02 10:24:24,414 [prior] Evaluating prior at array([0.2946949])
2023-07-02 10:24:24,414 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:24,414 [model] Got input parameters: {'Omega_m': 0.2946949033424985, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:24,414 [classy] Got parameters {'Omega_m': 0.2946949033424985, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:24,414 [classy] Computing new state
2023-07-02 10:24:24,414 [classy] Setting parameters: {'Omega_m': 0.2946949033424985, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:24,462 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.45637304553736}
2023-07-02 10:24:24,462 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:24,463 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0205016
2023-07-02 10:24:24,464 [model] Computed derived parameters: {}
2023-07-02 10:24:24,464 [mcmc] New sample, #142:
Omega_m:0.3205664
2023-07-02 10:24:24,464 [model] Posterior to be computed for parameters {'Omega_m': 0.5216382668281213}
2023-07-02 10:24:24,464 [prior] Evaluating prior at array([0.52163827])
2023-07-02 10:24:24,464 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:24,464 [model] Got input parameters: {'Omega_m': 0.5216382668281213, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:24,464 [classy] Got parameters {'Omega_m': 0.5216382668281213, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:24,464 [classy] Computing new state
2023-07-02 10:24:24,464 [classy] Setting parameters: {'Omega_m': 0.5216382668281213, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:24,510 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 127.65480282168627}
2023-07-02 10:24:24,510 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:24,512 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.73086
2023-07-02 10:24:24,512 [model] Computed derived parameters: {}
2023-07-02 10:24:24,512 [mcmc] New sample, #143:
Omega_m:0.2946949
2023-07-02 10:24:24,512 [model] Posterior to be computed for parameters {'Omega_m': 0.3041145005943974}
2023-07-02 10:24:24,512 [prior] Evaluating prior at array([0.3041145])
2023-07-02 10:24:24,512 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:24,513 [model] Got input parameters: {'Omega_m': 0.3041145005943974, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:24,513 [classy] Got parameters {'Omega_m': 0.3041145005943974, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:24,513 [classy] Computing new state
2023-07-02 10:24:24,513 [classy] Setting parameters: {'Omega_m': 0.3041145005943974, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:24,559 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2793371657879}
2023-07-02 10:24:24,559 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:24,561 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00458897
2023-07-02 10:24:24,561 [model] Computed derived parameters: {}
2023-07-02 10:24:24,561 [mcmc] New sample, #144:
Omega_m:0.5216383
2023-07-02 10:24:24,561 [model] Posterior to be computed for parameters {'Omega_m': 0.5066056641309248}
2023-07-02 10:24:24,561 [prior] Evaluating prior at array([0.50660566])
2023-07-02 10:24:24,561 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:24,561 [model] Got input parameters: {'Omega_m': 0.5066056641309248, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:24,561 [classy] Got parameters {'Omega_m': 0.5066056641309248, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:24,561 [classy] Computing new state
2023-07-02 10:24:24,561 [classy] Setting parameters: {'Omega_m': 0.5066056641309248, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:24,608 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 128.7809373182323}
2023-07-02 10:24:24,608 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:24,609 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.532
2023-07-02 10:24:24,610 [model] Computed derived parameters: {}
2023-07-02 10:24:24,610 [model] Posterior to be computed for parameters {'Omega_m': 0.5944673860934429}
2023-07-02 10:24:24,610 [prior] Evaluating prior at array([0.59446739])
2023-07-02 10:24:24,610 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:24,610 [model] Got input parameters: {'Omega_m': 0.5944673860934429, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:24,610 [classy] Got parameters {'Omega_m': 0.5944673860934429, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:24,610 [classy] Computing new state
2023-07-02 10:24:24,610 [classy] Setting parameters: {'Omega_m': 0.5944673860934429, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:24,658 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 122.63127732817031}
2023-07-02 10:24:24,658 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:24,660 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.77852
2023-07-02 10:24:24,660 [model] Computed derived parameters: {}
2023-07-02 10:24:24,660 [model] Posterior to be computed for parameters {'Omega_m': -0.01490252417513166}
2023-07-02 10:24:24,660 [prior] Evaluating prior at array([-0.01490252])
2023-07-02 10:24:24,660 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:24,660 [model] Posterior to be computed for parameters {'Omega_m': 0.39423406197239275}
2023-07-02 10:24:24,660 [prior] Evaluating prior at array([0.39423406])
2023-07-02 10:24:24,660 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:24,660 [model] Got input parameters: {'Omega_m': 0.39423406197239275, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:24,660 [classy] Got parameters {'Omega_m': 0.39423406197239275, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:24,660 [classy] Computing new state
2023-07-02 10:24:24,660 [classy] Setting parameters: {'Omega_m': 0.39423406197239275, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:24,707 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 138.42833281259124}
2023-07-02 10:24:24,708 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:24,709 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.339453
2023-07-02 10:24:24,709 [model] Computed derived parameters: {}
2023-07-02 10:24:24,709 [mcmc] New sample, #145:
Omega_m:0.3041145
2023-07-02 10:24:24,709 [model] Posterior to be computed for parameters {'Omega_m': 0.9067531437355372}
2023-07-02 10:24:24,710 [prior] Evaluating prior at array([0.90675314])
2023-07-02 10:24:24,710 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:24,710 [model] Got input parameters: {'Omega_m': 0.9067531437355372, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:24,710 [classy] Got parameters {'Omega_m': 0.9067531437355372, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:24,710 [classy] Computing new state
2023-07-02 10:24:24,710 [classy] Setting parameters: {'Omega_m': 0.9067531437355372, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:24,756 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 106.69436053260269}
2023-07-02 10:24:24,756 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:24,758 [bao_likelihood.baolikelihood] Computed log-likelihood = -7.99539
2023-07-02 10:24:24,758 [model] Computed derived parameters: {}
2023-07-02 10:24:24,758 [model] Posterior to be computed for parameters {'Omega_m': 0.19156367502989086}
2023-07-02 10:24:24,758 [prior] Evaluating prior at array([0.19156368])
2023-07-02 10:24:24,758 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:24,758 [model] Got input parameters: {'Omega_m': 0.19156367502989086, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:24,758 [classy] Got parameters {'Omega_m': 0.19156367502989086, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:24,758 [classy] Computing new state
2023-07-02 10:24:24,758 [classy] Setting parameters: {'Omega_m': 0.19156367502989086, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:24,803 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 164.96654510076615}
2023-07-02 10:24:24,804 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:24,806 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.26399
2023-07-02 10:24:24,806 [model] Computed derived parameters: {}
2023-07-02 10:24:24,807 [mcmc] New sample, #146:
Omega_m:0.3942341
2023-07-02 10:24:24,807 [model] Posterior to be computed for parameters {'Omega_m': 0.12725039500568475}
2023-07-02 10:24:24,807 [prior] Evaluating prior at array([0.1272504])
2023-07-02 10:24:24,807 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:24,807 [model] Got input parameters: {'Omega_m': 0.12725039500568475, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:24,807 [classy] Got parameters {'Omega_m': 0.12725039500568475, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:24,807 [classy] Computing new state
2023-07-02 10:24:24,807 [classy] Setting parameters: {'Omega_m': 0.12725039500568475, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:24,853 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 178.22844003094588}
2023-07-02 10:24:24,853 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:24,856 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.73424
2023-07-02 10:24:24,856 [model] Computed derived parameters: {}
2023-07-02 10:24:24,856 [model] Posterior to be computed for parameters {'Omega_m': 0.18351084657607714}
2023-07-02 10:24:24,856 [prior] Evaluating prior at array([0.18351085])
2023-07-02 10:24:24,856 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:24,856 [model] Got input parameters: {'Omega_m': 0.18351084657607714, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:24,856 [classy] Got parameters {'Omega_m': 0.18351084657607714, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:24,856 [classy] Computing new state
2023-07-02 10:24:24,856 [classy] Setting parameters: {'Omega_m': 0.18351084657607714, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:24,903 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 166.43592799283766}
2023-07-02 10:24:24,903 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:24,906 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.47664
2023-07-02 10:24:24,906 [model] Computed derived parameters: {}
2023-07-02 10:24:24,906 [mcmc] New sample, #147:
Omega_m:0.1915637
2023-07-02 10:24:24,906 [model] Posterior to be computed for parameters {'Omega_m': 0.06313668392974646}
2023-07-02 10:24:24,906 [prior] Evaluating prior at array([0.06313668])
2023-07-02 10:24:24,906 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:24,907 [model] Posterior to be computed for parameters {'Omega_m': 0.3200165709482702}
2023-07-02 10:24:24,907 [prior] Evaluating prior at array([0.32001657])
2023-07-02 10:24:24,907 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:24,907 [model] Got input parameters: {'Omega_m': 0.3200165709482702, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:24,907 [classy] Got parameters {'Omega_m': 0.3200165709482702, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:24,907 [classy] Computing new state
2023-07-02 10:24:24,907 [classy] Setting parameters: {'Omega_m': 0.3200165709482702, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:24,953 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.36334634414226}
2023-07-02 10:24:24,953 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:24,956 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00361727
2023-07-02 10:24:24,956 [model] Computed derived parameters: {}
2023-07-02 10:24:24,956 [mcmc] New sample, #148:
Omega_m:0.1835108
2023-07-02 10:24:24,956 [model] Posterior to be computed for parameters {'Omega_m': 0.30374436317079995}
2023-07-02 10:24:24,956 [prior] Evaluating prior at array([0.30374436])
2023-07-02 10:24:24,956 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:24,956 [model] Got input parameters: {'Omega_m': 0.30374436317079995, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:24,956 [classy] Got parameters {'Omega_m': 0.30374436317079995, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:24,956 [classy] Computing new state
2023-07-02 10:24:24,956 [classy] Setting parameters: {'Omega_m': 0.30374436317079995, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:25,006 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.32497992374226}
2023-07-02 10:24:25,007 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:25,008 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00499001
2023-07-02 10:24:25,008 [model] Computed derived parameters: {}
2023-07-02 10:24:25,008 [mcmc] New sample, #149:
Omega_m:0.3200166
2023-07-02 10:24:25,008 [model] Posterior to be computed for parameters {'Omega_m': -0.1262566739697653}
2023-07-02 10:24:25,008 [prior] Evaluating prior at array([-0.12625667])
2023-07-02 10:24:25,009 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:25,009 [model] Posterior to be computed for parameters {'Omega_m': 0.6584618252520076}
2023-07-02 10:24:25,009 [prior] Evaluating prior at array([0.65846183])
2023-07-02 10:24:25,009 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:25,009 [model] Got input parameters: {'Omega_m': 0.6584618252520076, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:25,009 [classy] Got parameters {'Omega_m': 0.6584618252520076, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:25,009 [classy] Computing new state
2023-07-02 10:24:25,009 [classy] Setting parameters: {'Omega_m': 0.6584618252520076, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:25,057 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 118.7211717728523}
2023-07-02 10:24:25,057 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:25,059 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.78249
2023-07-02 10:24:25,059 [model] Computed derived parameters: {}
2023-07-02 10:24:25,059 [model] Posterior to be computed for parameters {'Omega_m': 0.1501468984841768}
2023-07-02 10:24:25,059 [prior] Evaluating prior at array([0.1501469])
2023-07-02 10:24:25,059 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:25,059 [model] Got input parameters: {'Omega_m': 0.1501468984841768, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:25,059 [classy] Got parameters {'Omega_m': 0.1501468984841768, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:25,059 [classy] Computing new state
2023-07-02 10:24:25,059 [classy] Setting parameters: {'Omega_m': 0.1501468984841768, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:25,107 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 173.07108984499627}
2023-07-02 10:24:25,107 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:25,108 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.62888
2023-07-02 10:24:25,108 [model] Computed derived parameters: {}
2023-07-02 10:24:25,108 [model] Posterior to be computed for parameters {'Omega_m': 0.12230486797178103}
2023-07-02 10:24:25,109 [prior] Evaluating prior at array([0.12230487])
2023-07-02 10:24:25,109 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:25,109 [model] Got input parameters: {'Omega_m': 0.12230486797178103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:25,109 [classy] Got parameters {'Omega_m': 0.12230486797178103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:25,109 [classy] Computing new state
2023-07-02 10:24:25,109 [classy] Setting parameters: {'Omega_m': 0.12230486797178103, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:25,156 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 179.4186178433223}
2023-07-02 10:24:25,156 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:25,158 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.01451
2023-07-02 10:24:25,158 [model] Computed derived parameters: {}
2023-07-02 10:24:25,158 [model] Posterior to be computed for parameters {'Omega_m': 0.5536096831927042}
2023-07-02 10:24:25,158 [prior] Evaluating prior at array([0.55360968])
2023-07-02 10:24:25,158 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:25,158 [model] Got input parameters: {'Omega_m': 0.5536096831927042, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:25,159 [classy] Got parameters {'Omega_m': 0.5536096831927042, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:25,159 [classy] Computing new state
2023-07-02 10:24:25,159 [classy] Setting parameters: {'Omega_m': 0.5536096831927042, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:25,206 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 125.36579661687814}
2023-07-02 10:24:25,206 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:25,208 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.17529
2023-07-02 10:24:25,208 [model] Computed derived parameters: {}
2023-07-02 10:24:25,208 [model] Posterior to be computed for parameters {'Omega_m': 0.30221631904211776}
2023-07-02 10:24:25,208 [prior] Evaluating prior at array([0.30221632])
2023-07-02 10:24:25,208 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:25,208 [model] Got input parameters: {'Omega_m': 0.30221631904211776, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:25,208 [classy] Got parameters {'Omega_m': 0.30221631904211776, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:25,208 [classy] Computing new state
2023-07-02 10:24:25,208 [classy] Setting parameters: {'Omega_m': 0.30221631904211776, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:25,255 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.51391658649328}
2023-07-02 10:24:25,255 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:25,257 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00683591
2023-07-02 10:24:25,257 [model] Computed derived parameters: {}
2023-07-02 10:24:25,257 [mcmc] New sample, #150:
Omega_m:0.3037444
2023-07-02 10:24:25,258 [model] Posterior to be computed for parameters {'Omega_m': -0.13618722146547912}
2023-07-02 10:24:25,258 [prior] Evaluating prior at array([-0.13618722])
2023-07-02 10:24:25,258 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:25,258 [model] Posterior to be computed for parameters {'Omega_m': 0.3082574811849115}
2023-07-02 10:24:25,258 [prior] Evaluating prior at array([0.30825748])
2023-07-02 10:24:25,258 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:25,258 [model] Got input parameters: {'Omega_m': 0.3082574811849115, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:25,258 [classy] Got parameters {'Omega_m': 0.3082574811849115, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:25,258 [classy] Computing new state
2023-07-02 10:24:25,258 [classy] Setting parameters: {'Omega_m': 0.3082574811849115, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:25,304 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.77177263957392}
2023-07-02 10:24:25,304 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:25,307 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00130949
2023-07-02 10:24:25,307 [model] Computed derived parameters: {}
2023-07-02 10:24:25,307 [mcmc] New sample, #151:
Omega_m:0.3022163
2023-07-02 10:24:25,307 [model] Posterior to be computed for parameters {'Omega_m': 0.3724394958323314}
2023-07-02 10:24:25,307 [prior] Evaluating prior at array([0.3724395])
2023-07-02 10:24:25,307 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:25,307 [model] Got input parameters: {'Omega_m': 0.3724394958323314, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:25,307 [classy] Got parameters {'Omega_m': 0.3724394958323314, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:25,308 [classy] Computing new state
2023-07-02 10:24:25,308 [classy] Setting parameters: {'Omega_m': 0.3724394958323314, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:25,354 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.6041382108848}
2023-07-02 10:24:25,354 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:25,356 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.191603
2023-07-02 10:24:25,357 [model] Computed derived parameters: {}
2023-07-02 10:24:25,357 [mcmc] New sample, #152:
Omega_m:0.3082575
2023-07-02 10:24:25,357 [model] Posterior to be computed for parameters {'Omega_m': 0.3083756291470865}
2023-07-02 10:24:25,357 [prior] Evaluating prior at array([0.30837563])
2023-07-02 10:24:25,357 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:25,357 [model] Got input parameters: {'Omega_m': 0.3083756291470865, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:25,357 [classy] Got parameters {'Omega_m': 0.3083756291470865, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:25,357 [classy] Computing new state
2023-07-02 10:24:25,357 [classy] Setting parameters: {'Omega_m': 0.3083756291470865, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:25,402 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.75738625562877}
2023-07-02 10:24:25,403 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:25,405 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00124815
2023-07-02 10:24:25,405 [model] Computed derived parameters: {}
2023-07-02 10:24:25,405 [mcmc] New sample, #153:
Omega_m:0.3724395
2023-07-02 10:24:25,406 [model] Posterior to be computed for parameters {'Omega_m': 0.35319819954668974}
2023-07-02 10:24:25,406 [prior] Evaluating prior at array([0.3531982])
2023-07-02 10:24:25,406 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:25,406 [model] Got input parameters: {'Omega_m': 0.35319819954668974, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:25,406 [classy] Got parameters {'Omega_m': 0.35319819954668974, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:25,406 [classy] Computing new state
2023-07-02 10:24:25,406 [classy] Setting parameters: {'Omega_m': 0.35319819954668974, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:25,452 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.62629260300002}
2023-07-02 10:24:25,452 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:25,454 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.092403
2023-07-02 10:24:25,455 [model] Computed derived parameters: {}
2023-07-02 10:24:25,455 [mcmc] New sample, #154:
Omega_m:0.3083756
2023-07-02 10:24:25,455 [model] Posterior to be computed for parameters {'Omega_m': 0.5005742682134801}
2023-07-02 10:24:25,455 [prior] Evaluating prior at array([0.50057427])
2023-07-02 10:24:25,455 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:25,455 [model] Got input parameters: {'Omega_m': 0.5005742682134801, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:25,455 [classy] Got parameters {'Omega_m': 0.5005742682134801, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:25,455 [classy] Computing new state
2023-07-02 10:24:25,455 [classy] Setting parameters: {'Omega_m': 0.5005742682134801, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:25,502 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 129.24229745316117}
2023-07-02 10:24:25,502 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:25,504 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.45425
2023-07-02 10:24:25,504 [model] Computed derived parameters: {}
2023-07-02 10:24:25,504 [mcmc] New sample, #155:
Omega_m:0.3531982
2023-07-02 10:24:25,505 [model] Posterior to be computed for parameters {'Omega_m': 0.5289638033121735}
2023-07-02 10:24:25,505 [prior] Evaluating prior at array([0.5289638])
2023-07-02 10:24:25,505 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:25,505 [model] Got input parameters: {'Omega_m': 0.5289638033121735, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:25,505 [classy] Got parameters {'Omega_m': 0.5289638033121735, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:25,505 [classy] Computing new state
2023-07-02 10:24:25,505 [classy] Setting parameters: {'Omega_m': 0.5289638033121735, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:25,552 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 127.11788462815247}
2023-07-02 10:24:25,552 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:25,555 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.83025
2023-07-02 10:24:25,555 [model] Computed derived parameters: {}
2023-07-02 10:24:25,555 [mcmc] New sample, #156:
Omega_m:0.5005743
2023-07-02 10:24:25,555 [model] Posterior to be computed for parameters {'Omega_m': 0.533166710063196}
2023-07-02 10:24:25,555 [prior] Evaluating prior at array([0.53316671])
2023-07-02 10:24:25,555 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:25,555 [model] Got input parameters: {'Omega_m': 0.533166710063196, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:25,555 [classy] Got parameters {'Omega_m': 0.533166710063196, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:25,555 [classy] Computing new state
2023-07-02 10:24:25,555 [classy] Setting parameters: {'Omega_m': 0.533166710063196, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:25,602 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 126.81327403852498}
2023-07-02 10:24:25,602 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:25,605 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.88794
2023-07-02 10:24:25,605 [model] Computed derived parameters: {}
2023-07-02 10:24:25,605 [mcmc] New sample, #157:
Omega_m:0.5289638
2023-07-02 10:24:25,605 [model] Posterior to be computed for parameters {'Omega_m': 0.6817820141490225}
2023-07-02 10:24:25,605 [prior] Evaluating prior at array([0.68178201])
2023-07-02 10:24:25,606 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:25,606 [model] Got input parameters: {'Omega_m': 0.6817820141490225, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:25,606 [classy] Got parameters {'Omega_m': 0.6817820141490225, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:25,606 [classy] Computing new state
2023-07-02 10:24:25,606 [classy] Setting parameters: {'Omega_m': 0.6817820141490225, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:25,651 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 117.39585065339337}
2023-07-02 10:24:25,651 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:25,653 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.16174
2023-07-02 10:24:25,653 [model] Computed derived parameters: {}
2023-07-02 10:24:25,654 [model] Posterior to be computed for parameters {'Omega_m': 0.679562879559181}
2023-07-02 10:24:25,654 [prior] Evaluating prior at array([0.67956288])
2023-07-02 10:24:25,654 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:25,654 [model] Got input parameters: {'Omega_m': 0.679562879559181, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:25,654 [classy] Got parameters {'Omega_m': 0.679562879559181, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:25,654 [classy] Computing new state
2023-07-02 10:24:25,654 [classy] Setting parameters: {'Omega_m': 0.679562879559181, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:25,701 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 117.51986375578694}
2023-07-02 10:24:25,701 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:25,703 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.1254
2023-07-02 10:24:25,703 [model] Computed derived parameters: {}
2023-07-02 10:24:25,703 [model] Posterior to be computed for parameters {'Omega_m': 0.5167059602785964}
2023-07-02 10:24:25,703 [prior] Evaluating prior at array([0.51670596])
2023-07-02 10:24:25,703 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:25,703 [model] Got input parameters: {'Omega_m': 0.5167059602785964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:25,703 [classy] Got parameters {'Omega_m': 0.5167059602785964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:25,703 [classy] Computing new state
2023-07-02 10:24:25,703 [classy] Setting parameters: {'Omega_m': 0.5167059602785964, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:25,749 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 128.02062945909347}
2023-07-02 10:24:25,749 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:25,751 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.66484
2023-07-02 10:24:25,751 [model] Computed derived parameters: {}
2023-07-02 10:24:25,752 [mcmc] New sample, #158:
Omega_m:0.5331667
2023-07-02 10:24:25,752 [model] Posterior to be computed for parameters {'Omega_m': 0.49208229611278004}
2023-07-02 10:24:25,752 [prior] Evaluating prior at array([0.4920823])
2023-07-02 10:24:25,752 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:25,752 [model] Got input parameters: {'Omega_m': 0.49208229611278004, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:25,752 [classy] Got parameters {'Omega_m': 0.49208229611278004, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:25,752 [classy] Computing new state
2023-07-02 10:24:25,752 [classy] Setting parameters: {'Omega_m': 0.49208229611278004, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:25,798 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 129.90142308539504}
2023-07-02 10:24:25,798 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:25,800 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.34689
2023-07-02 10:24:25,800 [model] Computed derived parameters: {}
2023-07-02 10:24:25,800 [mcmc] New sample, #159:
Omega_m:0.516706
2023-07-02 10:24:25,800 [model] Posterior to be computed for parameters {'Omega_m': 0.6430921747357369}
2023-07-02 10:24:25,800 [prior] Evaluating prior at array([0.64309217])
2023-07-02 10:24:25,801 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:25,801 [model] Got input parameters: {'Omega_m': 0.6430921747357369, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:25,801 [classy] Got parameters {'Omega_m': 0.6430921747357369, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:25,801 [classy] Computing new state
2023-07-02 10:24:25,801 [classy] Setting parameters: {'Omega_m': 0.6430921747357369, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:25,846 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 119.62234724441264}
2023-07-02 10:24:25,846 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:25,848 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.53602
2023-07-02 10:24:25,848 [model] Computed derived parameters: {}
2023-07-02 10:24:25,848 [model] Posterior to be computed for parameters {'Omega_m': 0.5320469735180322}
2023-07-02 10:24:25,848 [prior] Evaluating prior at array([0.53204697])
2023-07-02 10:24:25,848 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:25,848 [model] Got input parameters: {'Omega_m': 0.5320469735180322, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:25,848 [classy] Got parameters {'Omega_m': 0.5320469735180322, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:25,848 [classy] Computing new state
2023-07-02 10:24:25,848 [classy] Setting parameters: {'Omega_m': 0.5320469735180322, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:25,895 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 126.89418917242322}
2023-07-02 10:24:25,895 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:25,897 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.87252
2023-07-02 10:24:25,897 [model] Computed derived parameters: {}
2023-07-02 10:24:25,897 [mcmc] New sample, #160:
Omega_m:0.4920823
2023-07-02 10:24:25,897 [mcmc] Learn + convergence test @ 160 samples accepted.
2023-07-02 10:24:25,897 [mcmc] Ready to check convergence and learn a new proposal covmat
2023-07-02 10:24:25,902 [mcmc] - Acceptance rate: 0.670
2023-07-02 10:24:25,902 [mcmc] - Condition number = 1
2023-07-02 10:24:25,902 [mcmc] - Eigenvalues = array([0.05632543])
2023-07-02 10:24:25,902 [mcmc] - Convergence of means: R-1 = 0.056325 after 128 accepted steps
2023-07-02 10:24:25,902 [mcmc] - Updated covariance matrix of proposal pdf.
2023-07-02 10:24:25,902 [mcmc] array([[0.01093334]])
2023-07-02 10:24:25,913 [mcmc] Dumped checkpoint and progress info, and current covmat.
2023-07-02 10:24:25,913 [model] Posterior to be computed for parameters {'Omega_m': 0.4774438593566598}
2023-07-02 10:24:25,913 [prior] Evaluating prior at array([0.47744386])
2023-07-02 10:24:25,913 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:25,913 [model] Got input parameters: {'Omega_m': 0.4774438593566598, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:25,913 [classy] Got parameters {'Omega_m': 0.4774438593566598, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:25,913 [classy] Computing new state
2023-07-02 10:24:25,913 [classy] Setting parameters: {'Omega_m': 0.4774438593566598, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:25,960 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 131.0648721847981}
2023-07-02 10:24:25,960 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:25,962 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.16796
2023-07-02 10:24:25,962 [model] Computed derived parameters: {}
2023-07-02 10:24:25,962 [mcmc] New sample, #161:
Omega_m:0.532047
2023-07-02 10:24:25,962 [model] Posterior to be computed for parameters {'Omega_m': 0.5738120430032648}
2023-07-02 10:24:25,962 [prior] Evaluating prior at array([0.57381204])
2023-07-02 10:24:25,962 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:25,962 [model] Got input parameters: {'Omega_m': 0.5738120430032648, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:25,962 [classy] Got parameters {'Omega_m': 0.5738120430032648, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:25,962 [classy] Computing new state
2023-07-02 10:24:25,962 [classy] Setting parameters: {'Omega_m': 0.5738120430032648, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:26,009 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 123.98843837033732}
2023-07-02 10:24:26,009 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:26,011 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.46916
2023-07-02 10:24:26,011 [model] Computed derived parameters: {}
2023-07-02 10:24:26,011 [model] Posterior to be computed for parameters {'Omega_m': 0.47314949572939563}
2023-07-02 10:24:26,011 [prior] Evaluating prior at array([0.4731495])
2023-07-02 10:24:26,011 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:26,011 [model] Got input parameters: {'Omega_m': 0.47314949572939563, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:26,011 [classy] Got parameters {'Omega_m': 0.47314949572939563, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:26,011 [classy] Computing new state
2023-07-02 10:24:26,011 [classy] Setting parameters: {'Omega_m': 0.47314949572939563, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:26,059 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 131.41293811896026}
2023-07-02 10:24:26,059 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:26,061 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.11704
2023-07-02 10:24:26,061 [model] Computed derived parameters: {}
2023-07-02 10:24:26,061 [mcmc] New sample, #162:
Omega_m:0.4774439
2023-07-02 10:24:26,061 [model] Posterior to be computed for parameters {'Omega_m': 0.7605905762513676}
2023-07-02 10:24:26,061 [prior] Evaluating prior at array([0.76059058])
2023-07-02 10:24:26,061 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:26,061 [model] Got input parameters: {'Omega_m': 0.7605905762513676, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:26,061 [classy] Got parameters {'Omega_m': 0.7605905762513676, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:26,061 [classy] Computing new state
2023-07-02 10:24:26,061 [classy] Setting parameters: {'Omega_m': 0.7605905762513676, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:26,105 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 113.25436525207276}
2023-07-02 10:24:26,105 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:26,108 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.47878
2023-07-02 10:24:26,108 [model] Computed derived parameters: {}
2023-07-02 10:24:26,108 [model] Posterior to be computed for parameters {'Omega_m': 0.7460764282280585}
2023-07-02 10:24:26,108 [prior] Evaluating prior at array([0.74607643])
2023-07-02 10:24:26,109 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:26,109 [model] Got input parameters: {'Omega_m': 0.7460764282280585, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:26,109 [classy] Got parameters {'Omega_m': 0.7460764282280585, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:26,109 [classy] Computing new state
2023-07-02 10:24:26,109 [classy] Setting parameters: {'Omega_m': 0.7460764282280585, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:26,153 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 113.98093873759065}
2023-07-02 10:24:26,153 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:26,155 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.23299
2023-07-02 10:24:26,155 [model] Computed derived parameters: {}
2023-07-02 10:24:26,155 [model] Posterior to be computed for parameters {'Omega_m': 0.5845237762772991}
2023-07-02 10:24:26,155 [prior] Evaluating prior at array([0.58452378])
2023-07-02 10:24:26,155 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:26,155 [model] Got input parameters: {'Omega_m': 0.5845237762772991, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:26,155 [classy] Got parameters {'Omega_m': 0.5845237762772991, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:26,155 [classy] Computing new state
2023-07-02 10:24:26,155 [classy] Setting parameters: {'Omega_m': 0.5845237762772991, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:26,202 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 123.27836859667431}
2023-07-02 10:24:26,202 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:26,203 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.62855
2023-07-02 10:24:26,204 [model] Computed derived parameters: {}
2023-07-02 10:24:26,204 [model] Posterior to be computed for parameters {'Omega_m': 0.06924054558443976}
2023-07-02 10:24:26,204 [prior] Evaluating prior at array([0.06924055])
2023-07-02 10:24:26,204 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:26,204 [model] Posterior to be computed for parameters {'Omega_m': 0.5985162204616779}
2023-07-02 10:24:26,204 [prior] Evaluating prior at array([0.59851622])
2023-07-02 10:24:26,204 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:26,204 [model] Got input parameters: {'Omega_m': 0.5985162204616779, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:26,204 [classy] Got parameters {'Omega_m': 0.5985162204616779, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:26,204 [classy] Computing new state
2023-07-02 10:24:26,204 [classy] Setting parameters: {'Omega_m': 0.5985162204616779, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:26,251 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 122.37101734279705}
2023-07-02 10:24:26,251 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:26,253 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.84012
2023-07-02 10:24:26,253 [model] Computed derived parameters: {}
2023-07-02 10:24:26,253 [model] Posterior to be computed for parameters {'Omega_m': 0.2775269429012641}
2023-07-02 10:24:26,253 [prior] Evaluating prior at array([0.27752694])
2023-07-02 10:24:26,254 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:26,254 [model] Got input parameters: {'Omega_m': 0.2775269429012641, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:26,254 [classy] Got parameters {'Omega_m': 0.2775269429012641, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:26,254 [classy] Computing new state
2023-07-02 10:24:26,254 [classy] Setting parameters: {'Omega_m': 0.2775269429012641, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:26,301 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.6883259660247}
2023-07-02 10:24:26,301 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:26,303 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0821969
2023-07-02 10:24:26,303 [model] Computed derived parameters: {}
2023-07-02 10:24:26,303 [mcmc] New sample, #163:
Omega_m:0.4731495
2023-07-02 10:24:26,304 [model] Posterior to be computed for parameters {'Omega_m': 0.16395279632349347}
2023-07-02 10:24:26,304 [prior] Evaluating prior at array([0.1639528])
2023-07-02 10:24:26,304 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:26,304 [model] Got input parameters: {'Omega_m': 0.16395279632349347, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:26,304 [classy] Got parameters {'Omega_m': 0.16395279632349347, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:26,304 [classy] Computing new state
2023-07-02 10:24:26,304 [classy] Setting parameters: {'Omega_m': 0.16395279632349347, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:26,351 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 170.2110087133082}
2023-07-02 10:24:26,351 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:26,353 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.09419
2023-07-02 10:24:26,353 [model] Computed derived parameters: {}
2023-07-02 10:24:26,353 [model] Posterior to be computed for parameters {'Omega_m': 0.2100183328556683}
2023-07-02 10:24:26,353 [prior] Evaluating prior at array([0.21001833])
2023-07-02 10:24:26,353 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:26,353 [model] Got input parameters: {'Omega_m': 0.2100183328556683, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:26,354 [classy] Got parameters {'Omega_m': 0.2100183328556683, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:26,354 [classy] Computing new state
2023-07-02 10:24:26,354 [classy] Setting parameters: {'Omega_m': 0.2100183328556683, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:26,400 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 161.76652434581797}
2023-07-02 10:24:26,400 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:26,402 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.855817
2023-07-02 10:24:26,402 [model] Computed derived parameters: {}
2023-07-02 10:24:26,402 [mcmc] New sample, #164:
Omega_m:0.2775269
2023-07-02 10:24:26,402 [model] Posterior to be computed for parameters {'Omega_m': 0.35683882831770697}
2023-07-02 10:24:26,402 [prior] Evaluating prior at array([0.35683883])
2023-07-02 10:24:26,403 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:26,403 [model] Got input parameters: {'Omega_m': 0.35683882831770697, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:26,403 [classy] Got parameters {'Omega_m': 0.35683882831770697, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:26,403 [classy] Computing new state
2023-07-02 10:24:26,403 [classy] Setting parameters: {'Omega_m': 0.35683882831770697, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:26,450 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.2359771346703}
2023-07-02 10:24:26,450 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:26,452 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.108718
2023-07-02 10:24:26,452 [model] Computed derived parameters: {}
2023-07-02 10:24:26,452 [mcmc] New sample, #165:
Omega_m:0.2100183
2023-07-02 10:24:26,452 [model] Posterior to be computed for parameters {'Omega_m': 0.27206426005905776}
2023-07-02 10:24:26,452 [prior] Evaluating prior at array([0.27206426])
2023-07-02 10:24:26,452 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:26,452 [model] Got input parameters: {'Omega_m': 0.27206426005905776, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:26,452 [classy] Got parameters {'Omega_m': 0.27206426005905776, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:26,452 [classy] Computing new state
2023-07-02 10:24:26,452 [classy] Setting parameters: {'Omega_m': 0.27206426005905776, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:26,504 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.42336273891743}
2023-07-02 10:24:26,504 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:26,506 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.111442
2023-07-02 10:24:26,506 [model] Computed derived parameters: {}
2023-07-02 10:24:26,506 [mcmc] New sample, #166:
Omega_m:0.3568388
2023-07-02 10:24:26,506 [model] Posterior to be computed for parameters {'Omega_m': 0.14282092452913356}
2023-07-02 10:24:26,506 [prior] Evaluating prior at array([0.14282092])
2023-07-02 10:24:26,506 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:26,506 [model] Got input parameters: {'Omega_m': 0.14282092452913356, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:26,506 [classy] Got parameters {'Omega_m': 0.14282092452913356, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:26,507 [classy] Computing new state
2023-07-02 10:24:26,507 [classy] Setting parameters: {'Omega_m': 0.14282092452913356, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:26,557 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 174.66174457862428}
2023-07-02 10:24:26,557 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:26,559 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.95065
2023-07-02 10:24:26,559 [model] Computed derived parameters: {}
2023-07-02 10:24:26,559 [model] Posterior to be computed for parameters {'Omega_m': -0.26293376211527425}
2023-07-02 10:24:26,559 [prior] Evaluating prior at array([-0.26293376])
2023-07-02 10:24:26,560 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:26,560 [model] Posterior to be computed for parameters {'Omega_m': 1.1045725082869593}
2023-07-02 10:24:26,560 [prior] Evaluating prior at array([1.10457251])
2023-07-02 10:24:26,560 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:26,560 [model] Posterior to be computed for parameters {'Omega_m': 0.3884939697145821}
2023-07-02 10:24:26,560 [prior] Evaluating prior at array([0.38849397])
2023-07-02 10:24:26,560 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:26,560 [model] Got input parameters: {'Omega_m': 0.3884939697145821, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:26,560 [classy] Got parameters {'Omega_m': 0.3884939697145821, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:26,560 [classy] Computing new state
2023-07-02 10:24:26,560 [classy] Setting parameters: {'Omega_m': 0.3884939697145821, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:26,611 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 138.990168970512}
2023-07-02 10:24:26,611 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:26,612 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.297146
2023-07-02 10:24:26,613 [model] Computed derived parameters: {}
2023-07-02 10:24:26,613 [model] Posterior to be computed for parameters {'Omega_m': 0.25568947353622556}
2023-07-02 10:24:26,613 [prior] Evaluating prior at array([0.25568947])
2023-07-02 10:24:26,613 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:26,613 [model] Got input parameters: {'Omega_m': 0.25568947353622556, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:26,613 [classy] Got parameters {'Omega_m': 0.25568947353622556, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:26,613 [classy] Computing new state
2023-07-02 10:24:26,613 [classy] Setting parameters: {'Omega_m': 0.25568947353622556, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:26,664 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 154.70412042524313}
2023-07-02 10:24:26,664 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:26,666 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.229941
2023-07-02 10:24:26,667 [model] Computed derived parameters: {}
2023-07-02 10:24:26,667 [mcmc] New sample, #167:
Omega_m:0.2720643
2023-07-02 10:24:26,667 [model] Posterior to be computed for parameters {'Omega_m': -0.12012007550950393}
2023-07-02 10:24:26,667 [prior] Evaluating prior at array([-0.12012008])
2023-07-02 10:24:26,667 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:26,667 [model] Posterior to be computed for parameters {'Omega_m': 0.047758830547878856}
2023-07-02 10:24:26,667 [prior] Evaluating prior at array([0.04775883])
2023-07-02 10:24:26,667 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:26,667 [model] Posterior to be computed for parameters {'Omega_m': 0.1424692906878532}
2023-07-02 10:24:26,667 [prior] Evaluating prior at array([0.14246929])
2023-07-02 10:24:26,667 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:26,667 [model] Got input parameters: {'Omega_m': 0.1424692906878532, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:26,667 [classy] Got parameters {'Omega_m': 0.1424692906878532, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:26,667 [classy] Computing new state
2023-07-02 10:24:26,668 [classy] Setting parameters: {'Omega_m': 0.1424692906878532, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:26,717 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 174.73943969517296}
2023-07-02 10:24:26,717 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:26,719 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.96681
2023-07-02 10:24:26,719 [model] Computed derived parameters: {}
2023-07-02 10:24:26,719 [model] Posterior to be computed for parameters {'Omega_m': 0.43445417868177993}
2023-07-02 10:24:26,719 [prior] Evaluating prior at array([0.43445418])
2023-07-02 10:24:26,719 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:26,719 [model] Got input parameters: {'Omega_m': 0.43445417868177993, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:26,719 [classy] Got parameters {'Omega_m': 0.43445417868177993, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:26,719 [classy] Computing new state
2023-07-02 10:24:26,719 [classy] Setting parameters: {'Omega_m': 0.43445417868177993, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:26,767 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 134.69783423555538}
2023-07-02 10:24:26,767 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:26,769 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.694648
2023-07-02 10:24:26,769 [model] Computed derived parameters: {}
2023-07-02 10:24:26,769 [model] Posterior to be computed for parameters {'Omega_m': -0.02269367400022987}
2023-07-02 10:24:26,769 [prior] Evaluating prior at array([-0.02269367])
2023-07-02 10:24:26,769 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:26,769 [model] Posterior to be computed for parameters {'Omega_m': 0.5685277025739688}
2023-07-02 10:24:26,769 [prior] Evaluating prior at array([0.5685277])
2023-07-02 10:24:26,770 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:26,770 [model] Got input parameters: {'Omega_m': 0.5685277025739688, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:26,770 [classy] Got parameters {'Omega_m': 0.5685277025739688, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:26,770 [classy] Computing new state
2023-07-02 10:24:26,770 [classy] Setting parameters: {'Omega_m': 0.5685277025739688, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:26,817 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 124.34379622318833}
2023-07-02 10:24:26,817 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:26,819 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.39142
2023-07-02 10:24:26,819 [model] Computed derived parameters: {}
2023-07-02 10:24:26,819 [model] Posterior to be computed for parameters {'Omega_m': 0.8050832595443578}
2023-07-02 10:24:26,819 [prior] Evaluating prior at array([0.80508326])
2023-07-02 10:24:26,819 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:26,819 [model] Got input parameters: {'Omega_m': 0.8050832595443578, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:26,819 [classy] Got parameters {'Omega_m': 0.8050832595443578, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:26,819 [classy] Computing new state
2023-07-02 10:24:26,819 [classy] Setting parameters: {'Omega_m': 0.8050832595443578, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:26,864 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 111.11855680193099}
2023-07-02 10:24:26,864 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:26,866 [bao_likelihood.baolikelihood] Computed log-likelihood = -6.23864
2023-07-02 10:24:26,866 [model] Computed derived parameters: {}
2023-07-02 10:24:26,866 [model] Posterior to be computed for parameters {'Omega_m': 0.6927934489172098}
2023-07-02 10:24:26,866 [prior] Evaluating prior at array([0.69279345])
2023-07-02 10:24:26,867 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:26,867 [model] Got input parameters: {'Omega_m': 0.6927934489172098, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:26,867 [classy] Got parameters {'Omega_m': 0.6927934489172098, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:26,867 [classy] Computing new state
2023-07-02 10:24:26,867 [classy] Setting parameters: {'Omega_m': 0.6927934489172098, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:26,912 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 116.78687977312518}
2023-07-02 10:24:26,912 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:26,914 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.34276
2023-07-02 10:24:26,914 [model] Computed derived parameters: {}
2023-07-02 10:24:26,914 [model] Posterior to be computed for parameters {'Omega_m': 0.23325763467043187}
2023-07-02 10:24:26,914 [prior] Evaluating prior at array([0.23325763])
2023-07-02 10:24:26,915 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:26,915 [model] Got input parameters: {'Omega_m': 0.23325763467043187, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:26,915 [classy] Got parameters {'Omega_m': 0.23325763467043187, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:26,915 [classy] Computing new state
2023-07-02 10:24:26,915 [classy] Setting parameters: {'Omega_m': 0.23325763467043187, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:26,961 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 158.03360777233948}
2023-07-02 10:24:26,961 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:26,963 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.47697
2023-07-02 10:24:26,963 [model] Computed derived parameters: {}
2023-07-02 10:24:26,963 [mcmc] New sample, #168:
Omega_m:0.2556895
2023-07-02 10:24:26,963 [model] Posterior to be computed for parameters {'Omega_m': 0.1422117643113403}
2023-07-02 10:24:26,963 [prior] Evaluating prior at array([0.14221176])
2023-07-02 10:24:26,963 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:26,963 [model] Got input parameters: {'Omega_m': 0.1422117643113403, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:26,963 [classy] Got parameters {'Omega_m': 0.1422117643113403, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:26,963 [classy] Computing new state
2023-07-02 10:24:26,963 [classy] Setting parameters: {'Omega_m': 0.1422117643113403, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:27,011 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 174.79641830869977}
2023-07-02 10:24:27,011 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:27,014 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.97869
2023-07-02 10:24:27,014 [model] Computed derived parameters: {}
2023-07-02 10:24:27,014 [model] Posterior to be computed for parameters {'Omega_m': -0.009196565651528071}
2023-07-02 10:24:27,015 [prior] Evaluating prior at array([-0.00919657])
2023-07-02 10:24:27,015 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:27,015 [model] Posterior to be computed for parameters {'Omega_m': 0.534066959013109}
2023-07-02 10:24:27,015 [prior] Evaluating prior at array([0.53406696])
2023-07-02 10:24:27,015 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:27,015 [model] Got input parameters: {'Omega_m': 0.534066959013109, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:27,015 [classy] Got parameters {'Omega_m': 0.534066959013109, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:27,015 [classy] Computing new state
2023-07-02 10:24:27,015 [classy] Setting parameters: {'Omega_m': 0.534066959013109, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:27,071 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 126.74834780876553}
2023-07-02 10:24:27,071 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:27,074 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.90036
2023-07-02 10:24:27,074 [model] Computed derived parameters: {}
2023-07-02 10:24:27,074 [mcmc] New sample, #169:
Omega_m:0.2332576
2023-07-02 10:24:27,074 [model] Posterior to be computed for parameters {'Omega_m': 0.10478821118155307}
2023-07-02 10:24:27,074 [prior] Evaluating prior at array([0.10478821])
2023-07-02 10:24:27,074 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:27,074 [model] Got input parameters: {'Omega_m': 0.10478821118155307, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:27,074 [classy] Got parameters {'Omega_m': 0.10478821118155307, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:27,074 [classy] Computing new state
2023-07-02 10:24:27,074 [classy] Setting parameters: {'Omega_m': 0.10478821118155307, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:27,119 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 183.88359980630298}
2023-07-02 10:24:27,119 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:27,121 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.14778
2023-07-02 10:24:27,121 [model] Computed derived parameters: {}
2023-07-02 10:24:27,121 [model] Posterior to be computed for parameters {'Omega_m': 0.550668738047621}
2023-07-02 10:24:27,122 [prior] Evaluating prior at array([0.55066874])
2023-07-02 10:24:27,122 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:27,122 [model] Got input parameters: {'Omega_m': 0.550668738047621, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:27,122 [classy] Got parameters {'Omega_m': 0.550668738047621, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:27,122 [classy] Computing new state
2023-07-02 10:24:27,122 [classy] Setting parameters: {'Omega_m': 0.550668738047621, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:27,168 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 125.57061084606978}
2023-07-02 10:24:27,168 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:27,170 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.13331
2023-07-02 10:24:27,170 [model] Computed derived parameters: {}
2023-07-02 10:24:27,170 [mcmc] New sample, #170:
Omega_m:0.534067
2023-07-02 10:24:27,170 [model] Posterior to be computed for parameters {'Omega_m': 0.6007601829917492}
2023-07-02 10:24:27,170 [prior] Evaluating prior at array([0.60076018])
2023-07-02 10:24:27,170 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:27,170 [model] Got input parameters: {'Omega_m': 0.6007601829917492, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:27,170 [classy] Got parameters {'Omega_m': 0.6007601829917492, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:27,170 [classy] Computing new state
2023-07-02 10:24:27,170 [classy] Setting parameters: {'Omega_m': 0.6007601829917492, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:27,218 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 122.22756796216372}
2023-07-02 10:24:27,218 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:27,220 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.87438
2023-07-02 10:24:27,220 [model] Computed derived parameters: {}
2023-07-02 10:24:27,220 [model] Posterior to be computed for parameters {'Omega_m': 0.4526248853094927}
2023-07-02 10:24:27,220 [prior] Evaluating prior at array([0.45262489])
2023-07-02 10:24:27,220 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:27,220 [model] Got input parameters: {'Omega_m': 0.4526248853094927, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:27,220 [classy] Got parameters {'Omega_m': 0.4526248853094927, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:27,220 [classy] Computing new state
2023-07-02 10:24:27,220 [classy] Setting parameters: {'Omega_m': 0.4526248853094927, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:27,268 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 133.12094456354563}
2023-07-02 10:24:27,268 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:27,270 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.884374
2023-07-02 10:24:27,270 [model] Computed derived parameters: {}
2023-07-02 10:24:27,270 [mcmc] New sample, #171:
Omega_m:0.5506687
2023-07-02 10:24:27,270 [model] Posterior to be computed for parameters {'Omega_m': 0.12507670821837036}
2023-07-02 10:24:27,270 [prior] Evaluating prior at array([0.12507671])
2023-07-02 10:24:27,270 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:27,270 [model] Got input parameters: {'Omega_m': 0.12507670821837036, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:27,270 [classy] Got parameters {'Omega_m': 0.12507670821837036, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:27,271 [classy] Computing new state
2023-07-02 10:24:27,271 [classy] Setting parameters: {'Omega_m': 0.12507670821837036, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:27,317 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 178.74797904890733}
2023-07-02 10:24:27,317 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:27,319 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.85545
2023-07-02 10:24:27,319 [model] Computed derived parameters: {}
2023-07-02 10:24:27,319 [model] Posterior to be computed for parameters {'Omega_m': 0.6676719936567093}
2023-07-02 10:24:27,319 [prior] Evaluating prior at array([0.66767199])
2023-07-02 10:24:27,319 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:27,319 [model] Got input parameters: {'Omega_m': 0.6676719936567093, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:27,319 [classy] Got parameters {'Omega_m': 0.6676719936567093, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:27,319 [classy] Computing new state
2023-07-02 10:24:27,319 [classy] Setting parameters: {'Omega_m': 0.6676719936567093, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:27,364 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 118.19181827627244}
2023-07-02 10:24:27,364 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:27,366 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.93157
2023-07-02 10:24:27,366 [model] Computed derived parameters: {}
2023-07-02 10:24:27,366 [model] Posterior to be computed for parameters {'Omega_m': 0.757040022077594}
2023-07-02 10:24:27,366 [prior] Evaluating prior at array([0.75704002])
2023-07-02 10:24:27,366 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:27,366 [model] Got input parameters: {'Omega_m': 0.757040022077594, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:27,366 [classy] Got parameters {'Omega_m': 0.757040022077594, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:27,366 [classy] Computing new state
2023-07-02 10:24:27,367 [classy] Setting parameters: {'Omega_m': 0.757040022077594, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:27,412 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 113.43069203095706}
2023-07-02 10:24:27,412 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:27,414 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.41855
2023-07-02 10:24:27,414 [model] Computed derived parameters: {}
2023-07-02 10:24:27,414 [model] Posterior to be computed for parameters {'Omega_m': 0.5341352573318914}
2023-07-02 10:24:27,414 [prior] Evaluating prior at array([0.53413526])
2023-07-02 10:24:27,414 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:27,414 [model] Got input parameters: {'Omega_m': 0.5341352573318914, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:27,414 [classy] Got parameters {'Omega_m': 0.5341352573318914, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:27,414 [classy] Computing new state
2023-07-02 10:24:27,414 [classy] Setting parameters: {'Omega_m': 0.5341352573318914, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:27,461 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 126.74342532430178}
2023-07-02 10:24:27,461 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:27,462 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.90131
2023-07-02 10:24:27,463 [model] Computed derived parameters: {}
2023-07-02 10:24:27,463 [mcmc] New sample, #172:
Omega_m:0.4526249
2023-07-02 10:24:27,463 [model] Posterior to be computed for parameters {'Omega_m': 0.2764139728732288}
2023-07-02 10:24:27,463 [prior] Evaluating prior at array([0.27641397])
2023-07-02 10:24:27,463 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:27,463 [model] Got input parameters: {'Omega_m': 0.2764139728732288, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:27,463 [classy] Got parameters {'Omega_m': 0.2764139728732288, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:27,463 [classy] Computing new state
2023-07-02 10:24:27,463 [classy] Setting parameters: {'Omega_m': 0.2764139728732288, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:27,509 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.83707758514967}
2023-07-02 10:24:27,509 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:27,511 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0877608
2023-07-02 10:24:27,511 [model] Computed derived parameters: {}
2023-07-02 10:24:27,511 [mcmc] New sample, #173:
Omega_m:0.5341353
2023-07-02 10:24:27,511 [model] Posterior to be computed for parameters {'Omega_m': -0.04424440025705728}
2023-07-02 10:24:27,511 [prior] Evaluating prior at array([-0.0442444])
2023-07-02 10:24:27,511 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:27,512 [model] Posterior to be computed for parameters {'Omega_m': 0.5266753853360975}
2023-07-02 10:24:27,512 [prior] Evaluating prior at array([0.52667539])
2023-07-02 10:24:27,512 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:27,512 [model] Got input parameters: {'Omega_m': 0.5266753853360975, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:27,512 [classy] Got parameters {'Omega_m': 0.5266753853360975, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:27,512 [classy] Computing new state
2023-07-02 10:24:27,512 [classy] Setting parameters: {'Omega_m': 0.5266753853360975, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:27,559 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 127.28479833561015}
2023-07-02 10:24:27,559 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:27,561 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.79903
2023-07-02 10:24:27,561 [model] Computed derived parameters: {}
2023-07-02 10:24:27,561 [model] Posterior to be computed for parameters {'Omega_m': 0.05567446170158566}
2023-07-02 10:24:27,561 [prior] Evaluating prior at array([0.05567446])
2023-07-02 10:24:27,561 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:27,561 [model] Posterior to be computed for parameters {'Omega_m': 0.5413965954638591}
2023-07-02 10:24:27,561 [prior] Evaluating prior at array([0.5413966])
2023-07-02 10:24:27,561 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:27,561 [model] Got input parameters: {'Omega_m': 0.5413965954638591, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:27,561 [classy] Got parameters {'Omega_m': 0.5413965954638591, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:27,561 [classy] Computing new state
2023-07-02 10:24:27,561 [classy] Setting parameters: {'Omega_m': 0.5413965954638591, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:27,608 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 126.22382391579825}
2023-07-02 10:24:27,608 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:27,610 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.00232
2023-07-02 10:24:27,610 [model] Computed derived parameters: {}
2023-07-02 10:24:27,610 [model] Posterior to be computed for parameters {'Omega_m': 0.5154868577245266}
2023-07-02 10:24:27,610 [prior] Evaluating prior at array([0.51548686])
2023-07-02 10:24:27,610 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:27,610 [model] Got input parameters: {'Omega_m': 0.5154868577245266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:27,610 [classy] Got parameters {'Omega_m': 0.5154868577245266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:27,610 [classy] Computing new state
2023-07-02 10:24:27,610 [classy] Setting parameters: {'Omega_m': 0.5154868577245266, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:27,657 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 128.11159440930913}
2023-07-02 10:24:27,657 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:27,659 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.64864
2023-07-02 10:24:27,659 [model] Computed derived parameters: {}
2023-07-02 10:24:27,659 [model] Posterior to be computed for parameters {'Omega_m': 0.5991998935214596}
2023-07-02 10:24:27,659 [prior] Evaluating prior at array([0.59919989])
2023-07-02 10:24:27,659 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:27,659 [model] Got input parameters: {'Omega_m': 0.5991998935214596, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:27,660 [classy] Got parameters {'Omega_m': 0.5991998935214596, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:27,660 [classy] Computing new state
2023-07-02 10:24:27,660 [classy] Setting parameters: {'Omega_m': 0.5991998935214596, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:27,707 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 122.32725275527292}
2023-07-02 10:24:27,707 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:27,708 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.85055
2023-07-02 10:24:27,709 [model] Computed derived parameters: {}
2023-07-02 10:24:27,709 [model] Posterior to be computed for parameters {'Omega_m': 0.13900100346682256}
2023-07-02 10:24:27,709 [prior] Evaluating prior at array([0.139001])
2023-07-02 10:24:27,709 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:27,709 [model] Got input parameters: {'Omega_m': 0.13900100346682256, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:27,709 [classy] Got parameters {'Omega_m': 0.13900100346682256, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:27,709 [classy] Computing new state
2023-07-02 10:24:27,709 [classy] Setting parameters: {'Omega_m': 0.13900100346682256, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:27,756 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 175.51259965267232}
2023-07-02 10:24:27,756 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:27,758 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.12983
2023-07-02 10:24:27,758 [model] Computed derived parameters: {}
2023-07-02 10:24:27,758 [model] Posterior to be computed for parameters {'Omega_m': 0.26773400495235694}
2023-07-02 10:24:27,758 [prior] Evaluating prior at array([0.267734])
2023-07-02 10:24:27,758 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:27,758 [model] Got input parameters: {'Omega_m': 0.26773400495235694, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:27,758 [classy] Got parameters {'Omega_m': 0.26773400495235694, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:27,758 [classy] Computing new state
2023-07-02 10:24:27,758 [classy] Setting parameters: {'Omega_m': 0.26773400495235694, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:27,806 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.01503623821222}
2023-07-02 10:24:27,806 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:27,807 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.138167
2023-07-02 10:24:27,808 [model] Computed derived parameters: {}
2023-07-02 10:24:27,808 [mcmc] New sample, #174:
Omega_m:0.276414
2023-07-02 10:24:27,808 [model] Posterior to be computed for parameters {'Omega_m': 0.45183786622000616}
2023-07-02 10:24:27,808 [prior] Evaluating prior at array([0.45183787])
2023-07-02 10:24:27,808 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:27,808 [model] Got input parameters: {'Omega_m': 0.45183786622000616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:27,808 [classy] Got parameters {'Omega_m': 0.45183786622000616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:27,808 [classy] Computing new state
2023-07-02 10:24:27,808 [classy] Setting parameters: {'Omega_m': 0.45183786622000616, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:27,855 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 133.1879490254829}
2023-07-02 10:24:27,855 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:27,857 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.875825
2023-07-02 10:24:27,857 [model] Computed derived parameters: {}
2023-07-02 10:24:27,857 [mcmc] New sample, #175:
Omega_m:0.267734
2023-07-02 10:24:27,857 [model] Posterior to be computed for parameters {'Omega_m': 0.3085329635489119}
2023-07-02 10:24:27,857 [prior] Evaluating prior at array([0.30853296])
2023-07-02 10:24:27,857 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:27,857 [model] Got input parameters: {'Omega_m': 0.3085329635489119, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:27,857 [classy] Got parameters {'Omega_m': 0.3085329635489119, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:27,857 [classy] Computing new state
2023-07-02 10:24:27,857 [classy] Setting parameters: {'Omega_m': 0.3085329635489119, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:27,905 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.73823652512266}
2023-07-02 10:24:27,905 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:27,906 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00116921
2023-07-02 10:24:27,907 [model] Computed derived parameters: {}
2023-07-02 10:24:27,907 [mcmc] New sample, #176:
Omega_m:0.4518379
2023-07-02 10:24:27,907 [model] Posterior to be computed for parameters {'Omega_m': -0.03285669777687322}
2023-07-02 10:24:27,907 [prior] Evaluating prior at array([-0.0328567])
2023-07-02 10:24:27,907 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:27,907 [model] Posterior to be computed for parameters {'Omega_m': 0.5304728679004929}
2023-07-02 10:24:27,907 [prior] Evaluating prior at array([0.53047287])
2023-07-02 10:24:27,907 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:27,907 [model] Got input parameters: {'Omega_m': 0.5304728679004929, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:27,907 [classy] Got parameters {'Omega_m': 0.5304728679004929, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:27,907 [classy] Computing new state
2023-07-02 10:24:27,907 [classy] Setting parameters: {'Omega_m': 0.5304728679004929, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:27,955 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 127.0082292709288}
2023-07-02 10:24:27,955 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:27,957 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.85091
2023-07-02 10:24:27,957 [model] Computed derived parameters: {}
2023-07-02 10:24:27,957 [model] Posterior to be computed for parameters {'Omega_m': -0.08845110240715992}
2023-07-02 10:24:27,957 [prior] Evaluating prior at array([-0.0884511])
2023-07-02 10:24:27,957 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:27,957 [model] Posterior to be computed for parameters {'Omega_m': 1.3580768616683812}
2023-07-02 10:24:27,957 [prior] Evaluating prior at array([1.35807686])
2023-07-02 10:24:27,957 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:27,957 [model] Posterior to be computed for parameters {'Omega_m': 0.04270312622917444}
2023-07-02 10:24:27,957 [prior] Evaluating prior at array([0.04270313])
2023-07-02 10:24:27,957 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:27,958 [model] Posterior to be computed for parameters {'Omega_m': 0.41553439362310207}
2023-07-02 10:24:27,958 [prior] Evaluating prior at array([0.41553439])
2023-07-02 10:24:27,958 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:27,958 [model] Got input parameters: {'Omega_m': 0.41553439362310207, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:27,958 [classy] Got parameters {'Omega_m': 0.41553439362310207, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:27,958 [classy] Computing new state
2023-07-02 10:24:27,958 [classy] Setting parameters: {'Omega_m': 0.41553439362310207, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:28,005 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 136.4094049992323}
2023-07-02 10:24:28,005 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:28,007 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.515515
2023-07-02 10:24:28,007 [model] Computed derived parameters: {}
2023-07-02 10:24:28,007 [model] Posterior to be computed for parameters {'Omega_m': 0.5909026749520173}
2023-07-02 10:24:28,007 [prior] Evaluating prior at array([0.59090267])
2023-07-02 10:24:28,007 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:28,007 [model] Got input parameters: {'Omega_m': 0.5909026749520173, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:28,007 [classy] Got parameters {'Omega_m': 0.5909026749520173, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:28,007 [classy] Computing new state
2023-07-02 10:24:28,007 [classy] Setting parameters: {'Omega_m': 0.5909026749520173, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:28,055 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 122.86194680451645}
2023-07-02 10:24:28,055 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:28,057 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.72454
2023-07-02 10:24:28,057 [model] Computed derived parameters: {}
2023-07-02 10:24:28,057 [model] Posterior to be computed for parameters {'Omega_m': -0.0832441033156755}
2023-07-02 10:24:28,057 [prior] Evaluating prior at array([-0.0832441])
2023-07-02 10:24:28,057 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:28,058 [model] Posterior to be computed for parameters {'Omega_m': 0.2851000731093252}
2023-07-02 10:24:28,058 [prior] Evaluating prior at array([0.28510007])
2023-07-02 10:24:28,058 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:28,058 [model] Got input parameters: {'Omega_m': 0.2851000731093252, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:28,058 [classy] Got parameters {'Omega_m': 0.2851000731093252, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:28,058 [classy] Computing new state
2023-07-02 10:24:28,058 [classy] Setting parameters: {'Omega_m': 0.2851000731093252, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:28,105 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.6894681204715}
2023-07-02 10:24:28,105 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:28,106 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0495185
2023-07-02 10:24:28,107 [model] Computed derived parameters: {}
2023-07-02 10:24:28,107 [mcmc] New sample, #177:
Omega_m:0.308533
2023-07-02 10:24:28,107 [model] Posterior to be computed for parameters {'Omega_m': 0.47332113587248015}
2023-07-02 10:24:28,107 [prior] Evaluating prior at array([0.47332114])
2023-07-02 10:24:28,107 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:28,107 [model] Got input parameters: {'Omega_m': 0.47332113587248015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:28,107 [classy] Got parameters {'Omega_m': 0.47332113587248015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:28,107 [classy] Computing new state
2023-07-02 10:24:28,107 [classy] Setting parameters: {'Omega_m': 0.47332113587248015, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:28,156 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 131.39896641565284}
2023-07-02 10:24:28,156 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:28,158 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.11906
2023-07-02 10:24:28,158 [model] Computed derived parameters: {}
2023-07-02 10:24:28,158 [model] Posterior to be computed for parameters {'Omega_m': -0.0208845242336802}
2023-07-02 10:24:28,158 [prior] Evaluating prior at array([-0.02088452])
2023-07-02 10:24:28,158 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:28,158 [model] Posterior to be computed for parameters {'Omega_m': 0.17422918548014144}
2023-07-02 10:24:28,158 [prior] Evaluating prior at array([0.17422919])
2023-07-02 10:24:28,158 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:28,158 [model] Got input parameters: {'Omega_m': 0.17422918548014144, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:28,158 [classy] Got parameters {'Omega_m': 0.17422918548014144, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:28,158 [classy] Computing new state
2023-07-02 10:24:28,159 [classy] Setting parameters: {'Omega_m': 0.17422918548014144, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:28,205 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 168.18946311664695}
2023-07-02 10:24:28,205 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:28,207 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.75085
2023-07-02 10:24:28,207 [model] Computed derived parameters: {}
2023-07-02 10:24:28,207 [model] Posterior to be computed for parameters {'Omega_m': 0.7483208209499159}
2023-07-02 10:24:28,207 [prior] Evaluating prior at array([0.74832082])
2023-07-02 10:24:28,207 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:28,207 [model] Got input parameters: {'Omega_m': 0.7483208209499159, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:28,207 [classy] Got parameters {'Omega_m': 0.7483208209499159, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:28,207 [classy] Computing new state
2023-07-02 10:24:28,207 [classy] Setting parameters: {'Omega_m': 0.7483208209499159, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:28,253 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 113.86756945572505}
2023-07-02 10:24:28,253 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:28,255 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.27092
2023-07-02 10:24:28,255 [model] Computed derived parameters: {}
2023-07-02 10:24:28,255 [model] Posterior to be computed for parameters {'Omega_m': 0.5270729908760221}
2023-07-02 10:24:28,255 [prior] Evaluating prior at array([0.52707299])
2023-07-02 10:24:28,255 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:28,255 [model] Got input parameters: {'Omega_m': 0.5270729908760221, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:28,255 [classy] Got parameters {'Omega_m': 0.5270729908760221, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:28,255 [classy] Computing new state
2023-07-02 10:24:28,255 [classy] Setting parameters: {'Omega_m': 0.5270729908760221, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:28,301 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 127.25574585074364}
2023-07-02 10:24:28,301 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:28,304 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.80444
2023-07-02 10:24:28,304 [model] Computed derived parameters: {}
2023-07-02 10:24:28,304 [mcmc] New sample, #178:
Omega_m:0.2851001
2023-07-02 10:24:28,304 [model] Posterior to be computed for parameters {'Omega_m': 0.2403619553169652}
2023-07-02 10:24:28,304 [prior] Evaluating prior at array([0.24036196])
2023-07-02 10:24:28,305 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:28,305 [model] Got input parameters: {'Omega_m': 0.2403619553169652, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:28,305 [classy] Got parameters {'Omega_m': 0.2403619553169652, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:28,305 [classy] Computing new state
2023-07-02 10:24:28,305 [classy] Setting parameters: {'Omega_m': 0.2403619553169652, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:28,351 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 156.95186704056877}
2023-07-02 10:24:28,351 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:28,354 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.387194
2023-07-02 10:24:28,354 [model] Computed derived parameters: {}
2023-07-02 10:24:28,354 [mcmc] New sample, #179:
Omega_m:0.527073
2023-07-02 10:24:28,354 [model] Posterior to be computed for parameters {'Omega_m': 0.3817540439306617}
2023-07-02 10:24:28,354 [prior] Evaluating prior at array([0.38175404])
2023-07-02 10:24:28,354 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:28,354 [model] Got input parameters: {'Omega_m': 0.3817540439306617, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:28,354 [classy] Got parameters {'Omega_m': 0.3817540439306617, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:28,354 [classy] Computing new state
2023-07-02 10:24:28,354 [classy] Setting parameters: {'Omega_m': 0.3817540439306617, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:28,400 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 139.659972009885}
2023-07-02 10:24:28,400 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:28,403 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.250477
2023-07-02 10:24:28,403 [model] Computed derived parameters: {}
2023-07-02 10:24:28,403 [mcmc] New sample, #180:
Omega_m:0.240362
2023-07-02 10:24:28,403 [model] Posterior to be computed for parameters {'Omega_m': 0.5108929214218408}
2023-07-02 10:24:28,403 [prior] Evaluating prior at array([0.51089292])
2023-07-02 10:24:28,403 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:28,403 [model] Got input parameters: {'Omega_m': 0.5108929214218408, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:28,403 [classy] Got parameters {'Omega_m': 0.5108929214218408, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:28,403 [classy] Computing new state
2023-07-02 10:24:28,403 [classy] Setting parameters: {'Omega_m': 0.5108929214218408, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:28,450 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 128.45633321788398}
2023-07-02 10:24:28,450 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:28,453 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.588
2023-07-02 10:24:28,453 [model] Computed derived parameters: {}
2023-07-02 10:24:28,453 [model] Posterior to be computed for parameters {'Omega_m': 0.06918960955578157}
2023-07-02 10:24:28,453 [prior] Evaluating prior at array([0.06918961])
2023-07-02 10:24:28,453 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:28,453 [model] Posterior to be computed for parameters {'Omega_m': 0.1850103480498319}
2023-07-02 10:24:28,453 [prior] Evaluating prior at array([0.18501035])
2023-07-02 10:24:28,453 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:28,453 [model] Got input parameters: {'Omega_m': 0.1850103480498319, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:28,453 [classy] Got parameters {'Omega_m': 0.1850103480498319, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:28,453 [classy] Computing new state
2023-07-02 10:24:28,454 [classy] Setting parameters: {'Omega_m': 0.1850103480498319, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:28,504 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 166.15874294749455}
2023-07-02 10:24:28,504 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:28,506 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.43533
2023-07-02 10:24:28,506 [model] Computed derived parameters: {}
2023-07-02 10:24:28,506 [mcmc] New sample, #181:
Omega_m:0.381754
2023-07-02 10:24:28,506 [model] Posterior to be computed for parameters {'Omega_m': 0.08242770385051884}
2023-07-02 10:24:28,506 [prior] Evaluating prior at array([0.0824277])
2023-07-02 10:24:28,506 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:28,506 [model] Posterior to be computed for parameters {'Omega_m': 0.2859260770913983}
2023-07-02 10:24:28,506 [prior] Evaluating prior at array([0.28592608])
2023-07-02 10:24:28,506 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:28,506 [model] Got input parameters: {'Omega_m': 0.2859260770913983, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:28,506 [classy] Got parameters {'Omega_m': 0.2859260770913983, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:28,506 [classy] Computing new state
2023-07-02 10:24:28,506 [classy] Setting parameters: {'Omega_m': 0.2859260770913983, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:28,558 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.58190192554164}
2023-07-02 10:24:28,558 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:28,560 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0464874
2023-07-02 10:24:28,560 [model] Computed derived parameters: {}
2023-07-02 10:24:28,560 [mcmc] New sample, #182:
Omega_m:0.1850103
2023-07-02 10:24:28,560 [model] Posterior to be computed for parameters {'Omega_m': 0.640498793144292}
2023-07-02 10:24:28,560 [prior] Evaluating prior at array([0.64049879])
2023-07-02 10:24:28,561 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:28,561 [model] Got input parameters: {'Omega_m': 0.640498793144292, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:28,561 [classy] Got parameters {'Omega_m': 0.640498793144292, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:28,561 [classy] Computing new state
2023-07-02 10:24:28,561 [classy] Setting parameters: {'Omega_m': 0.640498793144292, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:28,610 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 119.77667081684497}
2023-07-02 10:24:28,610 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:28,612 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.49473
2023-07-02 10:24:28,612 [model] Computed derived parameters: {}
2023-07-02 10:24:28,612 [model] Posterior to be computed for parameters {'Omega_m': 0.6158417773805812}
2023-07-02 10:24:28,612 [prior] Evaluating prior at array([0.61584178])
2023-07-02 10:24:28,612 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:28,612 [model] Got input parameters: {'Omega_m': 0.6158417773805812, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:28,612 [classy] Got parameters {'Omega_m': 0.6158417773805812, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:28,612 [classy] Computing new state
2023-07-02 10:24:28,612 [classy] Setting parameters: {'Omega_m': 0.6158417773805812, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:28,663 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 121.27782175578739}
2023-07-02 10:24:28,663 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:28,666 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.10691
2023-07-02 10:24:28,666 [model] Computed derived parameters: {}
2023-07-02 10:24:28,666 [model] Posterior to be computed for parameters {'Omega_m': 0.18381101836547764}
2023-07-02 10:24:28,666 [prior] Evaluating prior at array([0.18381102])
2023-07-02 10:24:28,666 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:28,666 [model] Got input parameters: {'Omega_m': 0.18381101836547764, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:28,666 [classy] Got parameters {'Omega_m': 0.18381101836547764, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:28,666 [classy] Computing new state
2023-07-02 10:24:28,666 [classy] Setting parameters: {'Omega_m': 0.18381101836547764, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:28,714 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 166.38030381078997}
2023-07-02 10:24:28,714 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:28,716 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.46831
2023-07-02 10:24:28,716 [model] Computed derived parameters: {}
2023-07-02 10:24:28,716 [model] Posterior to be computed for parameters {'Omega_m': 0.4944286144698772}
2023-07-02 10:24:28,716 [prior] Evaluating prior at array([0.49442861])
2023-07-02 10:24:28,716 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:28,716 [model] Got input parameters: {'Omega_m': 0.4944286144698772, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:28,716 [classy] Got parameters {'Omega_m': 0.4944286144698772, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:28,716 [classy] Computing new state
2023-07-02 10:24:28,716 [classy] Setting parameters: {'Omega_m': 0.4944286144698772, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:28,764 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 129.71816953033564}
2023-07-02 10:24:28,764 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:28,766 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.3763
2023-07-02 10:24:28,766 [model] Computed derived parameters: {}
2023-07-02 10:24:28,766 [model] Posterior to be computed for parameters {'Omega_m': 0.23034075303903057}
2023-07-02 10:24:28,766 [prior] Evaluating prior at array([0.23034075])
2023-07-02 10:24:28,766 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:28,766 [model] Got input parameters: {'Omega_m': 0.23034075303903057, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:28,766 [classy] Got parameters {'Omega_m': 0.23034075303903057, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:28,766 [classy] Computing new state
2023-07-02 10:24:28,766 [classy] Setting parameters: {'Omega_m': 0.23034075303903057, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:28,813 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 158.48549358881976}
2023-07-02 10:24:28,813 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:28,815 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.517161
2023-07-02 10:24:28,815 [model] Computed derived parameters: {}
2023-07-02 10:24:28,815 [mcmc] New sample, #183:
Omega_m:0.2859261
2023-07-02 10:24:28,815 [model] Posterior to be computed for parameters {'Omega_m': 0.010159662476791592}
2023-07-02 10:24:28,815 [prior] Evaluating prior at array([0.01015966])
2023-07-02 10:24:28,816 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:28,816 [model] Posterior to be computed for parameters {'Omega_m': -0.33642953335879144}
2023-07-02 10:24:28,816 [prior] Evaluating prior at array([-0.33642953])
2023-07-02 10:24:28,816 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:28,816 [model] Posterior to be computed for parameters {'Omega_m': 0.20254903196726934}
2023-07-02 10:24:28,816 [prior] Evaluating prior at array([0.20254903])
2023-07-02 10:24:28,816 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:28,816 [model] Got input parameters: {'Omega_m': 0.20254903196726934, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:28,816 [classy] Got parameters {'Omega_m': 0.20254903196726934, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:28,816 [classy] Computing new state
2023-07-02 10:24:28,816 [classy] Setting parameters: {'Omega_m': 0.20254903196726934, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:28,864 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 163.03484031123614}
2023-07-02 10:24:28,864 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:28,866 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.00851
2023-07-02 10:24:28,866 [model] Computed derived parameters: {}
2023-07-02 10:24:28,866 [mcmc] New sample, #184:
Omega_m:0.2303408
2023-07-02 10:24:28,866 [model] Posterior to be computed for parameters {'Omega_m': 0.11143582711414192}
2023-07-02 10:24:28,866 [prior] Evaluating prior at array([0.11143583])
2023-07-02 10:24:28,866 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:28,866 [model] Got input parameters: {'Omega_m': 0.11143582711414192, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:28,866 [classy] Got parameters {'Omega_m': 0.11143582711414192, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:28,866 [classy] Computing new state
2023-07-02 10:24:28,866 [classy] Setting parameters: {'Omega_m': 0.11143582711414192, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:28,912 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 182.14100128578502}
2023-07-02 10:24:28,912 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:28,914 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.69027
2023-07-02 10:24:28,915 [model] Computed derived parameters: {}
2023-07-02 10:24:28,915 [model] Posterior to be computed for parameters {'Omega_m': 0.3019958858575965}
2023-07-02 10:24:28,915 [prior] Evaluating prior at array([0.30199589])
2023-07-02 10:24:28,915 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:28,915 [model] Got input parameters: {'Omega_m': 0.3019958858575965, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:28,915 [classy] Got parameters {'Omega_m': 0.3019958858575965, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:28,915 [classy] Computing new state
2023-07-02 10:24:28,915 [classy] Setting parameters: {'Omega_m': 0.3019958858575965, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:28,962 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.541242924564}
2023-07-02 10:24:28,962 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:28,964 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00712767
2023-07-02 10:24:28,964 [model] Computed derived parameters: {}
2023-07-02 10:24:28,964 [mcmc] New sample, #185:
Omega_m:0.202549
2023-07-02 10:24:28,964 [model] Posterior to be computed for parameters {'Omega_m': -0.006710484738526312}
2023-07-02 10:24:28,964 [prior] Evaluating prior at array([-0.00671048])
2023-07-02 10:24:28,964 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:28,964 [model] Posterior to be computed for parameters {'Omega_m': 0.13218920182756003}
2023-07-02 10:24:28,964 [prior] Evaluating prior at array([0.1321892])
2023-07-02 10:24:28,964 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:28,964 [model] Got input parameters: {'Omega_m': 0.13218920182756003, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:28,965 [classy] Got parameters {'Omega_m': 0.13218920182756003, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:28,965 [classy] Computing new state
2023-07-02 10:24:28,965 [classy] Setting parameters: {'Omega_m': 0.13218920182756003, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:29,011 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 177.0682986296394}
2023-07-02 10:24:29,011 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:29,013 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.47004
2023-07-02 10:24:29,013 [model] Computed derived parameters: {}
2023-07-02 10:24:29,013 [mcmc] New sample, #186:
Omega_m:0.3019959
2023-07-02 10:24:29,014 [model] Posterior to be computed for parameters {'Omega_m': -0.2018324909461672}
2023-07-02 10:24:29,014 [prior] Evaluating prior at array([-0.20183249])
2023-07-02 10:24:29,014 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:29,014 [model] Posterior to be computed for parameters {'Omega_m': -0.152491160976961}
2023-07-02 10:24:29,014 [prior] Evaluating prior at array([-0.15249116])
2023-07-02 10:24:29,014 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:29,014 [model] Posterior to be computed for parameters {'Omega_m': 0.18610113894472463}
2023-07-02 10:24:29,014 [prior] Evaluating prior at array([0.18610114])
2023-07-02 10:24:29,014 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:29,014 [model] Got input parameters: {'Omega_m': 0.18610113894472463, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:29,014 [classy] Got parameters {'Omega_m': 0.18610113894472463, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:29,014 [classy] Computing new state
2023-07-02 10:24:29,014 [classy] Setting parameters: {'Omega_m': 0.18610113894472463, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:29,062 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 165.95816042121862}
2023-07-02 10:24:29,062 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:29,064 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.40578
2023-07-02 10:24:29,065 [model] Computed derived parameters: {}
2023-07-02 10:24:29,065 [mcmc] New sample, #187:
Omega_m:0.1321892
2023-07-02 10:24:29,065 [model] Posterior to be computed for parameters {'Omega_m': 0.6886665112664525}
2023-07-02 10:24:29,065 [prior] Evaluating prior at array([0.68866651])
2023-07-02 10:24:29,065 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:29,065 [model] Got input parameters: {'Omega_m': 0.6886665112664525, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:29,065 [classy] Got parameters {'Omega_m': 0.6886665112664525, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:29,065 [classy] Computing new state
2023-07-02 10:24:29,065 [classy] Setting parameters: {'Omega_m': 0.6886665112664525, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:29,109 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 117.01387886099977}
2023-07-02 10:24:29,109 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:29,111 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.27478
2023-07-02 10:24:29,111 [model] Computed derived parameters: {}
2023-07-02 10:24:29,111 [model] Posterior to be computed for parameters {'Omega_m': 0.25298577815102413}
2023-07-02 10:24:29,111 [prior] Evaluating prior at array([0.25298578])
2023-07-02 10:24:29,111 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:29,111 [model] Got input parameters: {'Omega_m': 0.25298577815102413, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:29,111 [classy] Got parameters {'Omega_m': 0.25298577815102413, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:29,112 [classy] Computing new state
2023-07-02 10:24:29,112 [classy] Setting parameters: {'Omega_m': 0.25298577815102413, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:29,158 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 155.09239383345}
2023-07-02 10:24:29,158 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:29,160 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.254256
2023-07-02 10:24:29,160 [model] Computed derived parameters: {}
2023-07-02 10:24:29,160 [mcmc] New sample, #188:
Omega_m:0.1861011
2023-07-02 10:24:29,160 [model] Posterior to be computed for parameters {'Omega_m': 0.3043960178728972}
2023-07-02 10:24:29,160 [prior] Evaluating prior at array([0.30439602])
2023-07-02 10:24:29,160 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:29,160 [model] Got input parameters: {'Omega_m': 0.3043960178728972, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:29,160 [classy] Got parameters {'Omega_m': 0.3043960178728972, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:29,160 [classy] Computing new state
2023-07-02 10:24:29,160 [classy] Setting parameters: {'Omega_m': 0.3043960178728972, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:29,207 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.24465841576716}
2023-07-02 10:24:29,207 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:29,209 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00429598
2023-07-02 10:24:29,209 [model] Computed derived parameters: {}
2023-07-02 10:24:29,209 [mcmc] New sample, #189:
Omega_m:0.2529858
2023-07-02 10:24:29,209 [model] Posterior to be computed for parameters {'Omega_m': 0.13894279846467986}
2023-07-02 10:24:29,209 [prior] Evaluating prior at array([0.1389428])
2023-07-02 10:24:29,209 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:29,209 [model] Got input parameters: {'Omega_m': 0.13894279846467986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:29,209 [classy] Got parameters {'Omega_m': 0.13894279846467986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:29,209 [classy] Computing new state
2023-07-02 10:24:29,209 [classy] Setting parameters: {'Omega_m': 0.13894279846467986, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:29,256 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 175.52568368528713}
2023-07-02 10:24:29,256 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:29,258 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.13262
2023-07-02 10:24:29,258 [model] Computed derived parameters: {}
2023-07-02 10:24:29,258 [model] Posterior to be computed for parameters {'Omega_m': 0.27146184702395915}
2023-07-02 10:24:29,258 [prior] Evaluating prior at array([0.27146185])
2023-07-02 10:24:29,258 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:29,258 [model] Got input parameters: {'Omega_m': 0.27146184702395915, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:29,258 [classy] Got parameters {'Omega_m': 0.27146184702395915, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:29,258 [classy] Computing new state
2023-07-02 10:24:29,258 [classy] Setting parameters: {'Omega_m': 0.27146184702395915, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:29,305 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.50519655712574}
2023-07-02 10:24:29,305 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:29,307 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.11497
2023-07-02 10:24:29,307 [model] Computed derived parameters: {}
2023-07-02 10:24:29,307 [mcmc] New sample, #190:
Omega_m:0.304396
2023-07-02 10:24:29,307 [model] Posterior to be computed for parameters {'Omega_m': 0.483127237762323}
2023-07-02 10:24:29,307 [prior] Evaluating prior at array([0.48312724])
2023-07-02 10:24:29,307 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:29,307 [model] Got input parameters: {'Omega_m': 0.483127237762323, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:29,307 [classy] Got parameters {'Omega_m': 0.483127237762323, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:29,307 [classy] Computing new state
2023-07-02 10:24:29,307 [classy] Setting parameters: {'Omega_m': 0.483127237762323, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:29,353 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.60900267309165}
2023-07-02 10:24:29,354 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:29,356 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.23646
2023-07-02 10:24:29,356 [model] Computed derived parameters: {}
2023-07-02 10:24:29,356 [model] Posterior to be computed for parameters {'Omega_m': 0.3892638309317183}
2023-07-02 10:24:29,356 [prior] Evaluating prior at array([0.38926383])
2023-07-02 10:24:29,356 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:29,356 [model] Got input parameters: {'Omega_m': 0.3892638309317183, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:29,356 [classy] Got parameters {'Omega_m': 0.3892638309317183, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:29,357 [classy] Computing new state
2023-07-02 10:24:29,357 [classy] Setting parameters: {'Omega_m': 0.3892638309317183, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:29,402 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 138.91435668177454}
2023-07-02 10:24:29,402 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:29,405 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.302687
2023-07-02 10:24:29,405 [model] Computed derived parameters: {}
2023-07-02 10:24:29,405 [mcmc] New sample, #191:
Omega_m:0.2714618
2023-07-02 10:24:29,405 [model] Posterior to be computed for parameters {'Omega_m': 0.4831783281387563}
2023-07-02 10:24:29,405 [prior] Evaluating prior at array([0.48317833])
2023-07-02 10:24:29,406 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:29,406 [model] Got input parameters: {'Omega_m': 0.4831783281387563, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:29,406 [classy] Got parameters {'Omega_m': 0.4831783281387563, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:29,406 [classy] Computing new state
2023-07-02 10:24:29,406 [classy] Setting parameters: {'Omega_m': 0.4831783281387563, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:29,451 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.6049284726945}
2023-07-02 10:24:29,451 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:29,453 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.23708
2023-07-02 10:24:29,453 [model] Computed derived parameters: {}
2023-07-02 10:24:29,454 [mcmc] New sample, #192:
Omega_m:0.3892638
2023-07-02 10:24:29,454 [model] Posterior to be computed for parameters {'Omega_m': 0.6000221929121535}
2023-07-02 10:24:29,454 [prior] Evaluating prior at array([0.60002219])
2023-07-02 10:24:29,454 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:29,454 [model] Got input parameters: {'Omega_m': 0.6000221929121535, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:29,454 [classy] Got parameters {'Omega_m': 0.6000221929121535, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:29,454 [classy] Computing new state
2023-07-02 10:24:29,454 [classy] Setting parameters: {'Omega_m': 0.6000221929121535, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:29,500 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 122.2746838949577}
2023-07-02 10:24:29,500 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:29,502 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.8631
2023-07-02 10:24:29,502 [model] Computed derived parameters: {}
2023-07-02 10:24:29,502 [model] Posterior to be computed for parameters {'Omega_m': 0.754922288752434}
2023-07-02 10:24:29,502 [prior] Evaluating prior at array([0.75492229])
2023-07-02 10:24:29,502 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:29,502 [model] Got input parameters: {'Omega_m': 0.754922288752434, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:29,502 [classy] Got parameters {'Omega_m': 0.754922288752434, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:29,503 [classy] Computing new state
2023-07-02 10:24:29,503 [classy] Setting parameters: {'Omega_m': 0.754922288752434, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:29,548 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 113.53629530572549}
2023-07-02 10:24:29,548 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:29,550 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.38265
2023-07-02 10:24:29,550 [model] Computed derived parameters: {}
2023-07-02 10:24:29,550 [model] Posterior to be computed for parameters {'Omega_m': 0.724634429393231}
2023-07-02 10:24:29,550 [prior] Evaluating prior at array([0.72463443])
2023-07-02 10:24:29,551 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:29,551 [model] Got input parameters: {'Omega_m': 0.724634429393231, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:29,551 [classy] Got parameters {'Omega_m': 0.724634429393231, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:29,551 [classy] Computing new state
2023-07-02 10:24:29,551 [classy] Setting parameters: {'Omega_m': 0.724634429393231, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:29,596 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 115.0830850418334}
2023-07-02 10:24:29,596 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:29,598 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.87221
2023-07-02 10:24:29,598 [model] Computed derived parameters: {}
2023-07-02 10:24:29,598 [model] Posterior to be computed for parameters {'Omega_m': 0.4888087006092323}
2023-07-02 10:24:29,598 [prior] Evaluating prior at array([0.4888087])
2023-07-02 10:24:29,598 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:29,598 [model] Got input parameters: {'Omega_m': 0.4888087006092323, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:29,598 [classy] Got parameters {'Omega_m': 0.4888087006092323, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:29,598 [classy] Computing new state
2023-07-02 10:24:29,598 [classy] Setting parameters: {'Omega_m': 0.4888087006092323, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:29,645 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.15858372339014}
2023-07-02 10:24:29,645 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:29,647 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.30618
2023-07-02 10:24:29,647 [model] Computed derived parameters: {}
2023-07-02 10:24:29,647 [mcmc] New sample, #193:
Omega_m:0.4831783
2023-07-02 10:24:29,647 [model] Posterior to be computed for parameters {'Omega_m': 0.9127037765380227}
2023-07-02 10:24:29,647 [prior] Evaluating prior at array([0.91270378])
2023-07-02 10:24:29,648 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:29,648 [model] Got input parameters: {'Omega_m': 0.9127037765380227, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:29,648 [classy] Got parameters {'Omega_m': 0.9127037765380227, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:29,648 [classy] Computing new state
2023-07-02 10:24:29,648 [classy] Setting parameters: {'Omega_m': 0.9127037765380227, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:29,695 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 106.45290818306594}
2023-07-02 10:24:29,696 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:29,697 [bao_likelihood.baolikelihood] Computed log-likelihood = -8.09856
2023-07-02 10:24:29,697 [model] Computed derived parameters: {}
2023-07-02 10:24:29,698 [model] Posterior to be computed for parameters {'Omega_m': 0.3474968270023766}
2023-07-02 10:24:29,698 [prior] Evaluating prior at array([0.34749683])
2023-07-02 10:24:29,698 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:29,698 [model] Got input parameters: {'Omega_m': 0.3474968270023766, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:29,698 [classy] Got parameters {'Omega_m': 0.3474968270023766, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:29,698 [classy] Computing new state
2023-07-02 10:24:29,698 [classy] Setting parameters: {'Omega_m': 0.3474968270023766, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:29,745 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.2450117324434}
2023-07-02 10:24:29,745 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:29,747 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0692969
2023-07-02 10:24:29,747 [model] Computed derived parameters: {}
2023-07-02 10:24:29,747 [mcmc] New sample, #194:
Omega_m:0.4888087
2023-07-02 10:24:29,747 [model] Posterior to be computed for parameters {'Omega_m': 0.023597584485858025}
2023-07-02 10:24:29,747 [prior] Evaluating prior at array([0.02359758])
2023-07-02 10:24:29,747 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:29,748 [model] Posterior to be computed for parameters {'Omega_m': -0.019508109722111755}
2023-07-02 10:24:29,748 [prior] Evaluating prior at array([-0.01950811])
2023-07-02 10:24:29,748 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:29,748 [model] Posterior to be computed for parameters {'Omega_m': 0.15857228394240894}
2023-07-02 10:24:29,748 [prior] Evaluating prior at array([0.15857228])
2023-07-02 10:24:29,748 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:29,748 [model] Got input parameters: {'Omega_m': 0.15857228394240894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:29,748 [classy] Got parameters {'Omega_m': 0.15857228394240894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:29,748 [classy] Computing new state
2023-07-02 10:24:29,748 [classy] Setting parameters: {'Omega_m': 0.15857228394240894, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:29,794 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 171.3051964927806}
2023-07-02 10:24:29,794 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:29,796 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.29203
2023-07-02 10:24:29,796 [model] Computed derived parameters: {}
2023-07-02 10:24:29,796 [model] Posterior to be computed for parameters {'Omega_m': 0.473006373903228}
2023-07-02 10:24:29,796 [prior] Evaluating prior at array([0.47300637])
2023-07-02 10:24:29,796 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:29,796 [model] Got input parameters: {'Omega_m': 0.473006373903228, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:29,796 [classy] Got parameters {'Omega_m': 0.473006373903228, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:29,796 [classy] Computing new state
2023-07-02 10:24:29,796 [classy] Setting parameters: {'Omega_m': 0.473006373903228, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:29,842 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 131.42459421715336}
2023-07-02 10:24:29,842 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:29,844 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.11535
2023-07-02 10:24:29,844 [model] Computed derived parameters: {}
2023-07-02 10:24:29,844 [model] Posterior to be computed for parameters {'Omega_m': 0.34897290181681667}
2023-07-02 10:24:29,844 [prior] Evaluating prior at array([0.3489729])
2023-07-02 10:24:29,844 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:29,844 [model] Got input parameters: {'Omega_m': 0.34897290181681667, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:29,844 [classy] Got parameters {'Omega_m': 0.34897290181681667, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:29,844 [classy] Computing new state
2023-07-02 10:24:29,844 [classy] Setting parameters: {'Omega_m': 0.34897290181681667, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:29,891 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.0839421607422}
2023-07-02 10:24:29,891 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:29,893 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0749875
2023-07-02 10:24:29,893 [model] Computed derived parameters: {}
2023-07-02 10:24:29,893 [mcmc] New sample, #195:
Omega_m:0.3474968
2023-07-02 10:24:29,893 [model] Posterior to be computed for parameters {'Omega_m': 0.42868800916654143}
2023-07-02 10:24:29,893 [prior] Evaluating prior at array([0.42868801])
2023-07-02 10:24:29,893 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:29,893 [model] Got input parameters: {'Omega_m': 0.42868800916654143, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:29,893 [classy] Got parameters {'Omega_m': 0.42868800916654143, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:29,893 [classy] Computing new state
2023-07-02 10:24:29,893 [classy] Setting parameters: {'Omega_m': 0.42868800916654143, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:29,940 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 135.21169451725174}
2023-07-02 10:24:29,940 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:29,942 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.637958
2023-07-02 10:24:29,942 [model] Computed derived parameters: {}
2023-07-02 10:24:29,942 [model] Posterior to be computed for parameters {'Omega_m': 0.5977114820660548}
2023-07-02 10:24:29,942 [prior] Evaluating prior at array([0.59771148])
2023-07-02 10:24:29,942 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:29,943 [model] Got input parameters: {'Omega_m': 0.5977114820660548, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:29,943 [classy] Got parameters {'Omega_m': 0.5977114820660548, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:29,943 [classy] Computing new state
2023-07-02 10:24:29,943 [classy] Setting parameters: {'Omega_m': 0.5977114820660548, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:29,989 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 122.42260238598074}
2023-07-02 10:24:29,989 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:29,991 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.82785
2023-07-02 10:24:29,991 [model] Computed derived parameters: {}
2023-07-02 10:24:29,991 [model] Posterior to be computed for parameters {'Omega_m': 0.4149618726835698}
2023-07-02 10:24:29,991 [prior] Evaluating prior at array([0.41496187])
2023-07-02 10:24:29,991 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:29,991 [model] Got input parameters: {'Omega_m': 0.4149618726835698, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:29,991 [classy] Got parameters {'Omega_m': 0.4149618726835698, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:29,991 [classy] Computing new state
2023-07-02 10:24:29,991 [classy] Setting parameters: {'Omega_m': 0.4149618726835698, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:30,039 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 136.4623631975701}
2023-07-02 10:24:30,040 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:30,041 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.510412
2023-07-02 10:24:30,041 [model] Computed derived parameters: {}
2023-07-02 10:24:30,042 [mcmc] New sample, #196:
Omega_m:0.3489729
2023-07-02 10:24:30,042 [model] Posterior to be computed for parameters {'Omega_m': 0.10964605242509334}
2023-07-02 10:24:30,042 [prior] Evaluating prior at array([0.10964605])
2023-07-02 10:24:30,042 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:30,042 [model] Got input parameters: {'Omega_m': 0.10964605242509334, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:30,042 [classy] Got parameters {'Omega_m': 0.10964605242509334, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:30,042 [classy] Computing new state
2023-07-02 10:24:30,042 [classy] Setting parameters: {'Omega_m': 0.10964605242509334, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:30,088 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 182.60414861927933}
2023-07-02 10:24:30,088 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:30,090 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.80998
2023-07-02 10:24:30,090 [model] Computed derived parameters: {}
2023-07-02 10:24:30,090 [model] Posterior to be computed for parameters {'Omega_m': 0.31103396972410113}
2023-07-02 10:24:30,090 [prior] Evaluating prior at array([0.31103397])
2023-07-02 10:24:30,090 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:30,091 [model] Got input parameters: {'Omega_m': 0.31103396972410113, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:30,091 [classy] Got parameters {'Omega_m': 0.31103396972410113, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:30,091 [classy] Computing new state
2023-07-02 10:24:30,091 [classy] Setting parameters: {'Omega_m': 0.31103396972410113, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:30,138 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.43496799132515}
2023-07-02 10:24:30,138 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:30,140 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000331776
2023-07-02 10:24:30,140 [model] Computed derived parameters: {}
2023-07-02 10:24:30,140 [mcmc] New sample, #197:
Omega_m:0.4149619
2023-07-02 10:24:30,140 [model] Posterior to be computed for parameters {'Omega_m': 0.2764323159134341}
2023-07-02 10:24:30,140 [prior] Evaluating prior at array([0.27643232])
2023-07-02 10:24:30,140 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:30,140 [model] Got input parameters: {'Omega_m': 0.2764323159134341, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:30,140 [classy] Got parameters {'Omega_m': 0.2764323159134341, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:30,140 [classy] Computing new state
2023-07-02 10:24:30,140 [classy] Setting parameters: {'Omega_m': 0.2764323159134341, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:30,187 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.83462352972455}
2023-07-02 10:24:30,187 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:30,188 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0876677
2023-07-02 10:24:30,189 [model] Computed derived parameters: {}
2023-07-02 10:24:30,189 [mcmc] New sample, #198:
Omega_m:0.311034
2023-07-02 10:24:30,189 [model] Posterior to be computed for parameters {'Omega_m': 0.6009290252802659}
2023-07-02 10:24:30,189 [prior] Evaluating prior at array([0.60092903])
2023-07-02 10:24:30,189 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:30,189 [model] Got input parameters: {'Omega_m': 0.6009290252802659, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:30,189 [classy] Got parameters {'Omega_m': 0.6009290252802659, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:30,189 [classy] Computing new state
2023-07-02 10:24:30,189 [classy] Setting parameters: {'Omega_m': 0.6009290252802659, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:30,236 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 122.21679802378137}
2023-07-02 10:24:30,236 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:30,238 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.87696
2023-07-02 10:24:30,238 [model] Computed derived parameters: {}
2023-07-02 10:24:30,238 [model] Posterior to be computed for parameters {'Omega_m': 0.23330121042142024}
2023-07-02 10:24:30,238 [prior] Evaluating prior at array([0.23330121])
2023-07-02 10:24:30,238 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:30,238 [model] Got input parameters: {'Omega_m': 0.23330121042142024, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:30,239 [classy] Got parameters {'Omega_m': 0.23330121042142024, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:30,239 [classy] Computing new state
2023-07-02 10:24:30,239 [classy] Setting parameters: {'Omega_m': 0.23330121042142024, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:30,286 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 158.0268921630566}
2023-07-02 10:24:30,286 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:30,288 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.476385
2023-07-02 10:24:30,288 [model] Computed derived parameters: {}
2023-07-02 10:24:30,288 [mcmc] New sample, #199:
Omega_m:0.2764323
2023-07-02 10:24:30,288 [model] Posterior to be computed for parameters {'Omega_m': 0.2768722639101802}
2023-07-02 10:24:30,288 [prior] Evaluating prior at array([0.27687226])
2023-07-02 10:24:30,288 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:30,288 [model] Got input parameters: {'Omega_m': 0.2768722639101802, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:30,288 [classy] Got parameters {'Omega_m': 0.2768722639101802, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:30,288 [classy] Computing new state
2023-07-02 10:24:30,288 [classy] Setting parameters: {'Omega_m': 0.2768722639101802, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:30,336 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.77576384892626}
2023-07-02 10:24:30,336 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:30,338 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0854456
2023-07-02 10:24:30,338 [model] Computed derived parameters: {}
2023-07-02 10:24:30,338 [mcmc] New sample, #200:
Omega_m:0.2333012
2023-07-02 10:24:30,338 [mcmc] Learn + convergence test @ 200 samples accepted.
2023-07-02 10:24:30,338 [mcmc] Ready to check convergence and learn a new proposal covmat
2023-07-02 10:24:30,343 [mcmc] - Acceptance rate: 0.541
2023-07-02 10:24:30,343 [mcmc] - Condition number = 1
2023-07-02 10:24:30,343 [mcmc] - Eigenvalues = array([0.0890007])
2023-07-02 10:24:30,344 [mcmc] - Convergence of means: R-1 = 0.089001 after 160 accepted steps
2023-07-02 10:24:30,344 [mcmc] - Updated covariance matrix of proposal pdf.
2023-07-02 10:24:30,344 [mcmc] array([[0.01207759]])
2023-07-02 10:24:30,354 [mcmc] Dumped checkpoint and progress info, and current covmat.
2023-07-02 10:24:30,354 [model] Posterior to be computed for parameters {'Omega_m': 0.39977621242772454}
2023-07-02 10:24:30,354 [prior] Evaluating prior at array([0.39977621])
2023-07-02 10:24:30,354 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:30,354 [model] Got input parameters: {'Omega_m': 0.39977621242772454, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:30,354 [classy] Got parameters {'Omega_m': 0.39977621242772454, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:30,354 [classy] Computing new state
2023-07-02 10:24:30,354 [classy] Setting parameters: {'Omega_m': 0.39977621242772454, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:30,401 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 137.89320060193035}
2023-07-02 10:24:30,401 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:30,403 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.382442
2023-07-02 10:24:30,403 [model] Computed derived parameters: {}
2023-07-02 10:24:30,403 [model] Posterior to be computed for parameters {'Omega_m': 0.40945932246365413}
2023-07-02 10:24:30,403 [prior] Evaluating prior at array([0.40945932])
2023-07-02 10:24:30,403 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:30,403 [model] Got input parameters: {'Omega_m': 0.40945932246365413, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:30,404 [classy] Got parameters {'Omega_m': 0.40945932246365413, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:30,404 [classy] Computing new state
2023-07-02 10:24:30,404 [classy] Setting parameters: {'Omega_m': 0.40945932246365413, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:30,450 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 136.97493316651716}
2023-07-02 10:24:30,451 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:30,452 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.462382
2023-07-02 10:24:30,452 [model] Computed derived parameters: {}
2023-07-02 10:24:30,452 [mcmc] New sample, #201:
Omega_m:0.2768723
2023-07-02 10:24:30,453 [model] Posterior to be computed for parameters {'Omega_m': 0.4441384854211399}
2023-07-02 10:24:30,453 [prior] Evaluating prior at array([0.44413849])
2023-07-02 10:24:30,453 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:30,453 [model] Got input parameters: {'Omega_m': 0.4441384854211399, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:30,453 [classy] Got parameters {'Omega_m': 0.4441384854211399, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:30,453 [classy] Computing new state
2023-07-02 10:24:30,453 [classy] Setting parameters: {'Omega_m': 0.4441384854211399, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:30,499 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 133.84954734478455}
2023-07-02 10:24:30,500 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:30,501 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.793744
2023-07-02 10:24:30,501 [model] Computed derived parameters: {}
2023-07-02 10:24:30,501 [mcmc] New sample, #202:
Omega_m:0.4094593
2023-07-02 10:24:30,502 [model] Posterior to be computed for parameters {'Omega_m': 0.14298380621549012}
2023-07-02 10:24:30,502 [prior] Evaluating prior at array([0.14298381])
2023-07-02 10:24:30,502 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:30,502 [model] Got input parameters: {'Omega_m': 0.14298380621549012, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:30,502 [classy] Got parameters {'Omega_m': 0.14298380621549012, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:30,502 [classy] Computing new state
2023-07-02 10:24:30,502 [classy] Setting parameters: {'Omega_m': 0.14298380621549012, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:30,549 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 174.62579877364738}
2023-07-02 10:24:30,549 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:30,551 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.94319
2023-07-02 10:24:30,551 [model] Computed derived parameters: {}
2023-07-02 10:24:30,551 [model] Posterior to be computed for parameters {'Omega_m': 0.5780826341881788}
2023-07-02 10:24:30,551 [prior] Evaluating prior at array([0.57808263])
2023-07-02 10:24:30,551 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:30,551 [model] Got input parameters: {'Omega_m': 0.5780826341881788, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:30,551 [classy] Got parameters {'Omega_m': 0.5780826341881788, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:30,551 [classy] Computing new state
2023-07-02 10:24:30,551 [classy] Setting parameters: {'Omega_m': 0.5780826341881788, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:30,598 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 123.70371322695571}
2023-07-02 10:24:30,598 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:30,600 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.53242
2023-07-02 10:24:30,600 [model] Computed derived parameters: {}
2023-07-02 10:24:30,600 [model] Posterior to be computed for parameters {'Omega_m': 0.5877231945791805}
2023-07-02 10:24:30,600 [prior] Evaluating prior at array([0.58772319])
2023-07-02 10:24:30,601 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:30,601 [model] Got input parameters: {'Omega_m': 0.5877231945791805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:30,601 [classy] Got parameters {'Omega_m': 0.5877231945791805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:30,601 [classy] Computing new state
2023-07-02 10:24:30,601 [classy] Setting parameters: {'Omega_m': 0.5877231945791805, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:30,648 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 123.06891222441007}
2023-07-02 10:24:30,648 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:30,650 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.6766
2023-07-02 10:24:30,650 [model] Computed derived parameters: {}
2023-07-02 10:24:30,650 [model] Posterior to be computed for parameters {'Omega_m': 0.6088468355592735}
2023-07-02 10:24:30,650 [prior] Evaluating prior at array([0.60884684])
2023-07-02 10:24:30,650 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:30,650 [model] Got input parameters: {'Omega_m': 0.6088468355592735, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:30,650 [classy] Got parameters {'Omega_m': 0.6088468355592735, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:30,650 [classy] Computing new state
2023-07-02 10:24:30,650 [classy] Setting parameters: {'Omega_m': 0.6088468355592735, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:30,698 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 121.71523923051315}
2023-07-02 10:24:30,698 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:30,700 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.99859
2023-07-02 10:24:30,700 [model] Computed derived parameters: {}
2023-07-02 10:24:30,700 [model] Posterior to be computed for parameters {'Omega_m': 0.4496948047295908}
2023-07-02 10:24:30,700 [prior] Evaluating prior at array([0.4496948])
2023-07-02 10:24:30,700 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:30,700 [model] Got input parameters: {'Omega_m': 0.4496948047295908, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:30,700 [classy] Got parameters {'Omega_m': 0.4496948047295908, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:30,700 [classy] Computing new state
2023-07-02 10:24:30,700 [classy] Setting parameters: {'Omega_m': 0.4496948047295908, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:30,747 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 133.37098705090028}
2023-07-02 10:24:30,747 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:30,749 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.852693
2023-07-02 10:24:30,749 [model] Computed derived parameters: {}
2023-07-02 10:24:30,749 [mcmc] New sample, #203:
Omega_m:0.4441385
2023-07-02 10:24:30,749 [model] Posterior to be computed for parameters {'Omega_m': 0.7592819383855134}
2023-07-02 10:24:30,749 [prior] Evaluating prior at array([0.75928194])
2023-07-02 10:24:30,749 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:30,749 [model] Got input parameters: {'Omega_m': 0.7592819383855134, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:30,749 [classy] Got parameters {'Omega_m': 0.7592819383855134, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:30,749 [classy] Computing new state
2023-07-02 10:24:30,749 [classy] Setting parameters: {'Omega_m': 0.7592819383855134, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:30,796 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 113.3192500866383}
2023-07-02 10:24:30,796 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:30,798 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.45657
2023-07-02 10:24:30,798 [model] Computed derived parameters: {}
2023-07-02 10:24:30,798 [model] Posterior to be computed for parameters {'Omega_m': 0.5846212824845307}
2023-07-02 10:24:30,798 [prior] Evaluating prior at array([0.58462128])
2023-07-02 10:24:30,798 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:30,798 [model] Got input parameters: {'Omega_m': 0.5846212824845307, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:30,798 [classy] Got parameters {'Omega_m': 0.5846212824845307, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:30,798 [classy] Computing new state
2023-07-02 10:24:30,798 [classy] Setting parameters: {'Omega_m': 0.5846212824845307, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:30,845 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 123.27196649181626}
2023-07-02 10:24:30,845 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:30,847 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.63002
2023-07-02 10:24:30,847 [model] Computed derived parameters: {}
2023-07-02 10:24:30,847 [mcmc] New sample, #204:
Omega_m:0.4496948
2023-07-02 10:24:30,848 [model] Posterior to be computed for parameters {'Omega_m': 0.4125472726067002}
2023-07-02 10:24:30,848 [prior] Evaluating prior at array([0.41254727])
2023-07-02 10:24:30,848 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:30,848 [model] Got input parameters: {'Omega_m': 0.4125472726067002, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:30,848 [classy] Got parameters {'Omega_m': 0.4125472726067002, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:30,848 [classy] Computing new state
2023-07-02 10:24:30,848 [classy] Setting parameters: {'Omega_m': 0.4125472726067002, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:30,896 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 136.6864804978648}
2023-07-02 10:24:30,896 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:30,898 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.48911
2023-07-02 10:24:30,898 [model] Computed derived parameters: {}
2023-07-02 10:24:30,898 [mcmc] New sample, #205:
Omega_m:0.5846213
2023-07-02 10:24:30,898 [model] Posterior to be computed for parameters {'Omega_m': 0.4910212406897691}
2023-07-02 10:24:30,898 [prior] Evaluating prior at array([0.49102124])
2023-07-02 10:24:30,898 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:30,898 [model] Got input parameters: {'Omega_m': 0.4910212406897691, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:30,898 [classy] Got parameters {'Omega_m': 0.4910212406897691, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:30,898 [classy] Computing new state
2023-07-02 10:24:30,898 [classy] Setting parameters: {'Omega_m': 0.4910212406897691, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:30,947 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 129.9845895086321}
2023-07-02 10:24:30,947 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:30,948 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.33365
2023-07-02 10:24:30,949 [model] Computed derived parameters: {}
2023-07-02 10:24:30,949 [mcmc] New sample, #206:
Omega_m:0.4125473
2023-07-02 10:24:30,949 [model] Posterior to be computed for parameters {'Omega_m': 0.42290287760102485}
2023-07-02 10:24:30,949 [prior] Evaluating prior at array([0.42290288])
2023-07-02 10:24:30,949 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:30,949 [model] Got input parameters: {'Omega_m': 0.42290287760102485, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:30,949 [classy] Got parameters {'Omega_m': 0.42290287760102485, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:30,949 [classy] Computing new state
2023-07-02 10:24:30,949 [classy] Setting parameters: {'Omega_m': 0.42290287760102485, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:30,996 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 135.73400938536898}
2023-07-02 10:24:30,996 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:30,998 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.582902
2023-07-02 10:24:30,998 [model] Computed derived parameters: {}
2023-07-02 10:24:30,998 [mcmc] New sample, #207:
Omega_m:0.4910212
2023-07-02 10:24:30,998 [model] Posterior to be computed for parameters {'Omega_m': 1.0275799849851428}
2023-07-02 10:24:30,998 [prior] Evaluating prior at array([1.02757998])
2023-07-02 10:24:30,998 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:30,999 [model] Posterior to be computed for parameters {'Omega_m': 0.4741551942600836}
2023-07-02 10:24:30,999 [prior] Evaluating prior at array([0.47415519])
2023-07-02 10:24:30,999 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:30,999 [model] Got input parameters: {'Omega_m': 0.4741551942600836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:30,999 [classy] Got parameters {'Omega_m': 0.4741551942600836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:30,999 [classy] Computing new state
2023-07-02 10:24:30,999 [classy] Setting parameters: {'Omega_m': 0.4741551942600836, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:31,048 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 131.3311402707497}
2023-07-02 10:24:31,048 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:31,050 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.1289
2023-07-02 10:24:31,050 [model] Computed derived parameters: {}
2023-07-02 10:24:31,050 [mcmc] New sample, #208:
Omega_m:0.4229029
2023-07-02 10:24:31,050 [model] Posterior to be computed for parameters {'Omega_m': 0.25800103099466554}
2023-07-02 10:24:31,050 [prior] Evaluating prior at array([0.25800103])
2023-07-02 10:24:31,050 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:31,050 [model] Got input parameters: {'Omega_m': 0.25800103099466554, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:31,050 [classy] Got parameters {'Omega_m': 0.25800103099466554, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:31,050 [classy] Computing new state
2023-07-02 10:24:31,050 [classy] Setting parameters: {'Omega_m': 0.25800103099466554, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:31,097 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 154.37484695687075}
2023-07-02 10:24:31,097 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:31,099 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.21026
2023-07-02 10:24:31,099 [model] Computed derived parameters: {}
2023-07-02 10:24:31,100 [mcmc] New sample, #209:
Omega_m:0.4741552
2023-07-02 10:24:31,100 [model] Posterior to be computed for parameters {'Omega_m': 0.09595403832211036}
2023-07-02 10:24:31,100 [prior] Evaluating prior at array([0.09595404])
2023-07-02 10:24:31,100 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:31,100 [model] Posterior to be computed for parameters {'Omega_m': 0.4288716374893335}
2023-07-02 10:24:31,100 [prior] Evaluating prior at array([0.42887164])
2023-07-02 10:24:31,100 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:31,100 [model] Got input parameters: {'Omega_m': 0.4288716374893335, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:31,100 [classy] Got parameters {'Omega_m': 0.4288716374893335, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:31,100 [classy] Computing new state
2023-07-02 10:24:31,100 [classy] Setting parameters: {'Omega_m': 0.4288716374893335, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:31,147 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 135.19522580392893}
2023-07-02 10:24:31,147 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:31,149 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.639736
2023-07-02 10:24:31,149 [model] Computed derived parameters: {}
2023-07-02 10:24:31,149 [mcmc] New sample, #210:
Omega_m:0.258001
2023-07-02 10:24:31,150 [model] Posterior to be computed for parameters {'Omega_m': 0.6144137273158524}
2023-07-02 10:24:31,150 [prior] Evaluating prior at array([0.61441373])
2023-07-02 10:24:31,150 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:31,150 [model] Got input parameters: {'Omega_m': 0.6144137273158524, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:31,150 [classy] Got parameters {'Omega_m': 0.6144137273158524, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:31,150 [classy] Computing new state
2023-07-02 10:24:31,150 [classy] Setting parameters: {'Omega_m': 0.6144137273158524, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:31,199 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 121.36669930040973}
2023-07-02 10:24:31,199 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:31,201 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.08473
2023-07-02 10:24:31,201 [model] Computed derived parameters: {}
2023-07-02 10:24:31,201 [model] Posterior to be computed for parameters {'Omega_m': 0.6372338092097729}
2023-07-02 10:24:31,201 [prior] Evaluating prior at array([0.63723381])
2023-07-02 10:24:31,201 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:31,201 [model] Got input parameters: {'Omega_m': 0.6372338092097729, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:31,201 [classy] Got parameters {'Omega_m': 0.6372338092097729, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:31,201 [classy] Computing new state
2023-07-02 10:24:31,201 [classy] Setting parameters: {'Omega_m': 0.6372338092097729, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:31,247 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 119.97190396094658}
2023-07-02 10:24:31,247 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:31,248 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.44287
2023-07-02 10:24:31,248 [model] Computed derived parameters: {}
2023-07-02 10:24:31,249 [model] Posterior to be computed for parameters {'Omega_m': 0.7474858842956685}
2023-07-02 10:24:31,249 [prior] Evaluating prior at array([0.74748588])
2023-07-02 10:24:31,249 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:31,249 [model] Got input parameters: {'Omega_m': 0.7474858842956685, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:31,249 [classy] Got parameters {'Omega_m': 0.7474858842956685, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:31,249 [classy] Computing new state
2023-07-02 10:24:31,249 [classy] Setting parameters: {'Omega_m': 0.7474858842956685, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:31,295 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 113.90970047286305}
2023-07-02 10:24:31,295 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:31,297 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.25681
2023-07-02 10:24:31,297 [model] Computed derived parameters: {}
2023-07-02 10:24:31,297 [model] Posterior to be computed for parameters {'Omega_m': 0.025480139707055982}
2023-07-02 10:24:31,297 [prior] Evaluating prior at array([0.02548014])
2023-07-02 10:24:31,297 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:31,298 [model] Posterior to be computed for parameters {'Omega_m': 0.17670400208050535}
2023-07-02 10:24:31,298 [prior] Evaluating prior at array([0.176704])
2023-07-02 10:24:31,298 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:31,298 [model] Got input parameters: {'Omega_m': 0.17670400208050535, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:31,298 [classy] Got parameters {'Omega_m': 0.17670400208050535, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:31,298 [classy] Computing new state
2023-07-02 10:24:31,298 [classy] Setting parameters: {'Omega_m': 0.17670400208050535, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:31,345 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 167.71543062241756}
2023-07-02 10:24:31,345 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:31,347 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.67455
2023-07-02 10:24:31,347 [model] Computed derived parameters: {}
2023-07-02 10:24:31,347 [model] Posterior to be computed for parameters {'Omega_m': 0.7410241377155051}
2023-07-02 10:24:31,347 [prior] Evaluating prior at array([0.74102414])
2023-07-02 10:24:31,347 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:31,347 [model] Got input parameters: {'Omega_m': 0.7410241377155051, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:31,347 [classy] Got parameters {'Omega_m': 0.7410241377155051, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:31,347 [classy] Computing new state
2023-07-02 10:24:31,347 [classy] Setting parameters: {'Omega_m': 0.7410241377155051, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:31,392 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 114.23750355048745}
2023-07-02 10:24:31,393 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:31,394 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.1477
2023-07-02 10:24:31,394 [model] Computed derived parameters: {}
2023-07-02 10:24:31,394 [model] Posterior to be computed for parameters {'Omega_m': 0.40250901173834935}
2023-07-02 10:24:31,394 [prior] Evaluating prior at array([0.40250901])
2023-07-02 10:24:31,395 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:31,395 [model] Got input parameters: {'Omega_m': 0.40250901173834935, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:31,395 [classy] Got parameters {'Omega_m': 0.40250901173834935, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:31,395 [classy] Computing new state
2023-07-02 10:24:31,395 [classy] Setting parameters: {'Omega_m': 0.40250901173834935, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:31,441 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 137.63191361364528}
2023-07-02 10:24:31,441 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:31,443 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.404393
2023-07-02 10:24:31,443 [model] Computed derived parameters: {}
2023-07-02 10:24:31,443 [mcmc] New sample, #211:
Omega_m:0.4288716
2023-07-02 10:24:31,443 [model] Posterior to be computed for parameters {'Omega_m': 0.22511625774384023}
2023-07-02 10:24:31,443 [prior] Evaluating prior at array([0.22511626])
2023-07-02 10:24:31,444 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:31,444 [model] Got input parameters: {'Omega_m': 0.22511625774384023, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:31,444 [classy] Got parameters {'Omega_m': 0.22511625774384023, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:31,444 [classy] Computing new state
2023-07-02 10:24:31,444 [classy] Setting parameters: {'Omega_m': 0.22511625774384023, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:31,490 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 159.30642796073212}
2023-07-02 10:24:31,490 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:31,492 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.594197
2023-07-02 10:24:31,492 [model] Computed derived parameters: {}
2023-07-02 10:24:31,492 [mcmc] New sample, #212:
Omega_m:0.402509
2023-07-02 10:24:31,492 [model] Posterior to be computed for parameters {'Omega_m': 0.6222113997661323}
2023-07-02 10:24:31,492 [prior] Evaluating prior at array([0.6222114])
2023-07-02 10:24:31,492 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:31,492 [model] Got input parameters: {'Omega_m': 0.6222113997661323, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:31,492 [classy] Got parameters {'Omega_m': 0.6222113997661323, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:31,492 [classy] Computing new state
2023-07-02 10:24:31,492 [classy] Setting parameters: {'Omega_m': 0.6222113997661323, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:31,539 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 120.88401794168351}
2023-07-02 10:24:31,539 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:31,540 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.20623
2023-07-02 10:24:31,541 [model] Computed derived parameters: {}
2023-07-02 10:24:31,541 [model] Posterior to be computed for parameters {'Omega_m': 0.3525670562097206}
2023-07-02 10:24:31,541 [prior] Evaluating prior at array([0.35256706])
2023-07-02 10:24:31,541 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:31,541 [model] Got input parameters: {'Omega_m': 0.3525670562097206, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:31,541 [classy] Got parameters {'Omega_m': 0.3525670562097206, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:31,541 [classy] Computing new state
2023-07-02 10:24:31,541 [classy] Setting parameters: {'Omega_m': 0.3525670562097206, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:31,588 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.69433305990663}
2023-07-02 10:24:31,588 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:31,590 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0896969
2023-07-02 10:24:31,590 [model] Computed derived parameters: {}
2023-07-02 10:24:31,590 [mcmc] New sample, #213:
Omega_m:0.2251163
2023-07-02 10:24:31,590 [model] Posterior to be computed for parameters {'Omega_m': 0.06835437233581043}
2023-07-02 10:24:31,590 [prior] Evaluating prior at array([0.06835437])
2023-07-02 10:24:31,590 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:31,590 [model] Posterior to be computed for parameters {'Omega_m': 0.46154693755984616}
2023-07-02 10:24:31,590 [prior] Evaluating prior at array([0.46154694])
2023-07-02 10:24:31,590 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:31,590 [model] Got input parameters: {'Omega_m': 0.46154693755984616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:31,590 [classy] Got parameters {'Omega_m': 0.46154693755984616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:31,590 [classy] Computing new state
2023-07-02 10:24:31,590 [classy] Setting parameters: {'Omega_m': 0.46154693755984616, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:31,637 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 132.3692622688547}
2023-07-02 10:24:31,637 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:31,638 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.983261
2023-07-02 10:24:31,639 [model] Computed derived parameters: {}
2023-07-02 10:24:31,639 [mcmc] New sample, #214:
Omega_m:0.3525671
2023-07-02 10:24:31,639 [model] Posterior to be computed for parameters {'Omega_m': 0.5015665817715478}
2023-07-02 10:24:31,639 [prior] Evaluating prior at array([0.50156658])
2023-07-02 10:24:31,639 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:31,639 [model] Got input parameters: {'Omega_m': 0.5015665817715478, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:31,639 [classy] Got parameters {'Omega_m': 0.5015665817715478, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:31,639 [classy] Computing new state
2023-07-02 10:24:31,639 [classy] Setting parameters: {'Omega_m': 0.5015665817715478, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:31,687 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 129.1660120798404}
2023-07-02 10:24:31,687 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:31,688 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.46696
2023-07-02 10:24:31,688 [model] Computed derived parameters: {}
2023-07-02 10:24:31,688 [model] Posterior to be computed for parameters {'Omega_m': 0.06170264801410158}
2023-07-02 10:24:31,689 [prior] Evaluating prior at array([0.06170265])
2023-07-02 10:24:31,689 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:31,689 [model] Posterior to be computed for parameters {'Omega_m': 0.1371097498100874}
2023-07-02 10:24:31,689 [prior] Evaluating prior at array([0.13710975])
2023-07-02 10:24:31,689 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:31,689 [model] Got input parameters: {'Omega_m': 0.1371097498100874, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:31,689 [classy] Got parameters {'Omega_m': 0.1371097498100874, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:31,689 [classy] Computing new state
2023-07-02 10:24:31,689 [classy] Setting parameters: {'Omega_m': 0.1371097498100874, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:31,734 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 175.93953038852771}
2023-07-02 10:24:31,735 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:31,737 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.22158
2023-07-02 10:24:31,737 [model] Computed derived parameters: {}
2023-07-02 10:24:31,737 [mcmc] New sample, #215:
Omega_m:0.4615469
2023-07-02 10:24:31,737 [model] Posterior to be computed for parameters {'Omega_m': 0.11477095070434704}
2023-07-02 10:24:31,737 [prior] Evaluating prior at array([0.11477095])
2023-07-02 10:24:31,737 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:31,737 [model] Got input parameters: {'Omega_m': 0.11477095070434704, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:31,737 [classy] Got parameters {'Omega_m': 0.11477095070434704, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:31,737 [classy] Computing new state
2023-07-02 10:24:31,737 [classy] Setting parameters: {'Omega_m': 0.11477095070434704, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:31,782 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 181.28947726684834}
2023-07-02 10:24:31,782 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:31,784 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.47376
2023-07-02 10:24:31,784 [model] Computed derived parameters: {}
2023-07-02 10:24:31,784 [mcmc] New sample, #216:
Omega_m:0.1371097
2023-07-02 10:24:31,785 [model] Posterior to be computed for parameters {'Omega_m': 0.056568275142955066}
2023-07-02 10:24:31,785 [prior] Evaluating prior at array([0.05656828])
2023-07-02 10:24:31,785 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:31,785 [model] Posterior to be computed for parameters {'Omega_m': 0.19699181886933703}
2023-07-02 10:24:31,785 [prior] Evaluating prior at array([0.19699182])
2023-07-02 10:24:31,785 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:31,785 [model] Got input parameters: {'Omega_m': 0.19699181886933703, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:31,785 [classy] Got parameters {'Omega_m': 0.19699181886933703, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:31,785 [classy] Computing new state
2023-07-02 10:24:31,785 [classy] Setting parameters: {'Omega_m': 0.19699181886933703, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:31,830 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 164.0018385280909}
2023-07-02 10:24:31,830 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:31,832 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.13296
2023-07-02 10:24:31,832 [model] Computed derived parameters: {}
2023-07-02 10:24:31,832 [mcmc] New sample, #217:
Omega_m:0.114771
2023-07-02 10:24:31,833 [model] Posterior to be computed for parameters {'Omega_m': -0.128973361162794}
2023-07-02 10:24:31,833 [prior] Evaluating prior at array([-0.12897336])
2023-07-02 10:24:31,833 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:31,833 [model] Posterior to be computed for parameters {'Omega_m': 0.3149837179339865}
2023-07-02 10:24:31,833 [prior] Evaluating prior at array([0.31498372])
2023-07-02 10:24:31,833 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:31,833 [model] Got input parameters: {'Omega_m': 0.3149837179339865, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:31,833 [classy] Got parameters {'Omega_m': 0.3149837179339865, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:31,833 [classy] Computing new state
2023-07-02 10:24:31,833 [classy] Setting parameters: {'Omega_m': 0.3149837179339865, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:31,879 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.96038851820035}
2023-07-02 10:24:31,879 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:31,881 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000583307
2023-07-02 10:24:31,881 [model] Computed derived parameters: {}
2023-07-02 10:24:31,882 [mcmc] New sample, #218:
Omega_m:0.1969918
2023-07-02 10:24:31,882 [model] Posterior to be computed for parameters {'Omega_m': 0.7898587727972055}
2023-07-02 10:24:31,882 [prior] Evaluating prior at array([0.78985877])
2023-07-02 10:24:31,882 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:31,882 [model] Got input parameters: {'Omega_m': 0.7898587727972055, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:31,882 [classy] Got parameters {'Omega_m': 0.7898587727972055, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:31,882 [classy] Computing new state
2023-07-02 10:24:31,882 [classy] Setting parameters: {'Omega_m': 0.7898587727972055, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:31,927 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 111.83440036181766}
2023-07-02 10:24:31,927 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:31,929 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.97771
2023-07-02 10:24:31,929 [model] Computed derived parameters: {}
2023-07-02 10:24:31,929 [model] Posterior to be computed for parameters {'Omega_m': -0.011094309867537677}
2023-07-02 10:24:31,929 [prior] Evaluating prior at array([-0.01109431])
2023-07-02 10:24:31,929 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:31,929 [model] Posterior to be computed for parameters {'Omega_m': 0.6330035361536757}
2023-07-02 10:24:31,929 [prior] Evaluating prior at array([0.63300354])
2023-07-02 10:24:31,929 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:31,929 [model] Got input parameters: {'Omega_m': 0.6330035361536757, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:31,929 [classy] Got parameters {'Omega_m': 0.6330035361536757, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:31,929 [classy] Computing new state
2023-07-02 10:24:31,929 [classy] Setting parameters: {'Omega_m': 0.6330035361536757, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:31,974 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 120.22643530201442}
2023-07-02 10:24:31,974 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:31,976 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.3759
2023-07-02 10:24:31,976 [model] Computed derived parameters: {}
2023-07-02 10:24:31,976 [model] Posterior to be computed for parameters {'Omega_m': 0.3790015944150532}
2023-07-02 10:24:31,976 [prior] Evaluating prior at array([0.37900159])
2023-07-02 10:24:31,977 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:31,977 [model] Got input parameters: {'Omega_m': 0.3790015944150532, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:31,977 [classy] Got parameters {'Omega_m': 0.3790015944150532, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:31,977 [classy] Computing new state
2023-07-02 10:24:31,977 [classy] Setting parameters: {'Omega_m': 0.3790015944150532, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:32,025 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 139.93669904033018}
2023-07-02 10:24:32,025 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:32,027 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.232387
2023-07-02 10:24:32,027 [model] Computed derived parameters: {}
2023-07-02 10:24:32,028 [mcmc] New sample, #219:
Omega_m:0.3149837
2023-07-02 10:24:32,028 [model] Posterior to be computed for parameters {'Omega_m': -0.05493501885983937}
2023-07-02 10:24:32,028 [prior] Evaluating prior at array([-0.05493502])
2023-07-02 10:24:32,028 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:32,028 [model] Posterior to be computed for parameters {'Omega_m': 0.014414403899369821}
2023-07-02 10:24:32,028 [prior] Evaluating prior at array([0.0144144])
2023-07-02 10:24:32,028 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:32,028 [model] Posterior to be computed for parameters {'Omega_m': 0.37444104820366886}
2023-07-02 10:24:32,028 [prior] Evaluating prior at array([0.37444105])
2023-07-02 10:24:32,029 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:32,029 [model] Got input parameters: {'Omega_m': 0.37444104820366886, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:32,029 [classy] Got parameters {'Omega_m': 0.37444104820366886, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:32,029 [classy] Computing new state
2023-07-02 10:24:32,029 [classy] Setting parameters: {'Omega_m': 0.37444104820366886, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:32,077 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.3993849707718}
2023-07-02 10:24:32,077 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:32,079 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.203688
2023-07-02 10:24:32,079 [model] Computed derived parameters: {}
2023-07-02 10:24:32,079 [mcmc] New sample, #220:
Omega_m:0.3790016
2023-07-02 10:24:32,079 [model] Posterior to be computed for parameters {'Omega_m': 0.35445990696561325}
2023-07-02 10:24:32,079 [prior] Evaluating prior at array([0.35445991])
2023-07-02 10:24:32,079 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:32,079 [model] Got input parameters: {'Omega_m': 0.35445990696561325, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:32,079 [classy] Got parameters {'Omega_m': 0.35445990696561325, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:32,079 [classy] Computing new state
2023-07-02 10:24:32,079 [classy] Setting parameters: {'Omega_m': 0.35445990696561325, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:32,126 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.49060846888224}
2023-07-02 10:24:32,126 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:32,128 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0979216
2023-07-02 10:24:32,128 [model] Computed derived parameters: {}
2023-07-02 10:24:32,128 [mcmc] New sample, #221:
Omega_m:0.374441
2023-07-02 10:24:32,128 [model] Posterior to be computed for parameters {'Omega_m': 0.010407866457893045}
2023-07-02 10:24:32,128 [prior] Evaluating prior at array([0.01040787])
2023-07-02 10:24:32,128 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:32,128 [model] Posterior to be computed for parameters {'Omega_m': 0.4372127213425229}
2023-07-02 10:24:32,128 [prior] Evaluating prior at array([0.43721272])
2023-07-02 10:24:32,129 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:32,129 [model] Got input parameters: {'Omega_m': 0.4372127213425229, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:32,129 [classy] Got parameters {'Omega_m': 0.4372127213425229, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:32,129 [classy] Computing new state
2023-07-02 10:24:32,129 [classy] Setting parameters: {'Omega_m': 0.4372127213425229, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:32,176 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 134.4543351311791}
2023-07-02 10:24:32,177 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:32,179 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.72239
2023-07-02 10:24:32,179 [model] Computed derived parameters: {}
2023-07-02 10:24:32,179 [model] Posterior to be computed for parameters {'Omega_m': -0.028788031729014063}
2023-07-02 10:24:32,179 [prior] Evaluating prior at array([-0.02878803])
2023-07-02 10:24:32,179 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:32,179 [model] Posterior to be computed for parameters {'Omega_m': 0.13942951698460262}
2023-07-02 10:24:32,179 [prior] Evaluating prior at array([0.13942952])
2023-07-02 10:24:32,179 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:32,179 [model] Got input parameters: {'Omega_m': 0.13942951698460262, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:32,179 [classy] Got parameters {'Omega_m': 0.13942951698460262, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:32,179 [classy] Computing new state
2023-07-02 10:24:32,179 [classy] Setting parameters: {'Omega_m': 0.13942951698460262, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:32,226 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 175.41639018254972}
2023-07-02 10:24:32,226 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:32,228 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.10932
2023-07-02 10:24:32,228 [model] Computed derived parameters: {}
2023-07-02 10:24:32,229 [model] Posterior to be computed for parameters {'Omega_m': 1.1306563201067692}
2023-07-02 10:24:32,229 [prior] Evaluating prior at array([1.13065632])
2023-07-02 10:24:32,229 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:32,229 [model] Posterior to be computed for parameters {'Omega_m': 0.5987534654370779}
2023-07-02 10:24:32,229 [prior] Evaluating prior at array([0.59875347])
2023-07-02 10:24:32,229 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:32,229 [model] Got input parameters: {'Omega_m': 0.5987534654370779, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:32,229 [classy] Got parameters {'Omega_m': 0.5987534654370779, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:32,229 [classy] Computing new state
2023-07-02 10:24:32,229 [classy] Setting parameters: {'Omega_m': 0.5987534654370779, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:32,276 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 122.35582537489515}
2023-07-02 10:24:32,276 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:32,278 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.84373
2023-07-02 10:24:32,278 [model] Computed derived parameters: {}
2023-07-02 10:24:32,278 [model] Posterior to be computed for parameters {'Omega_m': 0.5729794005909123}
2023-07-02 10:24:32,279 [prior] Evaluating prior at array([0.5729794])
2023-07-02 10:24:32,279 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:32,279 [model] Got input parameters: {'Omega_m': 0.5729794005909123, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:32,279 [classy] Got parameters {'Omega_m': 0.5729794005909123, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:32,279 [classy] Computing new state
2023-07-02 10:24:32,279 [classy] Setting parameters: {'Omega_m': 0.5729794005909123, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:32,325 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 124.0442080950109}
2023-07-02 10:24:32,325 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:32,327 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.45687
2023-07-02 10:24:32,327 [model] Computed derived parameters: {}
2023-07-02 10:24:32,327 [model] Posterior to be computed for parameters {'Omega_m': 0.3275877786593559}
2023-07-02 10:24:32,327 [prior] Evaluating prior at array([0.32758778])
2023-07-02 10:24:32,327 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:32,327 [model] Got input parameters: {'Omega_m': 0.3275877786593559, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:32,327 [classy] Got parameters {'Omega_m': 0.3275877786593559, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:32,327 [classy] Computing new state
2023-07-02 10:24:32,328 [classy] Setting parameters: {'Omega_m': 0.3275877786593559, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:32,375 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.48075793743797}
2023-07-02 10:24:32,375 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:32,378 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0136823
2023-07-02 10:24:32,378 [model] Computed derived parameters: {}
2023-07-02 10:24:32,378 [mcmc] New sample, #222:
Omega_m:0.3544599
2023-07-02 10:24:32,378 [model] Posterior to be computed for parameters {'Omega_m': 0.5312377323801267}
2023-07-02 10:24:32,378 [prior] Evaluating prior at array([0.53123773])
2023-07-02 10:24:32,378 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:32,378 [model] Got input parameters: {'Omega_m': 0.5312377323801267, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:32,378 [classy] Got parameters {'Omega_m': 0.5312377323801267, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:32,378 [classy] Computing new state
2023-07-02 10:24:32,378 [classy] Setting parameters: {'Omega_m': 0.5312377323801267, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:32,425 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 126.95277388258557}
2023-07-02 10:24:32,425 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:32,427 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.8614
2023-07-02 10:24:32,427 [model] Computed derived parameters: {}
2023-07-02 10:24:32,427 [model] Posterior to be computed for parameters {'Omega_m': -0.08690170860879098}
2023-07-02 10:24:32,427 [prior] Evaluating prior at array([-0.08690171])
2023-07-02 10:24:32,428 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:32,428 [model] Posterior to be computed for parameters {'Omega_m': 0.8466787969089373}
2023-07-02 10:24:32,428 [prior] Evaluating prior at array([0.8466788])
2023-07-02 10:24:32,428 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:32,428 [model] Got input parameters: {'Omega_m': 0.8466787969089373, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:32,428 [classy] Got parameters {'Omega_m': 0.8466787969089373, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:32,428 [classy] Computing new state
2023-07-02 10:24:32,428 [classy] Setting parameters: {'Omega_m': 0.8466787969089373, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:32,474 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 109.23687875386601}
2023-07-02 10:24:32,474 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:32,476 [bao_likelihood.baolikelihood] Computed log-likelihood = -6.95515
2023-07-02 10:24:32,476 [model] Computed derived parameters: {}
2023-07-02 10:24:32,476 [model] Posterior to be computed for parameters {'Omega_m': 0.06326783462421692}
2023-07-02 10:24:32,476 [prior] Evaluating prior at array([0.06326783])
2023-07-02 10:24:32,476 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:32,476 [model] Posterior to be computed for parameters {'Omega_m': -0.07742049823993286}
2023-07-02 10:24:32,477 [prior] Evaluating prior at array([-0.0774205])
2023-07-02 10:24:32,477 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:32,477 [model] Posterior to be computed for parameters {'Omega_m': 0.2929580961679103}
2023-07-02 10:24:32,477 [prior] Evaluating prior at array([0.2929581])
2023-07-02 10:24:32,477 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:32,477 [model] Got input parameters: {'Omega_m': 0.2929580961679103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:32,477 [classy] Got parameters {'Omega_m': 0.2929580961679103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:32,477 [classy] Computing new state
2023-07-02 10:24:32,477 [classy] Setting parameters: {'Omega_m': 0.2929580961679103, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:32,524 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.67698059855854}
2023-07-02 10:24:32,524 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:32,526 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0247688
2023-07-02 10:24:32,526 [model] Computed derived parameters: {}
2023-07-02 10:24:32,526 [mcmc] New sample, #223:
Omega_m:0.3275878
2023-07-02 10:24:32,526 [model] Posterior to be computed for parameters {'Omega_m': 0.24900554767871463}
2023-07-02 10:24:32,526 [prior] Evaluating prior at array([0.24900555])
2023-07-02 10:24:32,526 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:32,526 [model] Got input parameters: {'Omega_m': 0.24900554767871463, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:32,526 [classy] Got parameters {'Omega_m': 0.24900554767871463, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:32,526 [classy] Computing new state
2023-07-02 10:24:32,526 [classy] Setting parameters: {'Omega_m': 0.24900554767871463, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:32,575 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 155.67026826376588}
2023-07-02 10:24:32,575 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:32,577 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.292654
2023-07-02 10:24:32,577 [model] Computed derived parameters: {}
2023-07-02 10:24:32,577 [mcmc] New sample, #224:
Omega_m:0.2929581
2023-07-02 10:24:32,577 [model] Posterior to be computed for parameters {'Omega_m': 0.12053604369995527}
2023-07-02 10:24:32,577 [prior] Evaluating prior at array([0.12053604])
2023-07-02 10:24:32,577 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:32,578 [model] Got input parameters: {'Omega_m': 0.12053604369995527, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:32,578 [classy] Got parameters {'Omega_m': 0.12053604369995527, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:32,578 [classy] Computing new state
2023-07-02 10:24:32,578 [classy] Setting parameters: {'Omega_m': 0.12053604369995527, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:32,625 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 179.85143618228784}
2023-07-02 10:24:32,625 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:32,627 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.11873
2023-07-02 10:24:32,627 [model] Computed derived parameters: {}
2023-07-02 10:24:32,627 [model] Posterior to be computed for parameters {'Omega_m': 0.35619731640537233}
2023-07-02 10:24:32,627 [prior] Evaluating prior at array([0.35619732])
2023-07-02 10:24:32,627 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:32,627 [model] Got input parameters: {'Omega_m': 0.35619731640537233, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:32,627 [classy] Got parameters {'Omega_m': 0.35619731640537233, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:32,627 [classy] Computing new state
2023-07-02 10:24:32,627 [classy] Setting parameters: {'Omega_m': 0.35619731640537233, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:32,674 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.30448975792928}
2023-07-02 10:24:32,674 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:32,676 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.105756
2023-07-02 10:24:32,676 [model] Computed derived parameters: {}
2023-07-02 10:24:32,676 [mcmc] New sample, #225:
Omega_m:0.2490055
2023-07-02 10:24:32,676 [model] Posterior to be computed for parameters {'Omega_m': -0.14203509696661865}
2023-07-02 10:24:32,676 [prior] Evaluating prior at array([-0.1420351])
2023-07-02 10:24:32,676 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:32,677 [model] Posterior to be computed for parameters {'Omega_m': 0.22272736046232783}
2023-07-02 10:24:32,677 [prior] Evaluating prior at array([0.22272736])
2023-07-02 10:24:32,677 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:32,677 [model] Got input parameters: {'Omega_m': 0.22272736046232783, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:32,677 [classy] Got parameters {'Omega_m': 0.22272736046232783, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:32,677 [classy] Computing new state
2023-07-02 10:24:32,677 [classy] Setting parameters: {'Omega_m': 0.22272736046232783, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:32,725 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 159.68684505707603}
2023-07-02 10:24:32,725 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:32,726 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.631646
2023-07-02 10:24:32,726 [model] Computed derived parameters: {}
2023-07-02 10:24:32,726 [mcmc] New sample, #226:
Omega_m:0.3561973
2023-07-02 10:24:32,727 [model] Posterior to be computed for parameters {'Omega_m': 0.2420100057978665}
2023-07-02 10:24:32,727 [prior] Evaluating prior at array([0.24201001])
2023-07-02 10:24:32,727 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:32,727 [model] Got input parameters: {'Omega_m': 0.2420100057978665, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:32,727 [classy] Got parameters {'Omega_m': 0.2420100057978665, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:32,727 [classy] Computing new state
2023-07-02 10:24:32,727 [classy] Setting parameters: {'Omega_m': 0.2420100057978665, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:32,775 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 156.70462966349186}
2023-07-02 10:24:32,775 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:32,777 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.367954
2023-07-02 10:24:32,777 [model] Computed derived parameters: {}
2023-07-02 10:24:32,778 [mcmc] New sample, #227:
Omega_m:0.2227274
2023-07-02 10:24:32,778 [model] Posterior to be computed for parameters {'Omega_m': -0.2880944412945442}
2023-07-02 10:24:32,778 [prior] Evaluating prior at array([-0.28809444])
2023-07-02 10:24:32,778 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:32,778 [model] Posterior to be computed for parameters {'Omega_m': 0.17376400957053717}
2023-07-02 10:24:32,778 [prior] Evaluating prior at array([0.17376401])
2023-07-02 10:24:32,778 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:32,778 [model] Got input parameters: {'Omega_m': 0.17376400957053717, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:32,778 [classy] Got parameters {'Omega_m': 0.17376400957053717, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:32,778 [classy] Computing new state
2023-07-02 10:24:32,778 [classy] Setting parameters: {'Omega_m': 0.17376400957053717, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:32,825 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 168.2791009955139}
2023-07-02 10:24:32,825 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:32,827 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.76546
2023-07-02 10:24:32,827 [model] Computed derived parameters: {}
2023-07-02 10:24:32,827 [model] Posterior to be computed for parameters {'Omega_m': 0.37607891751964456}
2023-07-02 10:24:32,827 [prior] Evaluating prior at array([0.37607892])
2023-07-02 10:24:32,828 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:32,828 [model] Got input parameters: {'Omega_m': 0.37607891751964456, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:32,828 [classy] Got parameters {'Omega_m': 0.37607891751964456, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:32,828 [classy] Computing new state
2023-07-02 10:24:32,828 [classy] Setting parameters: {'Omega_m': 0.37607891751964456, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:32,875 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.2326036317528}
2023-07-02 10:24:32,875 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:32,876 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.213811
2023-07-02 10:24:32,876 [model] Computed derived parameters: {}
2023-07-02 10:24:32,876 [mcmc] New sample, #228:
Omega_m:0.24201
2023-07-02 10:24:32,877 [model] Posterior to be computed for parameters {'Omega_m': 0.24173620959475497}
2023-07-02 10:24:32,877 [prior] Evaluating prior at array([0.24173621])
2023-07-02 10:24:32,877 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:32,877 [model] Got input parameters: {'Omega_m': 0.24173620959475497, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:32,877 [classy] Got parameters {'Omega_m': 0.24173620959475497, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:32,877 [classy] Computing new state
2023-07-02 10:24:32,877 [classy] Setting parameters: {'Omega_m': 0.24173620959475497, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:32,923 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 156.74560690621124}
2023-07-02 10:24:32,923 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:32,925 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.371109
2023-07-02 10:24:32,925 [model] Computed derived parameters: {}
2023-07-02 10:24:32,925 [mcmc] New sample, #229:
Omega_m:0.3760789
2023-07-02 10:24:32,925 [model] Posterior to be computed for parameters {'Omega_m': 0.4630671777635974}
2023-07-02 10:24:32,926 [prior] Evaluating prior at array([0.46306718])
2023-07-02 10:24:32,926 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:32,926 [model] Got input parameters: {'Omega_m': 0.4630671777635974, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:32,926 [classy] Got parameters {'Omega_m': 0.4630671777635974, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:32,926 [classy] Computing new state
2023-07-02 10:24:32,926 [classy] Setting parameters: {'Omega_m': 0.4630671777635974, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:32,974 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 132.24261779669033}
2023-07-02 10:24:32,974 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:32,976 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.00046
2023-07-02 10:24:32,976 [model] Computed derived parameters: {}
2023-07-02 10:24:32,976 [mcmc] New sample, #230:
Omega_m:0.2417362
2023-07-02 10:24:32,976 [model] Posterior to be computed for parameters {'Omega_m': -0.04617548613570244}
2023-07-02 10:24:32,976 [prior] Evaluating prior at array([-0.04617549])
2023-07-02 10:24:32,976 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:32,976 [model] Posterior to be computed for parameters {'Omega_m': 0.5084495329767831}
2023-07-02 10:24:32,976 [prior] Evaluating prior at array([0.50844953])
2023-07-02 10:24:32,976 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:32,976 [model] Got input parameters: {'Omega_m': 0.5084495329767831, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:32,976 [classy] Got parameters {'Omega_m': 0.5084495329767831, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:32,976 [classy] Computing new state
2023-07-02 10:24:32,976 [classy] Setting parameters: {'Omega_m': 0.5084495329767831, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:33,024 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 128.64099228377574}
2023-07-02 10:24:33,024 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:33,025 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.55602
2023-07-02 10:24:33,026 [model] Computed derived parameters: {}
2023-07-02 10:24:33,026 [model] Posterior to be computed for parameters {'Omega_m': 0.45372739983027693}
2023-07-02 10:24:33,026 [prior] Evaluating prior at array([0.4537274])
2023-07-02 10:24:33,026 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:33,026 [model] Got input parameters: {'Omega_m': 0.45372739983027693, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:33,026 [classy] Got parameters {'Omega_m': 0.45372739983027693, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:33,026 [classy] Computing new state
2023-07-02 10:24:33,026 [classy] Setting parameters: {'Omega_m': 0.45372739983027693, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:33,073 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 133.02726825839167}
2023-07-02 10:24:33,073 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:33,075 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.896399
2023-07-02 10:24:33,075 [model] Computed derived parameters: {}
2023-07-02 10:24:33,075 [mcmc] New sample, #231:
Omega_m:0.4630672
2023-07-02 10:24:33,075 [model] Posterior to be computed for parameters {'Omega_m': 0.13922503701932348}
2023-07-02 10:24:33,075 [prior] Evaluating prior at array([0.13922504])
2023-07-02 10:24:33,075 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:33,075 [model] Got input parameters: {'Omega_m': 0.13922503701932348, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:33,075 [classy] Got parameters {'Omega_m': 0.13922503701932348, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:33,075 [classy] Computing new state
2023-07-02 10:24:33,075 [classy] Setting parameters: {'Omega_m': 0.13922503701932348, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:33,121 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 175.46227642795697}
2023-07-02 10:24:33,122 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:33,123 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.1191
2023-07-02 10:24:33,123 [model] Computed derived parameters: {}
2023-07-02 10:24:33,123 [model] Posterior to be computed for parameters {'Omega_m': 0.6681493144498616}
2023-07-02 10:24:33,123 [prior] Evaluating prior at array([0.66814931])
2023-07-02 10:24:33,124 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:33,124 [model] Got input parameters: {'Omega_m': 0.6681493144498616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:33,124 [classy] Got parameters {'Omega_m': 0.6681493144498616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:33,124 [classy] Computing new state
2023-07-02 10:24:33,124 [classy] Setting parameters: {'Omega_m': 0.6681493144498616, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:33,170 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 118.16460068319117}
2023-07-02 10:24:33,170 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:33,172 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.93932
2023-07-02 10:24:33,172 [model] Computed derived parameters: {}
2023-07-02 10:24:33,172 [model] Posterior to be computed for parameters {'Omega_m': 0.30842019410662236}
2023-07-02 10:24:33,172 [prior] Evaluating prior at array([0.30842019])
2023-07-02 10:24:33,172 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:33,172 [model] Got input parameters: {'Omega_m': 0.30842019410662236, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:33,172 [classy] Got parameters {'Omega_m': 0.30842019410662236, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:33,172 [classy] Computing new state
2023-07-02 10:24:33,172 [classy] Setting parameters: {'Omega_m': 0.30842019410662236, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:33,219 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.75196195744363}
2023-07-02 10:24:33,219 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:33,221 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00122548
2023-07-02 10:24:33,221 [model] Computed derived parameters: {}
2023-07-02 10:24:33,221 [mcmc] New sample, #232:
Omega_m:0.4537274
2023-07-02 10:24:33,221 [model] Posterior to be computed for parameters {'Omega_m': 0.512447156396256}
2023-07-02 10:24:33,221 [prior] Evaluating prior at array([0.51244716])
2023-07-02 10:24:33,222 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:33,222 [model] Got input parameters: {'Omega_m': 0.512447156396256, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:33,222 [classy] Got parameters {'Omega_m': 0.512447156396256, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:33,222 [classy] Computing new state
2023-07-02 10:24:33,222 [classy] Setting parameters: {'Omega_m': 0.512447156396256, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:33,268 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 128.3393509652851}
2023-07-02 10:24:33,268 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:33,270 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.60844
2023-07-02 10:24:33,270 [model] Computed derived parameters: {}
2023-07-02 10:24:33,270 [model] Posterior to be computed for parameters {'Omega_m': 0.12771750202596754}
2023-07-02 10:24:33,270 [prior] Evaluating prior at array([0.1277175])
2023-07-02 10:24:33,270 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:33,270 [model] Got input parameters: {'Omega_m': 0.12771750202596754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:33,270 [classy] Got parameters {'Omega_m': 0.12771750202596754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:33,270 [classy] Computing new state
2023-07-02 10:24:33,270 [classy] Setting parameters: {'Omega_m': 0.12771750202596754, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:33,317 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 178.1175155376701}
2023-07-02 10:24:33,317 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:33,319 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.7086
2023-07-02 10:24:33,319 [model] Computed derived parameters: {}
2023-07-02 10:24:33,319 [model] Posterior to be computed for parameters {'Omega_m': 0.3192442160939121}
2023-07-02 10:24:33,319 [prior] Evaluating prior at array([0.31924422])
2023-07-02 10:24:33,319 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:33,319 [model] Got input parameters: {'Omega_m': 0.3192442160939121, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:33,319 [classy] Got parameters {'Omega_m': 0.3192442160939121, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:33,319 [classy] Computing new state
2023-07-02 10:24:33,319 [classy] Setting parameters: {'Omega_m': 0.3192442160939121, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:33,367 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.45442538004215}
2023-07-02 10:24:33,367 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:33,369 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00295811
2023-07-02 10:24:33,369 [model] Computed derived parameters: {}
2023-07-02 10:24:33,369 [mcmc] New sample, #233:
Omega_m:0.3084202
2023-07-02 10:24:33,369 [model] Posterior to be computed for parameters {'Omega_m': -0.013384066519635696}
2023-07-02 10:24:33,370 [prior] Evaluating prior at array([-0.01338407])
2023-07-02 10:24:33,370 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:33,370 [model] Posterior to be computed for parameters {'Omega_m': 0.14284616853265178}
2023-07-02 10:24:33,370 [prior] Evaluating prior at array([0.14284617])
2023-07-02 10:24:33,370 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:33,370 [model] Got input parameters: {'Omega_m': 0.14284616853265178, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:33,370 [classy] Got parameters {'Omega_m': 0.14284616853265178, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:33,370 [classy] Computing new state
2023-07-02 10:24:33,370 [classy] Setting parameters: {'Omega_m': 0.14284616853265178, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:33,417 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 174.6561708028375}
2023-07-02 10:24:33,417 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:33,419 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.94949
2023-07-02 10:24:33,419 [model] Computed derived parameters: {}
2023-07-02 10:24:33,419 [model] Posterior to be computed for parameters {'Omega_m': 0.4335893109601029}
2023-07-02 10:24:33,419 [prior] Evaluating prior at array([0.43358931])
2023-07-02 10:24:33,419 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:33,419 [model] Got input parameters: {'Omega_m': 0.4335893109601029, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:33,419 [classy] Got parameters {'Omega_m': 0.4335893109601029, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:33,419 [classy] Computing new state
2023-07-02 10:24:33,420 [classy] Setting parameters: {'Omega_m': 0.4335893109601029, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:33,467 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 134.77448732094166}
2023-07-02 10:24:33,467 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:33,469 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.686032
2023-07-02 10:24:33,469 [model] Computed derived parameters: {}
2023-07-02 10:24:33,469 [model] Posterior to be computed for parameters {'Omega_m': -0.1615018933220546}
2023-07-02 10:24:33,469 [prior] Evaluating prior at array([-0.16150189])
2023-07-02 10:24:33,469 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:33,470 [model] Posterior to be computed for parameters {'Omega_m': 0.2762744002800014}
2023-07-02 10:24:33,470 [prior] Evaluating prior at array([0.2762744])
2023-07-02 10:24:33,470 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:33,470 [model] Got input parameters: {'Omega_m': 0.2762744002800014, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:33,470 [classy] Got parameters {'Omega_m': 0.2762744002800014, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:33,470 [classy] Computing new state
2023-07-02 10:24:33,470 [classy] Setting parameters: {'Omega_m': 0.2762744002800014, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:33,517 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.85576884001404}
2023-07-02 10:24:33,517 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:33,519 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0884728
2023-07-02 10:24:33,519 [model] Computed derived parameters: {}
2023-07-02 10:24:33,519 [mcmc] New sample, #234:
Omega_m:0.3192442
2023-07-02 10:24:33,519 [model] Posterior to be computed for parameters {'Omega_m': 0.2716699759177384}
2023-07-02 10:24:33,519 [prior] Evaluating prior at array([0.27166998])
2023-07-02 10:24:33,519 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:33,519 [model] Got input parameters: {'Omega_m': 0.2716699759177384, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:33,519 [classy] Got parameters {'Omega_m': 0.2716699759177384, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:33,519 [classy] Computing new state
2023-07-02 10:24:33,519 [classy] Setting parameters: {'Omega_m': 0.2716699759177384, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:33,567 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.47690619816993}
2023-07-02 10:24:33,567 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:33,569 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.113744
2023-07-02 10:24:33,569 [model] Computed derived parameters: {}
2023-07-02 10:24:33,569 [mcmc] New sample, #235:
Omega_m:0.2762744
2023-07-02 10:24:33,569 [model] Posterior to be computed for parameters {'Omega_m': -0.11503300504359948}
2023-07-02 10:24:33,569 [prior] Evaluating prior at array([-0.11503301])
2023-07-02 10:24:33,569 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:33,569 [model] Posterior to be computed for parameters {'Omega_m': 0.40297137044710585}
2023-07-02 10:24:33,569 [prior] Evaluating prior at array([0.40297137])
2023-07-02 10:24:33,570 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:33,570 [model] Got input parameters: {'Omega_m': 0.40297137044710585, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:33,570 [classy] Got parameters {'Omega_m': 0.40297137044710585, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:33,570 [classy] Computing new state
2023-07-02 10:24:33,570 [classy] Setting parameters: {'Omega_m': 0.40297137044710585, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:33,617 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 137.5878734637502}
2023-07-02 10:24:33,617 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:33,619 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.408155
2023-07-02 10:24:33,619 [model] Computed derived parameters: {}
2023-07-02 10:24:33,619 [mcmc] New sample, #236:
Omega_m:0.27167
2023-07-02 10:24:33,619 [model] Posterior to be computed for parameters {'Omega_m': 0.28947475971423997}
2023-07-02 10:24:33,619 [prior] Evaluating prior at array([0.28947476])
2023-07-02 10:24:33,619 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:33,619 [model] Got input parameters: {'Omega_m': 0.28947475971423997, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:33,619 [classy] Got parameters {'Omega_m': 0.28947475971423997, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:33,619 [classy] Computing new state
2023-07-02 10:24:33,619 [classy] Setting parameters: {'Omega_m': 0.28947475971423997, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:33,667 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.12285891340065}
2023-07-02 10:24:33,667 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:33,669 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0346247
2023-07-02 10:24:33,669 [model] Computed derived parameters: {}
2023-07-02 10:24:33,669 [mcmc] New sample, #237:
Omega_m:0.4029714
2023-07-02 10:24:33,669 [model] Posterior to be computed for parameters {'Omega_m': 0.6520331057528294}
2023-07-02 10:24:33,669 [prior] Evaluating prior at array([0.65203311])
2023-07-02 10:24:33,670 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:33,670 [model] Got input parameters: {'Omega_m': 0.6520331057528294, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:33,670 [classy] Got parameters {'Omega_m': 0.6520331057528294, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:33,670 [classy] Computing new state
2023-07-02 10:24:33,670 [classy] Setting parameters: {'Omega_m': 0.6520331057528294, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:33,714 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 119.09535881837297}
2023-07-02 10:24:33,714 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:33,716 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.67904
2023-07-02 10:24:33,716 [model] Computed derived parameters: {}
2023-07-02 10:24:33,716 [model] Posterior to be computed for parameters {'Omega_m': -0.04800350756211064}
2023-07-02 10:24:33,716 [prior] Evaluating prior at array([-0.04800351])
2023-07-02 10:24:33,716 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:33,716 [model] Posterior to be computed for parameters {'Omega_m': -0.07608471914594006}
2023-07-02 10:24:33,716 [prior] Evaluating prior at array([-0.07608472])
2023-07-02 10:24:33,716 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:33,716 [model] Posterior to be computed for parameters {'Omega_m': 0.5545258838541829}
2023-07-02 10:24:33,716 [prior] Evaluating prior at array([0.55452588])
2023-07-02 10:24:33,716 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:33,716 [model] Got input parameters: {'Omega_m': 0.5545258838541829, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:33,716 [classy] Got parameters {'Omega_m': 0.5545258838541829, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:33,716 [classy] Computing new state
2023-07-02 10:24:33,716 [classy] Setting parameters: {'Omega_m': 0.5545258838541829, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:33,763 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 125.30221650635134}
2023-07-02 10:24:33,763 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:33,765 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.18842
2023-07-02 10:24:33,765 [model] Computed derived parameters: {}
2023-07-02 10:24:33,765 [model] Posterior to be computed for parameters {'Omega_m': 0.12204130112340264}
2023-07-02 10:24:33,765 [prior] Evaluating prior at array([0.1220413])
2023-07-02 10:24:33,765 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:33,765 [model] Got input parameters: {'Omega_m': 0.12204130112340264, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:33,765 [classy] Got parameters {'Omega_m': 0.12204130112340264, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:33,765 [classy] Computing new state
2023-07-02 10:24:33,766 [classy] Setting parameters: {'Omega_m': 0.12204130112340264, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:33,811 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 179.4828667381155}
2023-07-02 10:24:33,812 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:33,813 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.02991
2023-07-02 10:24:33,813 [model] Computed derived parameters: {}
2023-07-02 10:24:33,814 [model] Posterior to be computed for parameters {'Omega_m': 0.14359989896195383}
2023-07-02 10:24:33,814 [prior] Evaluating prior at array([0.1435999])
2023-07-02 10:24:33,814 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:33,814 [model] Got input parameters: {'Omega_m': 0.14359989896195383, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:33,814 [classy] Got parameters {'Omega_m': 0.14359989896195383, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:33,814 [classy] Computing new state
2023-07-02 10:24:33,814 [classy] Setting parameters: {'Omega_m': 0.14359989896195383, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:33,861 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 174.49007888323177}
2023-07-02 10:24:33,861 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:33,862 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.9151
2023-07-02 10:24:33,863 [model] Computed derived parameters: {}
2023-07-02 10:24:33,863 [model] Posterior to be computed for parameters {'Omega_m': 0.2024111535861598}
2023-07-02 10:24:33,863 [prior] Evaluating prior at array([0.20241115])
2023-07-02 10:24:33,863 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:33,863 [model] Got input parameters: {'Omega_m': 0.2024111535861598, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:33,863 [classy] Got parameters {'Omega_m': 0.2024111535861598, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:33,863 [classy] Computing new state
2023-07-02 10:24:33,863 [classy] Setting parameters: {'Omega_m': 0.2024111535861598, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:33,910 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 163.05858666769473}
2023-07-02 10:24:33,910 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:33,911 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.01148
2023-07-02 10:24:33,912 [model] Computed derived parameters: {}
2023-07-02 10:24:33,912 [model] Posterior to be computed for parameters {'Omega_m': -0.04804387944963395}
2023-07-02 10:24:33,912 [prior] Evaluating prior at array([-0.04804388])
2023-07-02 10:24:33,912 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:33,912 [model] Posterior to be computed for parameters {'Omega_m': -0.06866448485059123}
2023-07-02 10:24:33,912 [prior] Evaluating prior at array([-0.06866448])
2023-07-02 10:24:33,912 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:33,912 [model] Posterior to be computed for parameters {'Omega_m': 0.5931348943540837}
2023-07-02 10:24:33,912 [prior] Evaluating prior at array([0.59313489])
2023-07-02 10:24:33,912 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:33,912 [model] Got input parameters: {'Omega_m': 0.5931348943540837, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:33,912 [classy] Got parameters {'Omega_m': 0.5931348943540837, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:33,912 [classy] Computing new state
2023-07-02 10:24:33,912 [classy] Setting parameters: {'Omega_m': 0.5931348943540837, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:33,959 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 122.71733251908825}
2023-07-02 10:24:33,959 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:33,961 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.75831
2023-07-02 10:24:33,961 [model] Computed derived parameters: {}
2023-07-02 10:24:33,961 [model] Posterior to be computed for parameters {'Omega_m': 0.044430873028144496}
2023-07-02 10:24:33,961 [prior] Evaluating prior at array([0.04443087])
2023-07-02 10:24:33,961 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:33,962 [model] Posterior to be computed for parameters {'Omega_m': 0.05154808696009494}
2023-07-02 10:24:33,962 [prior] Evaluating prior at array([0.05154809])
2023-07-02 10:24:33,962 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:33,962 [model] Posterior to be computed for parameters {'Omega_m': 0.43554585558239867}
2023-07-02 10:24:33,962 [prior] Evaluating prior at array([0.43554586])
2023-07-02 10:24:33,962 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:33,962 [model] Got input parameters: {'Omega_m': 0.43554585558239867, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:33,962 [classy] Got parameters {'Omega_m': 0.43554585558239867, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:33,962 [classy] Computing new state
2023-07-02 10:24:33,962 [classy] Setting parameters: {'Omega_m': 0.43554585558239867, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:34,008 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 134.60129361113044}
2023-07-02 10:24:34,008 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:34,010 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.705579
2023-07-02 10:24:34,010 [model] Computed derived parameters: {}
2023-07-02 10:24:34,011 [model] Posterior to be computed for parameters {'Omega_m': -0.08653025345603838}
2023-07-02 10:24:34,011 [prior] Evaluating prior at array([-0.08653025])
2023-07-02 10:24:34,011 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:34,011 [model] Posterior to be computed for parameters {'Omega_m': 0.9883640264557586}
2023-07-02 10:24:34,011 [prior] Evaluating prior at array([0.98836403])
2023-07-02 10:24:34,011 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:34,011 [model] Got input parameters: {'Omega_m': 0.9883640264557586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:34,011 [classy] Got parameters {'Omega_m': 0.9883640264557586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:34,011 [classy] Computing new state
2023-07-02 10:24:34,011 [classy] Setting parameters: {'Omega_m': 0.9883640264557586, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:34,057 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 103.530176673115}
2023-07-02 10:24:34,057 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:34,059 [bao_likelihood.baolikelihood] Computed log-likelihood = -9.40968
2023-07-02 10:24:34,059 [model] Computed derived parameters: {}
2023-07-02 10:24:34,059 [model] Posterior to be computed for parameters {'Omega_m': 0.41415744512422503}
2023-07-02 10:24:34,059 [prior] Evaluating prior at array([0.41415745])
2023-07-02 10:24:34,060 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:34,060 [model] Got input parameters: {'Omega_m': 0.41415744512422503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:34,060 [classy] Got parameters {'Omega_m': 0.41415744512422503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:34,060 [classy] Computing new state
2023-07-02 10:24:34,060 [classy] Setting parameters: {'Omega_m': 0.41415744512422503, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:34,106 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 136.53688825656826}
2023-07-02 10:24:34,106 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:34,108 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.503277
2023-07-02 10:24:34,108 [model] Computed derived parameters: {}
2023-07-02 10:24:34,108 [mcmc] New sample, #238:
Omega_m:0.2894748
2023-07-02 10:24:34,108 [model] Posterior to be computed for parameters {'Omega_m': 0.17629057185848465}
2023-07-02 10:24:34,108 [prior] Evaluating prior at array([0.17629057])
2023-07-02 10:24:34,108 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:34,108 [model] Got input parameters: {'Omega_m': 0.17629057185848465, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:34,109 [classy] Got parameters {'Omega_m': 0.17629057185848465, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:34,109 [classy] Computing new state
2023-07-02 10:24:34,109 [classy] Setting parameters: {'Omega_m': 0.17629057185848465, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:34,154 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 167.7942864521538}
2023-07-02 10:24:34,154 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:34,155 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.68713
2023-07-02 10:24:34,155 [model] Computed derived parameters: {}
2023-07-02 10:24:34,156 [model] Posterior to be computed for parameters {'Omega_m': 0.51894130877109}
2023-07-02 10:24:34,156 [prior] Evaluating prior at array([0.51894131])
2023-07-02 10:24:34,156 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:34,156 [model] Got input parameters: {'Omega_m': 0.51894130877109, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:34,156 [classy] Got parameters {'Omega_m': 0.51894130877109, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:34,156 [classy] Computing new state
2023-07-02 10:24:34,156 [classy] Setting parameters: {'Omega_m': 0.51894130877109, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:34,203 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 127.85439837043637}
2023-07-02 10:24:34,203 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:34,204 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.69467
2023-07-02 10:24:34,204 [model] Computed derived parameters: {}
2023-07-02 10:24:34,205 [model] Posterior to be computed for parameters {'Omega_m': 0.30172682655491306}
2023-07-02 10:24:34,205 [prior] Evaluating prior at array([0.30172683])
2023-07-02 10:24:34,205 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:34,205 [model] Got input parameters: {'Omega_m': 0.30172682655491306, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:34,205 [classy] Got parameters {'Omega_m': 0.30172682655491306, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:34,205 [classy] Computing new state
2023-07-02 10:24:34,205 [classy] Setting parameters: {'Omega_m': 0.30172682655491306, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:34,252 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.57461921196614}
2023-07-02 10:24:34,252 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:34,253 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00749249
2023-07-02 10:24:34,253 [model] Computed derived parameters: {}
2023-07-02 10:24:34,254 [mcmc] New sample, #239:
Omega_m:0.4141574
2023-07-02 10:24:34,254 [model] Posterior to be computed for parameters {'Omega_m': -0.17205017840895137}
2023-07-02 10:24:34,254 [prior] Evaluating prior at array([-0.17205018])
2023-07-02 10:24:34,254 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:34,254 [model] Posterior to be computed for parameters {'Omega_m': 0.3632792186069551}
2023-07-02 10:24:34,254 [prior] Evaluating prior at array([0.36327922])
2023-07-02 10:24:34,254 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:34,254 [model] Got input parameters: {'Omega_m': 0.3632792186069551, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:34,254 [classy] Got parameters {'Omega_m': 0.3632792186069551, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:34,254 [classy] Computing new state
2023-07-02 10:24:34,254 [classy] Setting parameters: {'Omega_m': 0.3632792186069551, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:34,301 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.55443720530906}
2023-07-02 10:24:34,301 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:34,302 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.140444
2023-07-02 10:24:34,302 [model] Computed derived parameters: {}
2023-07-02 10:24:34,302 [mcmc] New sample, #240:
Omega_m:0.3017268
2023-07-02 10:24:34,303 [mcmc] Learn + convergence test @ 240 samples accepted.
2023-07-02 10:24:34,303 [mcmc] Ready to check convergence and learn a new proposal covmat
2023-07-02 10:24:34,307 [mcmc] - Acceptance rate: 0.482
2023-07-02 10:24:34,308 [mcmc] - Condition number = 1
2023-07-02 10:24:34,308 [mcmc] - Eigenvalues = array([0.0293129])
2023-07-02 10:24:34,308 [mcmc] - Convergence of means: R-1 = 0.029313 after 192 accepted steps
2023-07-02 10:24:34,308 [mcmc] - Updated covariance matrix of proposal pdf.
2023-07-02 10:24:34,308 [mcmc] array([[0.01056899]])
2023-07-02 10:24:34,318 [mcmc] Dumped checkpoint and progress info, and current covmat.
2023-07-02 10:24:34,319 [model] Posterior to be computed for parameters {'Omega_m': 0.31502564044316034}
2023-07-02 10:24:34,319 [prior] Evaluating prior at array([0.31502564])
2023-07-02 10:24:34,319 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:34,320 [model] Got input parameters: {'Omega_m': 0.31502564044316034, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:34,320 [classy] Got parameters {'Omega_m': 0.31502564044316034, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:34,320 [classy] Computing new state
2023-07-02 10:24:34,320 [classy] Setting parameters: {'Omega_m': 0.31502564044316034, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:34,365 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.95538493399357}
2023-07-02 10:24:34,365 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:34,367 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000596107
2023-07-02 10:24:34,367 [model] Computed derived parameters: {}
2023-07-02 10:24:34,367 [mcmc] New sample, #241:
Omega_m:0.3632792
2023-07-02 10:24:34,367 [model] Posterior to be computed for parameters {'Omega_m': 0.715790827357236}
2023-07-02 10:24:34,367 [prior] Evaluating prior at array([0.71579083])
2023-07-02 10:24:34,368 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:34,368 [model] Got input parameters: {'Omega_m': 0.715790827357236, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:34,368 [classy] Got parameters {'Omega_m': 0.715790827357236, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:34,368 [classy] Computing new state
2023-07-02 10:24:34,368 [classy] Setting parameters: {'Omega_m': 0.715790827357236, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:34,413 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 115.54804867474522}
2023-07-02 10:24:34,413 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:34,415 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.72434
2023-07-02 10:24:34,415 [model] Computed derived parameters: {}
2023-07-02 10:24:34,415 [model] Posterior to be computed for parameters {'Omega_m': 0.043051841097762666}
2023-07-02 10:24:34,415 [prior] Evaluating prior at array([0.04305184])
2023-07-02 10:24:34,415 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:34,415 [model] Posterior to be computed for parameters {'Omega_m': 0.49004534774349}
2023-07-02 10:24:34,415 [prior] Evaluating prior at array([0.49004535])
2023-07-02 10:24:34,415 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:34,415 [model] Got input parameters: {'Omega_m': 0.49004534774349, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:34,415 [classy] Got parameters {'Omega_m': 0.49004534774349, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:34,415 [classy] Computing new state
2023-07-02 10:24:34,415 [classy] Setting parameters: {'Omega_m': 0.49004534774349, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:34,461 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.06123809309858}
2023-07-02 10:24:34,462 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:34,463 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.32151
2023-07-02 10:24:34,463 [model] Computed derived parameters: {}
2023-07-02 10:24:34,463 [model] Posterior to be computed for parameters {'Omega_m': 0.22706458154749415}
2023-07-02 10:24:34,463 [prior] Evaluating prior at array([0.22706458])
2023-07-02 10:24:34,464 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:34,464 [model] Got input parameters: {'Omega_m': 0.22706458154749415, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:34,464 [classy] Got parameters {'Omega_m': 0.22706458154749415, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:34,464 [classy] Computing new state
2023-07-02 10:24:34,464 [classy] Setting parameters: {'Omega_m': 0.22706458154749415, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:34,510 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 158.99852996411025}
2023-07-02 10:24:34,510 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:34,511 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.564698
2023-07-02 10:24:34,511 [model] Computed derived parameters: {}
2023-07-02 10:24:34,511 [mcmc] New sample, #242:
Omega_m:0.3150256
2023-07-02 10:24:34,512 [model] Posterior to be computed for parameters {'Omega_m': 0.3973865477445214}
2023-07-02 10:24:34,512 [prior] Evaluating prior at array([0.39738655])
2023-07-02 10:24:34,512 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:34,512 [model] Got input parameters: {'Omega_m': 0.3973865477445214, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:34,512 [classy] Got parameters {'Omega_m': 0.3973865477445214, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:34,512 [classy] Computing new state
2023-07-02 10:24:34,512 [classy] Setting parameters: {'Omega_m': 0.3973865477445214, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:34,557 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 138.1230724732596}
2023-07-02 10:24:34,557 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:34,559 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.363652
2023-07-02 10:24:34,559 [model] Computed derived parameters: {}
2023-07-02 10:24:34,559 [mcmc] New sample, #243:
Omega_m:0.2270646
2023-07-02 10:24:34,560 [model] Posterior to be computed for parameters {'Omega_m': -0.06350734434247052}
2023-07-02 10:24:34,560 [prior] Evaluating prior at array([-0.06350734])
2023-07-02 10:24:34,560 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:34,560 [model] Posterior to be computed for parameters {'Omega_m': 0.2871379829814817}
2023-07-02 10:24:34,560 [prior] Evaluating prior at array([0.28713798])
2023-07-02 10:24:34,560 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:34,560 [model] Got input parameters: {'Omega_m': 0.2871379829814817, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:34,560 [classy] Got parameters {'Omega_m': 0.2871379829814817, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:34,560 [classy] Computing new state
2023-07-02 10:24:34,560 [classy] Setting parameters: {'Omega_m': 0.2871379829814817, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:34,606 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.42457977600435}
2023-07-02 10:24:34,606 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:34,608 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0422261
2023-07-02 10:24:34,608 [model] Computed derived parameters: {}
2023-07-02 10:24:34,608 [mcmc] New sample, #244:
Omega_m:0.3973865
2023-07-02 10:24:34,608 [model] Posterior to be computed for parameters {'Omega_m': 0.8135940563711179}
2023-07-02 10:24:34,608 [prior] Evaluating prior at array([0.81359406])
2023-07-02 10:24:34,608 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:34,608 [model] Got input parameters: {'Omega_m': 0.8135940563711179, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:34,608 [classy] Got parameters {'Omega_m': 0.8135940563711179, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:34,608 [classy] Computing new state
2023-07-02 10:24:34,608 [classy] Setting parameters: {'Omega_m': 0.8135940563711179, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:34,654 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 110.72487062043798}
2023-07-02 10:24:34,654 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:34,656 [bao_likelihood.baolikelihood] Computed log-likelihood = -6.38487
2023-07-02 10:24:34,656 [model] Computed derived parameters: {}
2023-07-02 10:24:34,656 [model] Posterior to be computed for parameters {'Omega_m': 0.3453126659945814}
2023-07-02 10:24:34,656 [prior] Evaluating prior at array([0.34531267])
2023-07-02 10:24:34,656 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:34,656 [model] Got input parameters: {'Omega_m': 0.3453126659945814, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:34,656 [classy] Got parameters {'Omega_m': 0.3453126659945814, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:34,657 [classy] Computing new state
2023-07-02 10:24:34,657 [classy] Setting parameters: {'Omega_m': 0.3453126659945814, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:34,704 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.4844981018605}
2023-07-02 10:24:34,704 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:34,706 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.061257
2023-07-02 10:24:34,706 [model] Computed derived parameters: {}
2023-07-02 10:24:34,706 [mcmc] New sample, #245:
Omega_m:0.287138
2023-07-02 10:24:34,706 [model] Posterior to be computed for parameters {'Omega_m': 0.014814874050311455}
2023-07-02 10:24:34,706 [prior] Evaluating prior at array([0.01481487])
2023-07-02 10:24:34,707 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:34,707 [model] Posterior to be computed for parameters {'Omega_m': 0.1583518979919194}
2023-07-02 10:24:34,707 [prior] Evaluating prior at array([0.1583519])
2023-07-02 10:24:34,707 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:34,707 [model] Got input parameters: {'Omega_m': 0.1583518979919194, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:34,707 [classy] Got parameters {'Omega_m': 0.1583518979919194, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:34,707 [classy] Computing new state
2023-07-02 10:24:34,707 [classy] Setting parameters: {'Omega_m': 0.1583518979919194, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:34,753 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 171.35056401781728}
2023-07-02 10:24:34,753 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:34,755 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.30041
2023-07-02 10:24:34,755 [model] Computed derived parameters: {}
2023-07-02 10:24:34,755 [model] Posterior to be computed for parameters {'Omega_m': -0.07232789128491551}
2023-07-02 10:24:34,755 [prior] Evaluating prior at array([-0.07232789])
2023-07-02 10:24:34,755 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:34,755 [model] Posterior to be computed for parameters {'Omega_m': 0.4406047717389495}
2023-07-02 10:24:34,755 [prior] Evaluating prior at array([0.44060477])
2023-07-02 10:24:34,755 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:34,755 [model] Got input parameters: {'Omega_m': 0.4406047717389495, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:34,755 [classy] Got parameters {'Omega_m': 0.4406047717389495, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:34,755 [classy] Computing new state
2023-07-02 10:24:34,755 [classy] Setting parameters: {'Omega_m': 0.4406047717389495, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:34,802 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 134.15694856947442}
2023-07-02 10:24:34,803 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:34,804 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.757042
2023-07-02 10:24:34,804 [model] Computed derived parameters: {}
2023-07-02 10:24:34,804 [mcmc] New sample, #246:
Omega_m:0.3453127
2023-07-02 10:24:34,805 [model] Posterior to be computed for parameters {'Omega_m': 0.09135897796395381}
2023-07-02 10:24:34,805 [prior] Evaluating prior at array([0.09135898])
2023-07-02 10:24:34,805 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:34,805 [model] Posterior to be computed for parameters {'Omega_m': 0.7051282331099293}
2023-07-02 10:24:34,805 [prior] Evaluating prior at array([0.70512823])
2023-07-02 10:24:34,805 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:34,805 [model] Got input parameters: {'Omega_m': 0.7051282331099293, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:34,805 [classy] Got parameters {'Omega_m': 0.7051282331099293, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:34,805 [classy] Computing new state
2023-07-02 10:24:34,805 [classy] Setting parameters: {'Omega_m': 0.7051282331099293, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:34,851 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 116.11697619286602}
2023-07-02 10:24:34,851 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:34,853 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.54688
2023-07-02 10:24:34,853 [model] Computed derived parameters: {}
2023-07-02 10:24:34,853 [model] Posterior to be computed for parameters {'Omega_m': 0.36034243431319973}
2023-07-02 10:24:34,853 [prior] Evaluating prior at array([0.36034243])
2023-07-02 10:24:34,853 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:34,853 [model] Got input parameters: {'Omega_m': 0.36034243431319973, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:34,853 [classy] Got parameters {'Omega_m': 0.36034243431319973, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:34,853 [classy] Computing new state
2023-07-02 10:24:34,853 [classy] Setting parameters: {'Omega_m': 0.36034243431319973, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:34,900 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.86380125617106}
2023-07-02 10:24:34,900 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:34,902 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.125532
2023-07-02 10:24:34,902 [model] Computed derived parameters: {}
2023-07-02 10:24:34,902 [mcmc] New sample, #247:
Omega_m:0.4406048
2023-07-02 10:24:34,902 [model] Posterior to be computed for parameters {'Omega_m': 0.5257590469810414}
2023-07-02 10:24:34,902 [prior] Evaluating prior at array([0.52575905])
2023-07-02 10:24:34,902 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:34,902 [model] Got input parameters: {'Omega_m': 0.5257590469810414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:34,902 [classy] Got parameters {'Omega_m': 0.5257590469810414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:34,902 [classy] Computing new state
2023-07-02 10:24:34,903 [classy] Setting parameters: {'Omega_m': 0.5257590469810414, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:34,950 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 127.35184051667045}
2023-07-02 10:24:34,950 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:34,951 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.78657
2023-07-02 10:24:34,952 [model] Computed derived parameters: {}
2023-07-02 10:24:34,952 [model] Posterior to be computed for parameters {'Omega_m': 0.33415319748408423}
2023-07-02 10:24:34,952 [prior] Evaluating prior at array([0.3341532])
2023-07-02 10:24:34,952 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:34,952 [model] Got input parameters: {'Omega_m': 0.33415319748408423, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:34,952 [classy] Got parameters {'Omega_m': 0.33415319748408423, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:34,952 [classy] Computing new state
2023-07-02 10:24:34,952 [classy] Setting parameters: {'Omega_m': 0.33415319748408423, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:34,999 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.73017955827726}
2023-07-02 10:24:34,999 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:35,001 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0275135
2023-07-02 10:24:35,001 [model] Computed derived parameters: {}
2023-07-02 10:24:35,001 [mcmc] New sample, #248:
Omega_m:0.3603424
2023-07-02 10:24:35,001 [model] Posterior to be computed for parameters {'Omega_m': 0.6832175223342092}
2023-07-02 10:24:35,001 [prior] Evaluating prior at array([0.68321752])
2023-07-02 10:24:35,001 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:35,001 [model] Got input parameters: {'Omega_m': 0.6832175223342092, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:35,001 [classy] Got parameters {'Omega_m': 0.6832175223342092, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:35,002 [classy] Computing new state
2023-07-02 10:24:35,002 [classy] Setting parameters: {'Omega_m': 0.6832175223342092, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:35,048 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 117.31586028291349}
2023-07-02 10:24:35,049 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:35,050 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.18527
2023-07-02 10:24:35,050 [model] Computed derived parameters: {}
2023-07-02 10:24:35,051 [model] Posterior to be computed for parameters {'Omega_m': 0.3440741346986685}
2023-07-02 10:24:35,051 [prior] Evaluating prior at array([0.34407413])
2023-07-02 10:24:35,051 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:35,051 [model] Got input parameters: {'Omega_m': 0.3440741346986685, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:35,051 [classy] Got parameters {'Omega_m': 0.3440741346986685, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:35,051 [classy] Computing new state
2023-07-02 10:24:35,051 [classy] Setting parameters: {'Omega_m': 0.3440741346986685, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:35,099 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.62092319159086}
2023-07-02 10:24:35,099 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:35,101 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0569014
2023-07-02 10:24:35,101 [model] Computed derived parameters: {}
2023-07-02 10:24:35,101 [mcmc] New sample, #249:
Omega_m:0.3341532
2023-07-02 10:24:35,101 [model] Posterior to be computed for parameters {'Omega_m': 0.44215330489697613}
2023-07-02 10:24:35,101 [prior] Evaluating prior at array([0.4421533])
2023-07-02 10:24:35,102 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:35,102 [model] Got input parameters: {'Omega_m': 0.44215330489697613, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:35,102 [classy] Got parameters {'Omega_m': 0.44215330489697613, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:35,102 [classy] Computing new state
2023-07-02 10:24:35,102 [classy] Setting parameters: {'Omega_m': 0.44215330489697613, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:35,149 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 134.0219452172869}
2023-07-02 10:24:35,149 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:35,151 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.773049
2023-07-02 10:24:35,151 [model] Computed derived parameters: {}
2023-07-02 10:24:35,151 [mcmc] New sample, #250:
Omega_m:0.3440741
2023-07-02 10:24:35,151 [model] Posterior to be computed for parameters {'Omega_m': 0.44753478777966704}
2023-07-02 10:24:35,151 [prior] Evaluating prior at array([0.44753479])
2023-07-02 10:24:35,151 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:35,151 [model] Got input parameters: {'Omega_m': 0.44753478777966704, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:35,151 [classy] Got parameters {'Omega_m': 0.44753478777966704, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:35,151 [classy] Computing new state
2023-07-02 10:24:35,151 [classy] Setting parameters: {'Omega_m': 0.44753478777966704, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:35,199 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 133.55633865327076}
2023-07-02 10:24:35,199 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:35,201 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.8296
2023-07-02 10:24:35,201 [model] Computed derived parameters: {}
2023-07-02 10:24:35,201 [mcmc] New sample, #251:
Omega_m:0.4421533
2023-07-02 10:24:35,201 [model] Posterior to be computed for parameters {'Omega_m': 0.0074004595457976}
2023-07-02 10:24:35,201 [prior] Evaluating prior at array([0.00740046])
2023-07-02 10:24:35,201 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:35,201 [model] Posterior to be computed for parameters {'Omega_m': 0.47514889791446974}
2023-07-02 10:24:35,201 [prior] Evaluating prior at array([0.4751489])
2023-07-02 10:24:35,201 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:35,201 [model] Got input parameters: {'Omega_m': 0.47514889791446974, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:35,201 [classy] Got parameters {'Omega_m': 0.47514889791446974, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:35,201 [classy] Computing new state
2023-07-02 10:24:35,201 [classy] Setting parameters: {'Omega_m': 0.47514889791446974, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:35,249 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 131.25048356993895}
2023-07-02 10:24:35,249 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:35,251 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.14066
2023-07-02 10:24:35,251 [model] Computed derived parameters: {}
2023-07-02 10:24:35,251 [mcmc] New sample, #252:
Omega_m:0.4475348
2023-07-02 10:24:35,251 [model] Posterior to be computed for parameters {'Omega_m': 0.763291990916198}
2023-07-02 10:24:35,251 [prior] Evaluating prior at array([0.76329199])
2023-07-02 10:24:35,251 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:35,251 [model] Got input parameters: {'Omega_m': 0.763291990916198, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:35,251 [classy] Got parameters {'Omega_m': 0.763291990916198, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:35,251 [classy] Computing new state
2023-07-02 10:24:35,251 [classy] Setting parameters: {'Omega_m': 0.763291990916198, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:35,298 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 113.12080673048222}
2023-07-02 10:24:35,298 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:35,299 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.52466
2023-07-02 10:24:35,299 [model] Computed derived parameters: {}
2023-07-02 10:24:35,300 [model] Posterior to be computed for parameters {'Omega_m': 0.25389606941490783}
2023-07-02 10:24:35,300 [prior] Evaluating prior at array([0.25389607])
2023-07-02 10:24:35,300 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:35,300 [model] Got input parameters: {'Omega_m': 0.25389606941490783, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:35,300 [classy] Got parameters {'Omega_m': 0.25389606941490783, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:35,300 [classy] Computing new state
2023-07-02 10:24:35,300 [classy] Setting parameters: {'Omega_m': 0.25389606941490783, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:35,346 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 154.9612875842454}
2023-07-02 10:24:35,347 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:35,349 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.245912
2023-07-02 10:24:35,349 [model] Computed derived parameters: {}
2023-07-02 10:24:35,349 [mcmc] New sample, #253:
Omega_m:0.4751489
2023-07-02 10:24:35,349 [model] Posterior to be computed for parameters {'Omega_m': 0.5035523193029205}
2023-07-02 10:24:35,349 [prior] Evaluating prior at array([0.50355232])
2023-07-02 10:24:35,349 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:35,349 [model] Got input parameters: {'Omega_m': 0.5035523193029205, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:35,349 [classy] Got parameters {'Omega_m': 0.5035523193029205, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:35,349 [classy] Computing new state
2023-07-02 10:24:35,349 [classy] Setting parameters: {'Omega_m': 0.5035523193029205, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:35,396 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 129.01380379923384}
2023-07-02 10:24:35,397 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:35,399 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.49249
2023-07-02 10:24:35,399 [model] Computed derived parameters: {}
2023-07-02 10:24:35,399 [model] Posterior to be computed for parameters {'Omega_m': 0.19934393492241625}
2023-07-02 10:24:35,399 [prior] Evaluating prior at array([0.19934393])
2023-07-02 10:24:35,399 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:35,399 [model] Got input parameters: {'Omega_m': 0.19934393492241625, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:35,399 [classy] Got parameters {'Omega_m': 0.19934393492241625, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:35,400 [classy] Computing new state
2023-07-02 10:24:35,400 [classy] Setting parameters: {'Omega_m': 0.19934393492241625, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:35,446 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 163.5900623072125}
2023-07-02 10:24:35,446 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:35,449 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.07912
2023-07-02 10:24:35,449 [model] Computed derived parameters: {}
2023-07-02 10:24:35,449 [model] Posterior to be computed for parameters {'Omega_m': 0.26766418940777553}
2023-07-02 10:24:35,449 [prior] Evaluating prior at array([0.26766419])
2023-07-02 10:24:35,449 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:35,449 [model] Got input parameters: {'Omega_m': 0.26766418940777553, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:35,449 [classy] Got parameters {'Omega_m': 0.26766418940777553, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:35,449 [classy] Computing new state
2023-07-02 10:24:35,449 [classy] Setting parameters: {'Omega_m': 0.26766418940777553, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:35,495 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.02464293513242}
2023-07-02 10:24:35,495 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:35,498 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.138625
2023-07-02 10:24:35,498 [model] Computed derived parameters: {}
2023-07-02 10:24:35,498 [mcmc] New sample, #254:
Omega_m:0.2538961
2023-07-02 10:24:35,498 [model] Posterior to be computed for parameters {'Omega_m': 0.09468278122576704}
2023-07-02 10:24:35,498 [prior] Evaluating prior at array([0.09468278])
2023-07-02 10:24:35,498 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:35,498 [model] Posterior to be computed for parameters {'Omega_m': 0.2586908273376082}
2023-07-02 10:24:35,499 [prior] Evaluating prior at array([0.25869083])
2023-07-02 10:24:35,499 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:35,499 [model] Got input parameters: {'Omega_m': 0.2586908273376082, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:35,499 [classy] Got parameters {'Omega_m': 0.2586908273376082, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:35,499 [classy] Computing new state
2023-07-02 10:24:35,499 [classy] Setting parameters: {'Omega_m': 0.2586908273376082, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:35,545 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 154.27706515619906}
2023-07-02 10:24:35,545 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:35,548 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.204581
2023-07-02 10:24:35,548 [model] Computed derived parameters: {}
2023-07-02 10:24:35,548 [mcmc] New sample, #255:
Omega_m:0.2676642
2023-07-02 10:24:35,548 [model] Posterior to be computed for parameters {'Omega_m': -0.4189486526211731}
2023-07-02 10:24:35,548 [prior] Evaluating prior at array([-0.41894865])
2023-07-02 10:24:35,548 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:35,549 [model] Posterior to be computed for parameters {'Omega_m': 0.23243332303169287}
2023-07-02 10:24:35,549 [prior] Evaluating prior at array([0.23243332])
2023-07-02 10:24:35,549 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:35,549 [model] Got input parameters: {'Omega_m': 0.23243332303169287, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:35,549 [classy] Got parameters {'Omega_m': 0.23243332303169287, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:35,549 [classy] Computing new state
2023-07-02 10:24:35,549 [classy] Setting parameters: {'Omega_m': 0.23243332303169287, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:35,598 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 158.1608430267442}
2023-07-02 10:24:35,598 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:35,600 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.488127
2023-07-02 10:24:35,600 [model] Computed derived parameters: {}
2023-07-02 10:24:35,600 [mcmc] New sample, #256:
Omega_m:0.2586908
2023-07-02 10:24:35,600 [model] Posterior to be computed for parameters {'Omega_m': 0.3425795401572632}
2023-07-02 10:24:35,600 [prior] Evaluating prior at array([0.34257954])
2023-07-02 10:24:35,600 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:35,600 [model] Got input parameters: {'Omega_m': 0.3425795401572632, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:35,600 [classy] Got parameters {'Omega_m': 0.3425795401572632, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:35,600 [classy] Computing new state
2023-07-02 10:24:35,600 [classy] Setting parameters: {'Omega_m': 0.3425795401572632, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:35,645 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.78616251378932}
2023-07-02 10:24:35,646 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:35,648 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0518435
2023-07-02 10:24:35,649 [model] Computed derived parameters: {}
2023-07-02 10:24:35,649 [mcmc] New sample, #257:
Omega_m:0.2324333
2023-07-02 10:24:35,649 [model] Posterior to be computed for parameters {'Omega_m': 0.5358663448071408}
2023-07-02 10:24:35,649 [prior] Evaluating prior at array([0.53586634])
2023-07-02 10:24:35,649 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:35,649 [model] Got input parameters: {'Omega_m': 0.5358663448071408, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:35,649 [classy] Got parameters {'Omega_m': 0.5358663448071408, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:35,649 [classy] Computing new state
2023-07-02 10:24:35,649 [classy] Setting parameters: {'Omega_m': 0.5358663448071408, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:35,698 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 126.61890267443849}
2023-07-02 10:24:35,698 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:35,700 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.92526
2023-07-02 10:24:35,700 [model] Computed derived parameters: {}
2023-07-02 10:24:35,700 [model] Posterior to be computed for parameters {'Omega_m': 0.19448513918481194}
2023-07-02 10:24:35,700 [prior] Evaluating prior at array([0.19448514])
2023-07-02 10:24:35,700 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:35,700 [model] Got input parameters: {'Omega_m': 0.19448513918481194, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:35,700 [classy] Got parameters {'Omega_m': 0.19448513918481194, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:35,700 [classy] Computing new state
2023-07-02 10:24:35,700 [classy] Setting parameters: {'Omega_m': 0.19448513918481194, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:35,747 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 164.44481022917861}
2023-07-02 10:24:35,747 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:35,749 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.19228
2023-07-02 10:24:35,749 [model] Computed derived parameters: {}
2023-07-02 10:24:35,749 [mcmc] New sample, #258:
Omega_m:0.3425795
2023-07-02 10:24:35,749 [model] Posterior to be computed for parameters {'Omega_m': -0.2696260730425051}
2023-07-02 10:24:35,749 [prior] Evaluating prior at array([-0.26962607])
2023-07-02 10:24:35,750 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:35,750 [model] Posterior to be computed for parameters {'Omega_m': 0.24197848541038083}
2023-07-02 10:24:35,750 [prior] Evaluating prior at array([0.24197849])
2023-07-02 10:24:35,750 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:35,750 [model] Got input parameters: {'Omega_m': 0.24197848541038083, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:35,750 [classy] Got parameters {'Omega_m': 0.24197848541038083, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:35,750 [classy] Computing new state
2023-07-02 10:24:35,750 [classy] Setting parameters: {'Omega_m': 0.24197848541038083, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:35,798 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 156.70934473984335}
2023-07-02 10:24:35,798 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:35,800 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.368316
2023-07-02 10:24:35,800 [model] Computed derived parameters: {}
2023-07-02 10:24:35,800 [mcmc] New sample, #259:
Omega_m:0.1944851
2023-07-02 10:24:35,800 [model] Posterior to be computed for parameters {'Omega_m': 0.669964820249099}
2023-07-02 10:24:35,800 [prior] Evaluating prior at array([0.66996482])
2023-07-02 10:24:35,800 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:35,800 [model] Got input parameters: {'Omega_m': 0.669964820249099, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:35,800 [classy] Got parameters {'Omega_m': 0.669964820249099, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:35,800 [classy] Computing new state
2023-07-02 10:24:35,801 [classy] Setting parameters: {'Omega_m': 0.669964820249099, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:35,845 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 118.06126384739129}
2023-07-02 10:24:35,845 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:35,848 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.96882
2023-07-02 10:24:35,848 [model] Computed derived parameters: {}
2023-07-02 10:24:35,848 [model] Posterior to be computed for parameters {'Omega_m': 0.4754647738298306}
2023-07-02 10:24:35,848 [prior] Evaluating prior at array([0.47546477])
2023-07-02 10:24:35,848 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:35,848 [model] Got input parameters: {'Omega_m': 0.4754647738298306, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:35,849 [classy] Got parameters {'Omega_m': 0.4754647738298306, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:35,849 [classy] Computing new state
2023-07-02 10:24:35,849 [classy] Setting parameters: {'Omega_m': 0.4754647738298306, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:35,894 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 131.22487984269478}
2023-07-02 10:24:35,894 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:35,896 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.14441
2023-07-02 10:24:35,896 [model] Computed derived parameters: {}
2023-07-02 10:24:35,896 [model] Posterior to be computed for parameters {'Omega_m': 0.04831254976813887}
2023-07-02 10:24:35,896 [prior] Evaluating prior at array([0.04831255])
2023-07-02 10:24:35,896 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:35,897 [model] Posterior to be computed for parameters {'Omega_m': 0.1482742554819501}
2023-07-02 10:24:35,897 [prior] Evaluating prior at array([0.14827426])
2023-07-02 10:24:35,897 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:35,897 [model] Got input parameters: {'Omega_m': 0.1482742554819501, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:35,897 [classy] Got parameters {'Omega_m': 0.1482742554819501, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:35,897 [classy] Computing new state
2023-07-02 10:24:35,897 [classy] Setting parameters: {'Omega_m': 0.1482742554819501, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:35,946 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 173.47268589787632}
2023-07-02 10:24:35,947 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:35,949 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.70849
2023-07-02 10:24:35,949 [model] Computed derived parameters: {}
2023-07-02 10:24:35,949 [model] Posterior to be computed for parameters {'Omega_m': 0.04535082997946693}
2023-07-02 10:24:35,949 [prior] Evaluating prior at array([0.04535083])
2023-07-02 10:24:35,949 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:35,949 [model] Posterior to be computed for parameters {'Omega_m': 0.25082544616248903}
2023-07-02 10:24:35,949 [prior] Evaluating prior at array([0.25082545])
2023-07-02 10:24:35,949 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:35,949 [model] Got input parameters: {'Omega_m': 0.25082544616248903, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:35,949 [classy] Got parameters {'Omega_m': 0.25082544616248903, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:35,949 [classy] Computing new state
2023-07-02 10:24:35,949 [classy] Setting parameters: {'Omega_m': 0.25082544616248903, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:35,995 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 155.40510940046903}
2023-07-02 10:24:35,996 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:35,998 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.274707
2023-07-02 10:24:35,998 [model] Computed derived parameters: {}
2023-07-02 10:24:35,998 [mcmc] New sample, #260:
Omega_m:0.2419785
2023-07-02 10:24:35,998 [model] Posterior to be computed for parameters {'Omega_m': 0.49441129641189674}
2023-07-02 10:24:35,998 [prior] Evaluating prior at array([0.4944113])
2023-07-02 10:24:35,998 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:35,998 [model] Got input parameters: {'Omega_m': 0.49441129641189674, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:35,998 [classy] Got parameters {'Omega_m': 0.49441129641189674, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:35,998 [classy] Computing new state
2023-07-02 10:24:35,998 [classy] Setting parameters: {'Omega_m': 0.49441129641189674, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:36,047 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 129.7195185083725}
2023-07-02 10:24:36,048 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:36,051 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.37608
2023-07-02 10:24:36,051 [model] Computed derived parameters: {}
2023-07-02 10:24:36,051 [mcmc] New sample, #261:
Omega_m:0.2508254
2023-07-02 10:24:36,051 [model] Posterior to be computed for parameters {'Omega_m': 1.4009213072089395}
2023-07-02 10:24:36,051 [prior] Evaluating prior at array([1.40092131])
2023-07-02 10:24:36,051 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:36,051 [model] Posterior to be computed for parameters {'Omega_m': 1.0511254563929695}
2023-07-02 10:24:36,051 [prior] Evaluating prior at array([1.05112546])
2023-07-02 10:24:36,052 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:36,052 [model] Posterior to be computed for parameters {'Omega_m': 0.33671623275237167}
2023-07-02 10:24:36,052 [prior] Evaluating prior at array([0.33671623])
2023-07-02 10:24:36,052 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:36,052 [model] Got input parameters: {'Omega_m': 0.33671623275237167, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:36,052 [classy] Got parameters {'Omega_m': 0.33671623275237167, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:36,052 [classy] Computing new state
2023-07-02 10:24:36,052 [classy] Setting parameters: {'Omega_m': 0.33671623275237167, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:36,101 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.44077752729874}
2023-07-02 10:24:36,101 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:36,103 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0341484
2023-07-02 10:24:36,103 [model] Computed derived parameters: {}
2023-07-02 10:24:36,103 [mcmc] New sample, #262:
Omega_m:0.4944113
2023-07-02 10:24:36,103 [model] Posterior to be computed for parameters {'Omega_m': 0.5776696490323929}
2023-07-02 10:24:36,103 [prior] Evaluating prior at array([0.57766965])
2023-07-02 10:24:36,103 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:36,103 [model] Got input parameters: {'Omega_m': 0.5776696490323929, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:36,103 [classy] Got parameters {'Omega_m': 0.5776696490323929, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:36,103 [classy] Computing new state
2023-07-02 10:24:36,103 [classy] Setting parameters: {'Omega_m': 0.5776696490323929, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:36,150 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 123.73115406738957}
2023-07-02 10:24:36,151 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:36,152 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.52629
2023-07-02 10:24:36,152 [model] Computed derived parameters: {}
2023-07-02 10:24:36,152 [mcmc] New sample, #263:
Omega_m:0.3367162
2023-07-02 10:24:36,152 [model] Posterior to be computed for parameters {'Omega_m': 0.4018880896054711}
2023-07-02 10:24:36,152 [prior] Evaluating prior at array([0.40188809])
2023-07-02 10:24:36,153 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:36,153 [model] Got input parameters: {'Omega_m': 0.4018880896054711, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:36,153 [classy] Got parameters {'Omega_m': 0.4018880896054711, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:36,153 [classy] Computing new state
2023-07-02 10:24:36,153 [classy] Setting parameters: {'Omega_m': 0.4018880896054711, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:36,200 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 137.69113303730134}
2023-07-02 10:24:36,200 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:36,202 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.399362
2023-07-02 10:24:36,202 [model] Computed derived parameters: {}
2023-07-02 10:24:36,202 [mcmc] New sample, #264:
Omega_m:0.5776696
2023-07-02 10:24:36,202 [model] Posterior to be computed for parameters {'Omega_m': 0.17708367556916405}
2023-07-02 10:24:36,202 [prior] Evaluating prior at array([0.17708368])
2023-07-02 10:24:36,203 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:36,203 [model] Got input parameters: {'Omega_m': 0.17708367556916405, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:36,203 [classy] Got parameters {'Omega_m': 0.17708367556916405, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:36,203 [classy] Computing new state
2023-07-02 10:24:36,203 [classy] Setting parameters: {'Omega_m': 0.17708367556916405, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:36,249 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 167.6431315906166}
2023-07-02 10:24:36,249 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:36,251 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.66306
2023-07-02 10:24:36,251 [model] Computed derived parameters: {}
2023-07-02 10:24:36,251 [model] Posterior to be computed for parameters {'Omega_m': 0.8505636478000956}
2023-07-02 10:24:36,251 [prior] Evaluating prior at array([0.85056365])
2023-07-02 10:24:36,251 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:36,251 [model] Got input parameters: {'Omega_m': 0.8505636478000956, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:36,251 [classy] Got parameters {'Omega_m': 0.8505636478000956, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:36,251 [classy] Computing new state
2023-07-02 10:24:36,251 [classy] Setting parameters: {'Omega_m': 0.8505636478000956, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:36,296 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 109.06642259311982}
2023-07-02 10:24:36,296 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:36,299 [bao_likelihood.baolikelihood] Computed log-likelihood = -7.02228
2023-07-02 10:24:36,299 [model] Computed derived parameters: {}
2023-07-02 10:24:36,299 [model] Posterior to be computed for parameters {'Omega_m': 0.00765252349926937}
2023-07-02 10:24:36,299 [prior] Evaluating prior at array([0.00765252])
2023-07-02 10:24:36,299 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:36,299 [model] Posterior to be computed for parameters {'Omega_m': 0.18434806569073553}
2023-07-02 10:24:36,299 [prior] Evaluating prior at array([0.18434807])
2023-07-02 10:24:36,299 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:36,299 [model] Got input parameters: {'Omega_m': 0.18434806569073553, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:36,299 [classy] Got parameters {'Omega_m': 0.18434806569073553, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:36,299 [classy] Computing new state
2023-07-02 10:24:36,300 [classy] Setting parameters: {'Omega_m': 0.18434806569073553, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:36,344 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 166.28095143349583}
2023-07-02 10:24:36,344 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:36,346 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.45347
2023-07-02 10:24:36,346 [model] Computed derived parameters: {}
2023-07-02 10:24:36,347 [model] Posterior to be computed for parameters {'Omega_m': 0.25294945200723634}
2023-07-02 10:24:36,347 [prior] Evaluating prior at array([0.25294945])
2023-07-02 10:24:36,347 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:36,347 [model] Got input parameters: {'Omega_m': 0.25294945200723634, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:36,347 [classy] Got parameters {'Omega_m': 0.25294945200723634, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:36,347 [classy] Computing new state
2023-07-02 10:24:36,347 [classy] Setting parameters: {'Omega_m': 0.25294945200723634, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:36,393 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 155.09763710699846}
2023-07-02 10:24:36,393 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:36,395 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.254593
2023-07-02 10:24:36,395 [model] Computed derived parameters: {}
2023-07-02 10:24:36,395 [mcmc] New sample, #265:
Omega_m:0.4018881
2023-07-02 10:24:36,395 [model] Posterior to be computed for parameters {'Omega_m': 0.20762391451315676}
2023-07-02 10:24:36,395 [prior] Evaluating prior at array([0.20762391])
2023-07-02 10:24:36,395 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:36,395 [model] Got input parameters: {'Omega_m': 0.20762391451315676, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:36,395 [classy] Got parameters {'Omega_m': 0.20762391451315676, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:36,395 [classy] Computing new state
2023-07-02 10:24:36,395 [classy] Setting parameters: {'Omega_m': 0.20762391451315676, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:36,442 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 162.16924759509808}
2023-07-02 10:24:36,442 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:36,444 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.902995
2023-07-02 10:24:36,444 [model] Computed derived parameters: {}
2023-07-02 10:24:36,444 [mcmc] New sample, #266:
Omega_m:0.2529495
2023-07-02 10:24:36,444 [model] Posterior to be computed for parameters {'Omega_m': 0.16185614320184485}
2023-07-02 10:24:36,444 [prior] Evaluating prior at array([0.16185614])
2023-07-02 10:24:36,444 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:36,444 [model] Got input parameters: {'Omega_m': 0.16185614320184485, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:36,444 [classy] Got parameters {'Omega_m': 0.16185614320184485, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:36,444 [classy] Computing new state
2023-07-02 10:24:36,444 [classy] Setting parameters: {'Omega_m': 0.16185614320184485, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:36,490 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 170.63434306730588}
2023-07-02 10:24:36,490 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:36,492 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.16973
2023-07-02 10:24:36,492 [model] Computed derived parameters: {}
2023-07-02 10:24:36,492 [mcmc] New sample, #267:
Omega_m:0.2076239
2023-07-02 10:24:36,492 [model] Posterior to be computed for parameters {'Omega_m': -0.18943797647855606}
2023-07-02 10:24:36,492 [prior] Evaluating prior at array([-0.18943798])
2023-07-02 10:24:36,492 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:36,492 [model] Posterior to be computed for parameters {'Omega_m': 0.16725668375964547}
2023-07-02 10:24:36,492 [prior] Evaluating prior at array([0.16725668])
2023-07-02 10:24:36,493 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:36,493 [model] Got input parameters: {'Omega_m': 0.16725668375964547, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:36,493 [classy] Got parameters {'Omega_m': 0.16725668375964547, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:36,493 [classy] Computing new state
2023-07-02 10:24:36,493 [classy] Setting parameters: {'Omega_m': 0.16725668375964547, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:36,539 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 169.55154163522064}
2023-07-02 10:24:36,539 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:36,541 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.97901
2023-07-02 10:24:36,541 [model] Computed derived parameters: {}
2023-07-02 10:24:36,541 [mcmc] New sample, #268:
Omega_m:0.1618561
2023-07-02 10:24:36,541 [model] Posterior to be computed for parameters {'Omega_m': 0.4435351705972473}
2023-07-02 10:24:36,541 [prior] Evaluating prior at array([0.44353517])
2023-07-02 10:24:36,541 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:36,541 [model] Got input parameters: {'Omega_m': 0.4435351705972473, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:36,541 [classy] Got parameters {'Omega_m': 0.4435351705972473, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:36,541 [classy] Computing new state
2023-07-02 10:24:36,541 [classy] Setting parameters: {'Omega_m': 0.4435351705972473, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:36,588 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 133.90186111654256}
2023-07-02 10:24:36,588 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:36,590 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.787434
2023-07-02 10:24:36,590 [model] Computed derived parameters: {}
2023-07-02 10:24:36,590 [mcmc] New sample, #269:
Omega_m:0.1672567
2023-07-02 10:24:36,590 [model] Posterior to be computed for parameters {'Omega_m': 0.39585642584929737}
2023-07-02 10:24:36,590 [prior] Evaluating prior at array([0.39585643])
2023-07-02 10:24:36,590 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:36,590 [model] Got input parameters: {'Omega_m': 0.39585642584929737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:36,590 [classy] Got parameters {'Omega_m': 0.39585642584929737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:36,590 [classy] Computing new state
2023-07-02 10:24:36,590 [classy] Setting parameters: {'Omega_m': 0.39585642584929737, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:36,636 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 138.27094987964205}
2023-07-02 10:24:36,636 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:36,638 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.351822
2023-07-02 10:24:36,638 [model] Computed derived parameters: {}
2023-07-02 10:24:36,638 [mcmc] New sample, #270:
Omega_m:0.4435352
2023-07-02 10:24:36,638 [model] Posterior to be computed for parameters {'Omega_m': 0.196328920332325}
2023-07-02 10:24:36,638 [prior] Evaluating prior at array([0.19632892])
2023-07-02 10:24:36,639 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:36,639 [model] Got input parameters: {'Omega_m': 0.196328920332325, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:36,639 [classy] Got parameters {'Omega_m': 0.196328920332325, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:36,639 [classy] Computing new state
2023-07-02 10:24:36,639 [classy] Setting parameters: {'Omega_m': 0.196328920332325, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:36,685 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 164.118560493476}
2023-07-02 10:24:36,685 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:36,687 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.14845
2023-07-02 10:24:36,687 [model] Computed derived parameters: {}
2023-07-02 10:24:36,687 [mcmc] New sample, #271:
Omega_m:0.3958564
2023-07-02 10:24:36,687 [model] Posterior to be computed for parameters {'Omega_m': 0.13590762948900806}
2023-07-02 10:24:36,687 [prior] Evaluating prior at array([0.13590763])
2023-07-02 10:24:36,687 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:36,687 [model] Got input parameters: {'Omega_m': 0.13590762948900806, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:36,687 [classy] Got parameters {'Omega_m': 0.13590762948900806, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:36,687 [classy] Computing new state
2023-07-02 10:24:36,688 [classy] Setting parameters: {'Omega_m': 0.13590762948900806, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:36,734 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 176.21287425332562}
2023-07-02 10:24:36,734 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:36,735 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.28097
2023-07-02 10:24:36,735 [model] Computed derived parameters: {}
2023-07-02 10:24:36,736 [model] Posterior to be computed for parameters {'Omega_m': -0.0567035791899653}
2023-07-02 10:24:36,736 [prior] Evaluating prior at array([-0.05670358])
2023-07-02 10:24:36,736 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:36,736 [model] Posterior to be computed for parameters {'Omega_m': -0.17903738361380053}
2023-07-02 10:24:36,736 [prior] Evaluating prior at array([-0.17903738])
2023-07-02 10:24:36,736 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:36,736 [model] Posterior to be computed for parameters {'Omega_m': 0.2653467234624885}
2023-07-02 10:24:36,736 [prior] Evaluating prior at array([0.26534672])
2023-07-02 10:24:36,736 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:36,736 [model] Got input parameters: {'Omega_m': 0.2653467234624885, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:36,736 [classy] Got parameters {'Omega_m': 0.2653467234624885, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:36,736 [classy] Computing new state
2023-07-02 10:24:36,736 [classy] Setting parameters: {'Omega_m': 0.2653467234624885, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:36,782 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.3446820769581}
2023-07-02 10:24:36,782 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:36,784 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.154282
2023-07-02 10:24:36,784 [model] Computed derived parameters: {}
2023-07-02 10:24:36,784 [mcmc] New sample, #272:
Omega_m:0.1963289
2023-07-02 10:24:36,784 [model] Posterior to be computed for parameters {'Omega_m': 0.4248475712417653}
2023-07-02 10:24:36,784 [prior] Evaluating prior at array([0.42484757])
2023-07-02 10:24:36,784 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:36,785 [model] Got input parameters: {'Omega_m': 0.4248475712417653, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:36,785 [classy] Got parameters {'Omega_m': 0.4248475712417653, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:36,785 [classy] Computing new state
2023-07-02 10:24:36,785 [classy] Setting parameters: {'Omega_m': 0.4248475712417653, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:36,832 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 135.5576544370041}
2023-07-02 10:24:36,832 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:36,833 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.601204
2023-07-02 10:24:36,833 [model] Computed derived parameters: {}
2023-07-02 10:24:36,834 [model] Posterior to be computed for parameters {'Omega_m': 0.5680148171955208}
2023-07-02 10:24:36,834 [prior] Evaluating prior at array([0.56801482])
2023-07-02 10:24:36,834 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:36,834 [model] Got input parameters: {'Omega_m': 0.5680148171955208, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:36,834 [classy] Got parameters {'Omega_m': 0.5680148171955208, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:36,834 [classy] Computing new state
2023-07-02 10:24:36,834 [classy] Setting parameters: {'Omega_m': 0.5680148171955208, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:36,880 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 124.3784680091329}
2023-07-02 10:24:36,881 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:36,882 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.38391
2023-07-02 10:24:36,882 [model] Computed derived parameters: {}
2023-07-02 10:24:36,883 [model] Posterior to be computed for parameters {'Omega_m': 0.36286347346978975}
2023-07-02 10:24:36,883 [prior] Evaluating prior at array([0.36286347])
2023-07-02 10:24:36,883 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:36,883 [model] Got input parameters: {'Omega_m': 0.36286347346978975, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:36,883 [classy] Got parameters {'Omega_m': 0.36286347346978975, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:36,883 [classy] Computing new state
2023-07-02 10:24:36,883 [classy] Setting parameters: {'Omega_m': 0.36286347346978975, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:36,929 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.59809126242817}
2023-07-02 10:24:36,929 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:36,931 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.138289
2023-07-02 10:24:36,931 [model] Computed derived parameters: {}
2023-07-02 10:24:36,931 [mcmc] New sample, #273:
Omega_m:0.2653467
2023-07-02 10:24:36,931 [model] Posterior to be computed for parameters {'Omega_m': 0.7437438715764731}
2023-07-02 10:24:36,931 [prior] Evaluating prior at array([0.74374387])
2023-07-02 10:24:36,931 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:36,931 [model] Got input parameters: {'Omega_m': 0.7437438715764731, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:36,931 [classy] Got parameters {'Omega_m': 0.7437438715764731, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:36,931 [classy] Computing new state
2023-07-02 10:24:36,931 [classy] Setting parameters: {'Omega_m': 0.7437438715764731, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:36,978 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 114.09915664233431}
2023-07-02 10:24:36,978 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:36,979 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.19359
2023-07-02 10:24:36,979 [model] Computed derived parameters: {}
2023-07-02 10:24:36,980 [model] Posterior to be computed for parameters {'Omega_m': 0.6627150847305496}
2023-07-02 10:24:36,980 [prior] Evaluating prior at array([0.66271508])
2023-07-02 10:24:36,980 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:36,980 [model] Got input parameters: {'Omega_m': 0.6627150847305496, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:36,980 [classy] Got parameters {'Omega_m': 0.6627150847305496, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:36,980 [classy] Computing new state
2023-07-02 10:24:36,980 [classy] Setting parameters: {'Omega_m': 0.6627150847305496, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:37,033 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 118.47573240531189}
2023-07-02 10:24:37,033 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:37,035 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.85122
2023-07-02 10:24:37,035 [model] Computed derived parameters: {}
2023-07-02 10:24:37,035 [model] Posterior to be computed for parameters {'Omega_m': 0.43047220982149575}
2023-07-02 10:24:37,035 [prior] Evaluating prior at array([0.43047221])
2023-07-02 10:24:37,035 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:37,035 [model] Got input parameters: {'Omega_m': 0.43047220982149575, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:37,035 [classy] Got parameters {'Omega_m': 0.43047220982149575, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:37,035 [classy] Computing new state
2023-07-02 10:24:37,035 [classy] Setting parameters: {'Omega_m': 0.43047220982149575, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:37,082 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 135.0519829464644}
2023-07-02 10:24:37,082 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:37,084 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.655309
2023-07-02 10:24:37,084 [model] Computed derived parameters: {}
2023-07-02 10:24:37,084 [mcmc] New sample, #274:
Omega_m:0.3628635
2023-07-02 10:24:37,084 [model] Posterior to be computed for parameters {'Omega_m': 0.4891440713808798}
2023-07-02 10:24:37,084 [prior] Evaluating prior at array([0.48914407])
2023-07-02 10:24:37,084 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:37,084 [model] Got input parameters: {'Omega_m': 0.4891440713808798, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:37,084 [classy] Got parameters {'Omega_m': 0.4891440713808798, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:37,084 [classy] Computing new state
2023-07-02 10:24:37,085 [classy] Setting parameters: {'Omega_m': 0.4891440713808798, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:37,132 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.13216040401042}
2023-07-02 10:24:37,132 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:37,134 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.31033
2023-07-02 10:24:37,134 [model] Computed derived parameters: {}
2023-07-02 10:24:37,134 [mcmc] New sample, #275:
Omega_m:0.4304722
2023-07-02 10:24:37,134 [model] Posterior to be computed for parameters {'Omega_m': 0.9547213399664646}
2023-07-02 10:24:37,134 [prior] Evaluating prior at array([0.95472134])
2023-07-02 10:24:37,134 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:37,134 [model] Got input parameters: {'Omega_m': 0.9547213399664646, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:37,134 [classy] Got parameters {'Omega_m': 0.9547213399664646, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:37,134 [classy] Computing new state
2023-07-02 10:24:37,134 [classy] Setting parameters: {'Omega_m': 0.9547213399664646, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:37,181 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 104.79714900995674}
2023-07-02 10:24:37,181 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:37,183 [bao_likelihood.baolikelihood] Computed log-likelihood = -8.82713
2023-07-02 10:24:37,183 [model] Computed derived parameters: {}
2023-07-02 10:24:37,183 [model] Posterior to be computed for parameters {'Omega_m': 0.366412741174291}
2023-07-02 10:24:37,183 [prior] Evaluating prior at array([0.36641274])
2023-07-02 10:24:37,183 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:37,183 [model] Got input parameters: {'Omega_m': 0.366412741174291, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:37,183 [classy] Got parameters {'Omega_m': 0.366412741174291, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:37,183 [classy] Computing new state
2023-07-02 10:24:37,183 [classy] Setting parameters: {'Omega_m': 0.366412741174291, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:37,231 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.2268861967495}
2023-07-02 10:24:37,231 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:37,232 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.157164
2023-07-02 10:24:37,233 [model] Computed derived parameters: {}
2023-07-02 10:24:37,233 [mcmc] New sample, #276:
Omega_m:0.4891441
2023-07-02 10:24:37,233 [model] Posterior to be computed for parameters {'Omega_m': 0.2793292224374933}
2023-07-02 10:24:37,233 [prior] Evaluating prior at array([0.27932922])
2023-07-02 10:24:37,233 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:37,233 [model] Got input parameters: {'Omega_m': 0.2793292224374933, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:37,233 [classy] Got parameters {'Omega_m': 0.2793292224374933, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:37,233 [classy] Computing new state
2023-07-02 10:24:37,233 [classy] Setting parameters: {'Omega_m': 0.2793292224374933, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:37,281 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.44852361158812}
2023-07-02 10:24:37,281 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:37,282 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0736073
2023-07-02 10:24:37,283 [model] Computed derived parameters: {}
2023-07-02 10:24:37,283 [mcmc] New sample, #277:
Omega_m:0.3664127
2023-07-02 10:24:37,283 [model] Posterior to be computed for parameters {'Omega_m': -0.45887873046397015}
2023-07-02 10:24:37,283 [prior] Evaluating prior at array([-0.45887873])
2023-07-02 10:24:37,283 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:37,283 [model] Posterior to be computed for parameters {'Omega_m': 0.08126904742367341}
2023-07-02 10:24:37,283 [prior] Evaluating prior at array([0.08126905])
2023-07-02 10:24:37,283 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:37,283 [model] Posterior to be computed for parameters {'Omega_m': 0.5450522016189925}
2023-07-02 10:24:37,283 [prior] Evaluating prior at array([0.5450522])
2023-07-02 10:24:37,283 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:37,283 [model] Got input parameters: {'Omega_m': 0.5450522016189925, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:37,283 [classy] Got parameters {'Omega_m': 0.5450522016189925, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:37,283 [classy] Computing new state
2023-07-02 10:24:37,283 [classy] Setting parameters: {'Omega_m': 0.5450522016189925, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:37,333 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 125.96492433812496}
2023-07-02 10:24:37,333 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:37,335 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.05371
2023-07-02 10:24:37,335 [model] Computed derived parameters: {}
2023-07-02 10:24:37,335 [mcmc] New sample, #278:
Omega_m:0.2793292
2023-07-02 10:24:37,335 [model] Posterior to be computed for parameters {'Omega_m': 0.9699614982179212}
2023-07-02 10:24:37,335 [prior] Evaluating prior at array([0.9699615])
2023-07-02 10:24:37,335 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:37,335 [model] Got input parameters: {'Omega_m': 0.9699614982179212, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:37,335 [classy] Got parameters {'Omega_m': 0.9699614982179212, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:37,335 [classy] Computing new state
2023-07-02 10:24:37,335 [classy] Setting parameters: {'Omega_m': 0.9699614982179212, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:37,381 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 104.21700166276592}
2023-07-02 10:24:37,381 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:37,383 [bao_likelihood.baolikelihood] Computed log-likelihood = -9.09114
2023-07-02 10:24:37,383 [model] Computed derived parameters: {}
2023-07-02 10:24:37,383 [model] Posterior to be computed for parameters {'Omega_m': 0.3230633915456744}
2023-07-02 10:24:37,383 [prior] Evaluating prior at array([0.32306339])
2023-07-02 10:24:37,383 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:37,383 [model] Got input parameters: {'Omega_m': 0.3230633915456744, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:37,383 [classy] Got parameters {'Omega_m': 0.3230633915456744, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:37,383 [classy] Computing new state
2023-07-02 10:24:37,383 [classy] Setting parameters: {'Omega_m': 0.3230633915456744, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:37,431 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.00595288651814}
2023-07-02 10:24:37,431 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:37,433 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00688862
2023-07-02 10:24:37,433 [model] Computed derived parameters: {}
2023-07-02 10:24:37,433 [mcmc] New sample, #279:
Omega_m:0.5450522
2023-07-02 10:24:37,433 [model] Posterior to be computed for parameters {'Omega_m': 0.41837574108630543}
2023-07-02 10:24:37,433 [prior] Evaluating prior at array([0.41837574])
2023-07-02 10:24:37,433 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:37,433 [model] Got input parameters: {'Omega_m': 0.41837574108630543, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:37,433 [classy] Got parameters {'Omega_m': 0.41837574108630543, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:37,433 [classy] Computing new state
2023-07-02 10:24:37,433 [classy] Setting parameters: {'Omega_m': 0.41837574108630543, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:37,481 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 136.14761534235186}
2023-07-02 10:24:37,481 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:37,482 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.541125
2023-07-02 10:24:37,483 [model] Computed derived parameters: {}
2023-07-02 10:24:37,483 [mcmc] New sample, #280:
Omega_m:0.3230634
2023-07-02 10:24:37,483 [mcmc] Learn + convergence test @ 280 samples accepted.
2023-07-02 10:24:37,483 [mcmc] Ready to check convergence and learn a new proposal covmat
2023-07-02 10:24:37,487 [mcmc] - Acceptance rate: 0.474
2023-07-02 10:24:37,488 [mcmc] - Condition number = 1
2023-07-02 10:24:37,488 [mcmc] - Eigenvalues = array([0.06868928])
2023-07-02 10:24:37,488 [mcmc] - Convergence of means: R-1 = 0.068689 after 224 accepted steps
2023-07-02 10:24:37,488 [mcmc] - Updated covariance matrix of proposal pdf.
2023-07-02 10:24:37,488 [mcmc] array([[0.01198289]])
2023-07-02 10:24:37,498 [mcmc] Dumped checkpoint and progress info, and current covmat.
2023-07-02 10:24:37,498 [model] Posterior to be computed for parameters {'Omega_m': 0.32061509034429425}
2023-07-02 10:24:37,499 [prior] Evaluating prior at array([0.32061509])
2023-07-02 10:24:37,499 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:37,499 [model] Got input parameters: {'Omega_m': 0.32061509034429425, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:37,499 [classy] Got parameters {'Omega_m': 0.32061509034429425, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:37,499 [classy] Computing new state
2023-07-02 10:24:37,499 [classy] Setting parameters: {'Omega_m': 0.32061509034429425, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:37,547 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.2929013008537}
2023-07-02 10:24:37,547 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:37,549 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00417566
2023-07-02 10:24:37,549 [model] Computed derived parameters: {}
2023-07-02 10:24:37,549 [mcmc] New sample, #281:
Omega_m:0.4183757
2023-07-02 10:24:37,549 [model] Posterior to be computed for parameters {'Omega_m': 0.2814372444660057}
2023-07-02 10:24:37,549 [prior] Evaluating prior at array([0.28143724])
2023-07-02 10:24:37,549 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:37,549 [model] Got input parameters: {'Omega_m': 0.2814372444660057, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:37,549 [classy] Got parameters {'Omega_m': 0.2814372444660057, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:37,549 [classy] Computing new state
2023-07-02 10:24:37,549 [classy] Setting parameters: {'Omega_m': 0.2814372444660057, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:37,596 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.16970546432626}
2023-07-02 10:24:37,596 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:37,597 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0642104
2023-07-02 10:24:37,597 [model] Computed derived parameters: {}
2023-07-02 10:24:37,598 [mcmc] New sample, #282:
Omega_m:0.3206151
2023-07-02 10:24:37,598 [model] Posterior to be computed for parameters {'Omega_m': 0.7075316313666231}
2023-07-02 10:24:37,598 [prior] Evaluating prior at array([0.70753163])
2023-07-02 10:24:37,598 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:37,598 [model] Got input parameters: {'Omega_m': 0.7075316313666231, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:37,598 [classy] Got parameters {'Omega_m': 0.7075316313666231, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:37,598 [classy] Computing new state
2023-07-02 10:24:37,598 [classy] Setting parameters: {'Omega_m': 0.7075316313666231, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:37,643 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 115.98792193242247}
2023-07-02 10:24:37,643 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:37,645 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.5868
2023-07-02 10:24:37,645 [model] Computed derived parameters: {}
2023-07-02 10:24:37,645 [model] Posterior to be computed for parameters {'Omega_m': 0.7393211057965723}
2023-07-02 10:24:37,645 [prior] Evaluating prior at array([0.73932111])
2023-07-02 10:24:37,645 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:37,645 [model] Got input parameters: {'Omega_m': 0.7393211057965723, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:37,645 [classy] Got parameters {'Omega_m': 0.7393211057965723, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:37,645 [classy] Computing new state
2023-07-02 10:24:37,645 [classy] Setting parameters: {'Omega_m': 0.7393211057965723, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:37,692 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 114.32441398789165}
2023-07-02 10:24:37,692 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:37,693 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.11899
2023-07-02 10:24:37,694 [model] Computed derived parameters: {}
2023-07-02 10:24:37,694 [model] Posterior to be computed for parameters {'Omega_m': 0.27659985427874534}
2023-07-02 10:24:37,694 [prior] Evaluating prior at array([0.27659985])
2023-07-02 10:24:37,694 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:37,694 [model] Got input parameters: {'Omega_m': 0.27659985427874534, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:37,694 [classy] Got parameters {'Omega_m': 0.27659985427874534, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:37,694 [classy] Computing new state
2023-07-02 10:24:37,694 [classy] Setting parameters: {'Omega_m': 0.27659985427874534, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:37,741 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.81219843119393}
2023-07-02 10:24:37,741 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:37,743 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0868177
2023-07-02 10:24:37,743 [model] Computed derived parameters: {}
2023-07-02 10:24:37,743 [mcmc] New sample, #283:
Omega_m:0.2814372
2023-07-02 10:24:37,743 [model] Posterior to be computed for parameters {'Omega_m': 0.5462979332988132}
2023-07-02 10:24:37,743 [prior] Evaluating prior at array([0.54629793])
2023-07-02 10:24:37,743 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:37,743 [model] Got input parameters: {'Omega_m': 0.5462979332988132, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:37,743 [classy] Got parameters {'Omega_m': 0.5462979332988132, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:37,743 [classy] Computing new state
2023-07-02 10:24:37,743 [classy] Setting parameters: {'Omega_m': 0.5462979332988132, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:37,791 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 125.87710226921777}
2023-07-02 10:24:37,791 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:37,793 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.0713
2023-07-02 10:24:37,793 [model] Computed derived parameters: {}
2023-07-02 10:24:37,793 [model] Posterior to be computed for parameters {'Omega_m': 0.03217486685824211}
2023-07-02 10:24:37,793 [prior] Evaluating prior at array([0.03217487])
2023-07-02 10:24:37,793 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:37,793 [model] Posterior to be computed for parameters {'Omega_m': 0.4691759196098264}
2023-07-02 10:24:37,793 [prior] Evaluating prior at array([0.46917592])
2023-07-02 10:24:37,793 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:37,793 [model] Got input parameters: {'Omega_m': 0.4691759196098264, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:37,793 [classy] Got parameters {'Omega_m': 0.4691759196098264, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:37,793 [classy] Computing new state
2023-07-02 10:24:37,793 [classy] Setting parameters: {'Omega_m': 0.4691759196098264, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:37,841 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 131.73782438788174}
2023-07-02 10:24:37,841 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:37,842 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.07058
2023-07-02 10:24:37,842 [model] Computed derived parameters: {}
2023-07-02 10:24:37,843 [model] Posterior to be computed for parameters {'Omega_m': 0.23881576113396713}
2023-07-02 10:24:37,843 [prior] Evaluating prior at array([0.23881576])
2023-07-02 10:24:37,843 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:37,843 [model] Got input parameters: {'Omega_m': 0.23881576113396713, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:37,843 [classy] Got parameters {'Omega_m': 0.23881576113396713, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:37,843 [classy] Computing new state
2023-07-02 10:24:37,843 [classy] Setting parameters: {'Omega_m': 0.23881576113396713, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:37,890 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 157.18507699064207}
2023-07-02 10:24:37,890 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:37,892 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.40578
2023-07-02 10:24:37,892 [model] Computed derived parameters: {}
2023-07-02 10:24:37,892 [mcmc] New sample, #284:
Omega_m:0.2765999
2023-07-02 10:24:37,892 [model] Posterior to be computed for parameters {'Omega_m': 0.06443702284386527}
2023-07-02 10:24:37,892 [prior] Evaluating prior at array([0.06443702])
2023-07-02 10:24:37,892 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:37,892 [model] Posterior to be computed for parameters {'Omega_m': 0.39023119070878287}
2023-07-02 10:24:37,893 [prior] Evaluating prior at array([0.39023119])
2023-07-02 10:24:37,893 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:37,893 [model] Got input parameters: {'Omega_m': 0.39023119070878287, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:37,893 [classy] Got parameters {'Omega_m': 0.39023119070878287, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:37,893 [classy] Computing new state
2023-07-02 10:24:37,893 [classy] Setting parameters: {'Omega_m': 0.39023119070878287, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:37,939 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 138.8192961169284}
2023-07-02 10:24:37,939 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:37,941 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.309708
2023-07-02 10:24:37,941 [model] Computed derived parameters: {}
2023-07-02 10:24:37,941 [mcmc] New sample, #285:
Omega_m:0.2388158
2023-07-02 10:24:37,941 [model] Posterior to be computed for parameters {'Omega_m': 0.30913952192418875}
2023-07-02 10:24:37,941 [prior] Evaluating prior at array([0.30913952])
2023-07-02 10:24:37,942 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:37,942 [model] Got input parameters: {'Omega_m': 0.30913952192418875, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:37,942 [classy] Got parameters {'Omega_m': 0.30913952192418875, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:37,942 [classy] Computing new state
2023-07-02 10:24:37,942 [classy] Setting parameters: {'Omega_m': 0.30913952192418875, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:37,989 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.66448628995425}
2023-07-02 10:24:37,989 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:37,991 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000894084
2023-07-02 10:24:37,991 [model] Computed derived parameters: {}
2023-07-02 10:24:37,991 [mcmc] New sample, #286:
Omega_m:0.3902312
2023-07-02 10:24:37,991 [model] Posterior to be computed for parameters {'Omega_m': 0.17658623057298742}
2023-07-02 10:24:37,991 [prior] Evaluating prior at array([0.17658623])
2023-07-02 10:24:37,991 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:37,991 [model] Got input parameters: {'Omega_m': 0.17658623057298742, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:37,991 [classy] Got parameters {'Omega_m': 0.17658623057298742, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:37,991 [classy] Computing new state
2023-07-02 10:24:37,991 [classy] Setting parameters: {'Omega_m': 0.17658623057298742, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:38,038 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 167.73787840239098}
2023-07-02 10:24:38,038 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:38,040 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.67813
2023-07-02 10:24:38,040 [model] Computed derived parameters: {}
2023-07-02 10:24:38,040 [model] Posterior to be computed for parameters {'Omega_m': 0.4859688854980242}
2023-07-02 10:24:38,040 [prior] Evaluating prior at array([0.48596889])
2023-07-02 10:24:38,041 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:38,041 [model] Got input parameters: {'Omega_m': 0.4859688854980242, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:38,041 [classy] Got parameters {'Omega_m': 0.4859688854980242, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:38,041 [classy] Computing new state
2023-07-02 10:24:38,041 [classy] Setting parameters: {'Omega_m': 0.4859688854980242, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:38,089 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.38306535003525}
2023-07-02 10:24:38,089 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:38,091 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.27118
2023-07-02 10:24:38,091 [model] Computed derived parameters: {}
2023-07-02 10:24:38,091 [mcmc] New sample, #287:
Omega_m:0.3091395
2023-07-02 10:24:38,091 [model] Posterior to be computed for parameters {'Omega_m': 0.17387566990582798}
2023-07-02 10:24:38,091 [prior] Evaluating prior at array([0.17387567])
2023-07-02 10:24:38,091 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:38,091 [model] Got input parameters: {'Omega_m': 0.17387566990582798, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:38,091 [classy] Got parameters {'Omega_m': 0.17387566990582798, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:38,091 [classy] Computing new state
2023-07-02 10:24:38,091 [classy] Setting parameters: {'Omega_m': 0.17387566990582798, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:38,139 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 168.25757090640656}
2023-07-02 10:24:38,139 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:38,141 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.76195
2023-07-02 10:24:38,141 [model] Computed derived parameters: {}
2023-07-02 10:24:38,141 [mcmc] New sample, #288:
Omega_m:0.4859689
2023-07-02 10:24:38,141 [model] Posterior to be computed for parameters {'Omega_m': 0.07667602019801659}
2023-07-02 10:24:38,141 [prior] Evaluating prior at array([0.07667602])
2023-07-02 10:24:38,141 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:38,141 [model] Posterior to be computed for parameters {'Omega_m': 0.15926508262501907}
2023-07-02 10:24:38,141 [prior] Evaluating prior at array([0.15926508])
2023-07-02 10:24:38,141 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:38,141 [model] Got input parameters: {'Omega_m': 0.15926508262501907, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:38,141 [classy] Got parameters {'Omega_m': 0.15926508262501907, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:38,141 [classy] Computing new state
2023-07-02 10:24:38,141 [classy] Setting parameters: {'Omega_m': 0.15926508262501907, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:38,187 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 171.1628759371795}
2023-07-02 10:24:38,187 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:38,189 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.26582
2023-07-02 10:24:38,189 [model] Computed derived parameters: {}
2023-07-02 10:24:38,189 [model] Posterior to be computed for parameters {'Omega_m': 0.27237560224794655}
2023-07-02 10:24:38,189 [prior] Evaluating prior at array([0.2723756])
2023-07-02 10:24:38,190 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:38,190 [model] Got input parameters: {'Omega_m': 0.27237560224794655, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:38,190 [classy] Got parameters {'Omega_m': 0.27237560224794655, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:38,190 [classy] Computing new state
2023-07-02 10:24:38,190 [classy] Setting parameters: {'Omega_m': 0.27237560224794655, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:38,237 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.38113024440835}
2023-07-02 10:24:38,237 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:38,239 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.109643
2023-07-02 10:24:38,239 [model] Computed derived parameters: {}
2023-07-02 10:24:38,239 [mcmc] New sample, #289:
Omega_m:0.1738757
2023-07-02 10:24:38,239 [model] Posterior to be computed for parameters {'Omega_m': -0.13460393122207392}
2023-07-02 10:24:38,239 [prior] Evaluating prior at array([-0.13460393])
2023-07-02 10:24:38,239 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:38,240 [model] Posterior to be computed for parameters {'Omega_m': 0.503531186892616}
2023-07-02 10:24:38,240 [prior] Evaluating prior at array([0.50353119])
2023-07-02 10:24:38,240 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:38,240 [model] Got input parameters: {'Omega_m': 0.503531186892616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:38,240 [classy] Got parameters {'Omega_m': 0.503531186892616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:38,240 [classy] Computing new state
2023-07-02 10:24:38,240 [classy] Setting parameters: {'Omega_m': 0.503531186892616, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:38,287 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 129.01542106490226}
2023-07-02 10:24:38,287 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:38,289 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.49222
2023-07-02 10:24:38,289 [model] Computed derived parameters: {}
2023-07-02 10:24:38,289 [mcmc] New sample, #290:
Omega_m:0.2723756
2023-07-02 10:24:38,289 [model] Posterior to be computed for parameters {'Omega_m': 0.05085529592609095}
2023-07-02 10:24:38,289 [prior] Evaluating prior at array([0.0508553])
2023-07-02 10:24:38,289 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:38,290 [model] Posterior to be computed for parameters {'Omega_m': 0.2872807327584223}
2023-07-02 10:24:38,290 [prior] Evaluating prior at array([0.28728073])
2023-07-02 10:24:38,290 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:38,290 [model] Got input parameters: {'Omega_m': 0.2872807327584223, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:38,290 [classy] Got parameters {'Omega_m': 0.2872807327584223, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:38,290 [classy] Computing new state
2023-07-02 10:24:38,290 [classy] Setting parameters: {'Omega_m': 0.2872807327584223, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:38,336 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.40608732854608}
2023-07-02 10:24:38,336 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:38,338 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0417386
2023-07-02 10:24:38,338 [model] Computed derived parameters: {}
2023-07-02 10:24:38,338 [mcmc] New sample, #291:
Omega_m:0.5035312
2023-07-02 10:24:38,338 [model] Posterior to be computed for parameters {'Omega_m': 0.027879423884548837}
2023-07-02 10:24:38,338 [prior] Evaluating prior at array([0.02787942])
2023-07-02 10:24:38,339 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:38,339 [model] Posterior to be computed for parameters {'Omega_m': 0.10582772645420122}
2023-07-02 10:24:38,339 [prior] Evaluating prior at array([0.10582773])
2023-07-02 10:24:38,339 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:38,339 [model] Got input parameters: {'Omega_m': 0.10582772645420122, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:38,339 [classy] Got parameters {'Omega_m': 0.10582772645420122, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:38,339 [classy] Computing new state
2023-07-02 10:24:38,339 [classy] Setting parameters: {'Omega_m': 0.10582772645420122, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:38,385 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 183.60702231955432}
2023-07-02 10:24:38,385 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:38,387 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.07388
2023-07-02 10:24:38,387 [model] Computed derived parameters: {}
2023-07-02 10:24:38,387 [model] Posterior to be computed for parameters {'Omega_m': 0.5871076584549306}
2023-07-02 10:24:38,387 [prior] Evaluating prior at array([0.58710766])
2023-07-02 10:24:38,387 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:38,387 [model] Got input parameters: {'Omega_m': 0.5871076584549306, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:38,388 [classy] Got parameters {'Omega_m': 0.5871076584549306, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:38,388 [classy] Computing new state
2023-07-02 10:24:38,388 [classy] Setting parameters: {'Omega_m': 0.5871076584549306, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:38,435 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 123.10911559999538}
2023-07-02 10:24:38,435 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:38,436 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.66734
2023-07-02 10:24:38,436 [model] Computed derived parameters: {}
2023-07-02 10:24:38,436 [model] Posterior to be computed for parameters {'Omega_m': 0.5645305569812454}
2023-07-02 10:24:38,437 [prior] Evaluating prior at array([0.56453056])
2023-07-02 10:24:38,437 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:38,437 [model] Got input parameters: {'Omega_m': 0.5645305569812454, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:38,437 [classy] Got parameters {'Omega_m': 0.5645305569812454, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:38,437 [classy] Computing new state
2023-07-02 10:24:38,437 [classy] Setting parameters: {'Omega_m': 0.5645305569812454, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:38,483 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 124.61488948483871}
2023-07-02 10:24:38,483 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:38,485 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.33302
2023-07-02 10:24:38,485 [model] Computed derived parameters: {}
2023-07-02 10:24:38,485 [model] Posterior to be computed for parameters {'Omega_m': -0.10974533983213058}
2023-07-02 10:24:38,485 [prior] Evaluating prior at array([-0.10974534])
2023-07-02 10:24:38,485 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:38,485 [model] Posterior to be computed for parameters {'Omega_m': 0.20663883119354082}
2023-07-02 10:24:38,485 [prior] Evaluating prior at array([0.20663883])
2023-07-02 10:24:38,485 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:38,485 [model] Got input parameters: {'Omega_m': 0.20663883119354082, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:38,485 [classy] Got parameters {'Omega_m': 0.20663883119354082, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:38,485 [classy] Computing new state
2023-07-02 10:24:38,485 [classy] Setting parameters: {'Omega_m': 0.20663883119354082, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:38,532 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 162.3359893495993}
2023-07-02 10:24:38,533 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:38,534 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.922885
2023-07-02 10:24:38,534 [model] Computed derived parameters: {}
2023-07-02 10:24:38,534 [model] Posterior to be computed for parameters {'Omega_m': 0.18633835346579897}
2023-07-02 10:24:38,534 [prior] Evaluating prior at array([0.18633835])
2023-07-02 10:24:38,535 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:38,535 [model] Got input parameters: {'Omega_m': 0.18633835346579897, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:38,535 [classy] Got parameters {'Omega_m': 0.18633835346579897, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:38,535 [classy] Computing new state
2023-07-02 10:24:38,535 [classy] Setting parameters: {'Omega_m': 0.18633835346579897, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:38,580 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 165.91465817579618}
2023-07-02 10:24:38,580 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:38,583 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.39941
2023-07-02 10:24:38,583 [model] Computed derived parameters: {}
2023-07-02 10:24:38,583 [mcmc] New sample, #292:
Omega_m:0.2872807
2023-07-02 10:24:38,583 [model] Posterior to be computed for parameters {'Omega_m': -0.5938498460052375}
2023-07-02 10:24:38,583 [prior] Evaluating prior at array([-0.59384985])
2023-07-02 10:24:38,583 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:38,583 [model] Posterior to be computed for parameters {'Omega_m': -0.04210819313575659}
2023-07-02 10:24:38,583 [prior] Evaluating prior at array([-0.04210819])
2023-07-02 10:24:38,583 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:38,583 [model] Posterior to be computed for parameters {'Omega_m': -0.03164510637978149}
2023-07-02 10:24:38,583 [prior] Evaluating prior at array([-0.03164511])
2023-07-02 10:24:38,583 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:38,583 [model] Posterior to be computed for parameters {'Omega_m': 0.724181102508786}
2023-07-02 10:24:38,583 [prior] Evaluating prior at array([0.7241811])
2023-07-02 10:24:38,583 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:38,584 [model] Got input parameters: {'Omega_m': 0.724181102508786, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:38,584 [classy] Got parameters {'Omega_m': 0.724181102508786, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:38,584 [classy] Computing new state
2023-07-02 10:24:38,584 [classy] Setting parameters: {'Omega_m': 0.724181102508786, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:38,628 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 115.10677125739237}
2023-07-02 10:24:38,629 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:38,630 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.86462
2023-07-02 10:24:38,631 [model] Computed derived parameters: {}
2023-07-02 10:24:38,631 [model] Posterior to be computed for parameters {'Omega_m': 0.07599604528463412}
2023-07-02 10:24:38,631 [prior] Evaluating prior at array([0.07599605])
2023-07-02 10:24:38,631 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:38,631 [model] Posterior to be computed for parameters {'Omega_m': -0.32929697417432446}
2023-07-02 10:24:38,631 [prior] Evaluating prior at array([-0.32929697])
2023-07-02 10:24:38,631 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:38,631 [model] Posterior to be computed for parameters {'Omega_m': 0.17230812171601428}
2023-07-02 10:24:38,631 [prior] Evaluating prior at array([0.17230812])
2023-07-02 10:24:38,631 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:38,631 [model] Got input parameters: {'Omega_m': 0.17230812171601428, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:38,631 [classy] Got parameters {'Omega_m': 0.17230812171601428, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:38,631 [classy] Computing new state
2023-07-02 10:24:38,631 [classy] Setting parameters: {'Omega_m': 0.17230812171601428, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:38,677 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 168.56078738894445}
2023-07-02 10:24:38,677 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:38,679 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.81174
2023-07-02 10:24:38,679 [model] Computed derived parameters: {}
2023-07-02 10:24:38,679 [mcmc] New sample, #293:
Omega_m:0.1863384
2023-07-02 10:24:38,680 [model] Posterior to be computed for parameters {'Omega_m': 0.057573633348445286}
2023-07-02 10:24:38,680 [prior] Evaluating prior at array([0.05757363])
2023-07-02 10:24:38,680 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:38,680 [model] Posterior to be computed for parameters {'Omega_m': 0.48350611170517105}
2023-07-02 10:24:38,680 [prior] Evaluating prior at array([0.48350611])
2023-07-02 10:24:38,680 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:38,680 [model] Got input parameters: {'Omega_m': 0.48350611170517105, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:38,680 [classy] Got parameters {'Omega_m': 0.48350611170517105, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:38,680 [classy] Computing new state
2023-07-02 10:24:38,680 [classy] Setting parameters: {'Omega_m': 0.48350611170517105, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:38,726 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.57880397928434}
2023-07-02 10:24:38,726 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:38,728 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.24107
2023-07-02 10:24:38,728 [model] Computed derived parameters: {}
2023-07-02 10:24:38,728 [mcmc] New sample, #294:
Omega_m:0.1723081
2023-07-02 10:24:38,728 [model] Posterior to be computed for parameters {'Omega_m': -0.10013983779386132}
2023-07-02 10:24:38,728 [prior] Evaluating prior at array([-0.10013984])
2023-07-02 10:24:38,729 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:38,729 [model] Posterior to be computed for parameters {'Omega_m': 0.7470228981307647}
2023-07-02 10:24:38,729 [prior] Evaluating prior at array([0.7470229])
2023-07-02 10:24:38,729 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:38,729 [model] Got input parameters: {'Omega_m': 0.7470228981307647, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:38,729 [classy] Got parameters {'Omega_m': 0.7470228981307647, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:38,729 [classy] Computing new state
2023-07-02 10:24:38,729 [classy] Setting parameters: {'Omega_m': 0.7470228981307647, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:38,773 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 113.93308519913722}
2023-07-02 10:24:38,774 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:38,775 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.24898
2023-07-02 10:24:38,775 [model] Computed derived parameters: {}
2023-07-02 10:24:38,776 [model] Posterior to be computed for parameters {'Omega_m': 0.8250544186251356}
2023-07-02 10:24:38,776 [prior] Evaluating prior at array([0.82505442])
2023-07-02 10:24:38,776 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:38,776 [model] Got input parameters: {'Omega_m': 0.8250544186251356, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:38,776 [classy] Got parameters {'Omega_m': 0.8250544186251356, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:38,776 [classy] Computing new state
2023-07-02 10:24:38,776 [classy] Setting parameters: {'Omega_m': 0.8250544186251356, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:38,821 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 110.20194169158006}
2023-07-02 10:24:38,821 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:38,823 [bao_likelihood.baolikelihood] Computed log-likelihood = -6.58209
2023-07-02 10:24:38,823 [model] Computed derived parameters: {}
2023-07-02 10:24:38,823 [model] Posterior to be computed for parameters {'Omega_m': 0.5840699966216292}
2023-07-02 10:24:38,823 [prior] Evaluating prior at array([0.58407])
2023-07-02 10:24:38,823 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:38,823 [model] Got input parameters: {'Omega_m': 0.5840699966216292, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:38,823 [classy] Got parameters {'Omega_m': 0.5840699966216292, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:38,823 [classy] Computing new state
2023-07-02 10:24:38,823 [classy] Setting parameters: {'Omega_m': 0.5840699966216292, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:38,870 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 123.30817277338203}
2023-07-02 10:24:38,870 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:38,872 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.62175
2023-07-02 10:24:38,872 [model] Computed derived parameters: {}
2023-07-02 10:24:38,873 [model] Posterior to be computed for parameters {'Omega_m': 0.6376665469913265}
2023-07-02 10:24:38,873 [prior] Evaluating prior at array([0.63766655])
2023-07-02 10:24:38,873 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:38,873 [model] Got input parameters: {'Omega_m': 0.6376665469913265, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:38,873 [classy] Got parameters {'Omega_m': 0.6376665469913265, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:38,873 [classy] Computing new state
2023-07-02 10:24:38,873 [classy] Setting parameters: {'Omega_m': 0.6376665469913265, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:38,918 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 119.94596859058557}
2023-07-02 10:24:38,918 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:38,920 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.44973
2023-07-02 10:24:38,920 [model] Computed derived parameters: {}
2023-07-02 10:24:38,920 [model] Posterior to be computed for parameters {'Omega_m': 0.6104768795560938}
2023-07-02 10:24:38,920 [prior] Evaluating prior at array([0.61047688])
2023-07-02 10:24:38,920 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:38,920 [model] Got input parameters: {'Omega_m': 0.6104768795560938, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:38,920 [classy] Got parameters {'Omega_m': 0.6104768795560938, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:38,920 [classy] Computing new state
2023-07-02 10:24:38,920 [classy] Setting parameters: {'Omega_m': 0.6104768795560938, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:38,967 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 121.61283987933217}
2023-07-02 10:24:38,967 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:38,969 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.02376
2023-07-02 10:24:38,969 [model] Computed derived parameters: {}
2023-07-02 10:24:38,969 [model] Posterior to be computed for parameters {'Omega_m': 0.45827036257387266}
2023-07-02 10:24:38,969 [prior] Evaluating prior at array([0.45827036])
2023-07-02 10:24:38,969 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:38,969 [model] Got input parameters: {'Omega_m': 0.45827036257387266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:38,969 [classy] Got parameters {'Omega_m': 0.45827036257387266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:38,969 [classy] Computing new state
2023-07-02 10:24:38,969 [classy] Setting parameters: {'Omega_m': 0.45827036257387266, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:39,016 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 132.64361584242855}
2023-07-02 10:24:39,016 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:39,018 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.946536
2023-07-02 10:24:39,018 [model] Computed derived parameters: {}
2023-07-02 10:24:39,018 [mcmc] New sample, #295:
Omega_m:0.4835061
2023-07-02 10:24:39,018 [model] Posterior to be computed for parameters {'Omega_m': 0.48528512399685175}
2023-07-02 10:24:39,018 [prior] Evaluating prior at array([0.48528512])
2023-07-02 10:24:39,018 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:39,018 [model] Got input parameters: {'Omega_m': 0.48528512399685175, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:39,019 [classy] Got parameters {'Omega_m': 0.48528512399685175, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:39,019 [classy] Computing new state
2023-07-02 10:24:39,019 [classy] Setting parameters: {'Omega_m': 0.48528512399685175, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:39,066 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.43730898027638}
2023-07-02 10:24:39,066 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:39,068 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.2628
2023-07-02 10:24:39,068 [model] Computed derived parameters: {}
2023-07-02 10:24:39,068 [mcmc] New sample, #296:
Omega_m:0.4582704
2023-07-02 10:24:39,068 [model] Posterior to be computed for parameters {'Omega_m': 0.4057883187822118}
2023-07-02 10:24:39,068 [prior] Evaluating prior at array([0.40578832])
2023-07-02 10:24:39,068 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:39,068 [model] Got input parameters: {'Omega_m': 0.4057883187822118, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:39,068 [classy] Got parameters {'Omega_m': 0.4057883187822118, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:39,068 [classy] Computing new state
2023-07-02 10:24:39,069 [classy] Setting parameters: {'Omega_m': 0.4057883187822118, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:39,116 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 137.32058809492378}
2023-07-02 10:24:39,116 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:39,118 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.431374
2023-07-02 10:24:39,118 [model] Computed derived parameters: {}
2023-07-02 10:24:39,118 [mcmc] New sample, #297:
Omega_m:0.4852851
2023-07-02 10:24:39,118 [model] Posterior to be computed for parameters {'Omega_m': 0.16604242385534054}
2023-07-02 10:24:39,118 [prior] Evaluating prior at array([0.16604242])
2023-07-02 10:24:39,118 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:39,118 [model] Got input parameters: {'Omega_m': 0.16604242385534054, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:39,118 [classy] Got parameters {'Omega_m': 0.16604242385534054, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:39,118 [classy] Computing new state
2023-07-02 10:24:39,118 [classy] Setting parameters: {'Omega_m': 0.16604242385534054, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:39,165 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 169.79284201993966}
2023-07-02 10:24:39,165 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:39,167 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.0208
2023-07-02 10:24:39,167 [model] Computed derived parameters: {}
2023-07-02 10:24:39,167 [model] Posterior to be computed for parameters {'Omega_m': 0.5593957097953548}
2023-07-02 10:24:39,167 [prior] Evaluating prior at array([0.55939571])
2023-07-02 10:24:39,167 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:39,167 [model] Got input parameters: {'Omega_m': 0.5593957097953548, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:39,167 [classy] Got parameters {'Omega_m': 0.5593957097953548, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:39,167 [classy] Computing new state
2023-07-02 10:24:39,167 [classy] Setting parameters: {'Omega_m': 0.5593957097953548, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:39,216 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 124.96607877520823}
2023-07-02 10:24:39,216 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:39,218 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.25851
2023-07-02 10:24:39,218 [model] Computed derived parameters: {}
2023-07-02 10:24:39,218 [model] Posterior to be computed for parameters {'Omega_m': 0.7583577408816342}
2023-07-02 10:24:39,218 [prior] Evaluating prior at array([0.75835774])
2023-07-02 10:24:39,218 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:39,218 [model] Got input parameters: {'Omega_m': 0.7583577408816342, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:39,218 [classy] Got parameters {'Omega_m': 0.7583577408816342, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:39,218 [classy] Computing new state
2023-07-02 10:24:39,218 [classy] Setting parameters: {'Omega_m': 0.7583577408816342, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:39,263 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 113.36514974173697}
2023-07-02 10:24:39,263 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:39,265 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.44089
2023-07-02 10:24:39,265 [model] Computed derived parameters: {}
2023-07-02 10:24:39,265 [model] Posterior to be computed for parameters {'Omega_m': 0.6782615181304047}
2023-07-02 10:24:39,265 [prior] Evaluating prior at array([0.67826152])
2023-07-02 10:24:39,265 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:39,265 [model] Got input parameters: {'Omega_m': 0.6782615181304047, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:39,265 [classy] Got parameters {'Omega_m': 0.6782615181304047, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:39,265 [classy] Computing new state
2023-07-02 10:24:39,265 [classy] Setting parameters: {'Omega_m': 0.6782615181304047, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:39,312 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 117.59278847923802}
2023-07-02 10:24:39,312 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:39,314 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.10411
2023-07-02 10:24:39,314 [model] Computed derived parameters: {}
2023-07-02 10:24:39,314 [model] Posterior to be computed for parameters {'Omega_m': 0.6705787031509105}
2023-07-02 10:24:39,314 [prior] Evaluating prior at array([0.6705787])
2023-07-02 10:24:39,314 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:39,314 [model] Got input parameters: {'Omega_m': 0.6705787031509105, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:39,314 [classy] Got parameters {'Omega_m': 0.6705787031509105, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:39,314 [classy] Computing new state
2023-07-02 10:24:39,314 [classy] Setting parameters: {'Omega_m': 0.6705787031509105, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:39,361 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 118.02638772536578}
2023-07-02 10:24:39,361 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:39,363 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.9788
2023-07-02 10:24:39,363 [model] Computed derived parameters: {}
2023-07-02 10:24:39,363 [mcmc] New sample, #298:
Omega_m:0.4057883
2023-07-02 10:24:39,363 [model] Posterior to be computed for parameters {'Omega_m': 0.4858340744164399}
2023-07-02 10:24:39,363 [prior] Evaluating prior at array([0.48583407])
2023-07-02 10:24:39,363 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:39,363 [model] Got input parameters: {'Omega_m': 0.4858340744164399, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:39,363 [classy] Got parameters {'Omega_m': 0.4858340744164399, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:39,363 [classy] Computing new state
2023-07-02 10:24:39,363 [classy] Setting parameters: {'Omega_m': 0.4858340744164399, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:39,412 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.3937533647381}
2023-07-02 10:24:39,412 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:39,414 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.26953
2023-07-02 10:24:39,414 [model] Computed derived parameters: {}
2023-07-02 10:24:39,414 [mcmc] New sample, #299:
Omega_m:0.6705787
2023-07-02 10:24:39,414 [model] Posterior to be computed for parameters {'Omega_m': 0.2531899447351358}
2023-07-02 10:24:39,414 [prior] Evaluating prior at array([0.25318994])
2023-07-02 10:24:39,414 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:39,414 [model] Got input parameters: {'Omega_m': 0.2531899447351358, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:39,414 [classy] Got parameters {'Omega_m': 0.2531899447351358, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:39,414 [classy] Computing new state
2023-07-02 10:24:39,414 [classy] Setting parameters: {'Omega_m': 0.2531899447351358, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:39,462 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 155.0629567179264}
2023-07-02 10:24:39,462 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:39,464 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.252371
2023-07-02 10:24:39,464 [model] Computed derived parameters: {}
2023-07-02 10:24:39,464 [mcmc] New sample, #300:
Omega_m:0.4858341
2023-07-02 10:24:39,464 [model] Posterior to be computed for parameters {'Omega_m': 0.4099408498356112}
2023-07-02 10:24:39,464 [prior] Evaluating prior at array([0.40994085])
2023-07-02 10:24:39,465 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:39,465 [model] Got input parameters: {'Omega_m': 0.4099408498356112, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:39,465 [classy] Got parameters {'Omega_m': 0.4099408498356112, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:39,465 [classy] Computing new state
2023-07-02 10:24:39,465 [classy] Setting parameters: {'Omega_m': 0.4099408498356112, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:39,512 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 136.92981421293112}
2023-07-02 10:24:39,512 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:39,514 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.466512
2023-07-02 10:24:39,514 [model] Computed derived parameters: {}
2023-07-02 10:24:39,514 [mcmc] New sample, #301:
Omega_m:0.2531899
2023-07-02 10:24:39,514 [model] Posterior to be computed for parameters {'Omega_m': 0.5328267218175338}
2023-07-02 10:24:39,515 [prior] Evaluating prior at array([0.53282672])
2023-07-02 10:24:39,515 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:39,515 [model] Got input parameters: {'Omega_m': 0.5328267218175338, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:39,515 [classy] Got parameters {'Omega_m': 0.5328267218175338, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:39,515 [classy] Computing new state
2023-07-02 10:24:39,515 [classy] Setting parameters: {'Omega_m': 0.5328267218175338, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:39,563 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 126.83782411719453}
2023-07-02 10:24:39,563 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:39,564 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.88326
2023-07-02 10:24:39,564 [model] Computed derived parameters: {}
2023-07-02 10:24:39,565 [model] Posterior to be computed for parameters {'Omega_m': 1.55811726978832}
2023-07-02 10:24:39,565 [prior] Evaluating prior at array([1.55811727])
2023-07-02 10:24:39,565 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:39,565 [model] Posterior to be computed for parameters {'Omega_m': 0.6937925627855914}
2023-07-02 10:24:39,565 [prior] Evaluating prior at array([0.69379256])
2023-07-02 10:24:39,565 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:39,565 [model] Got input parameters: {'Omega_m': 0.6937925627855914, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:39,565 [classy] Got parameters {'Omega_m': 0.6937925627855914, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:39,565 [classy] Computing new state
2023-07-02 10:24:39,565 [classy] Setting parameters: {'Omega_m': 0.6937925627855914, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:39,617 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 116.73214297289047}
2023-07-02 10:24:39,617 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:39,619 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.35924
2023-07-02 10:24:39,619 [model] Computed derived parameters: {}
2023-07-02 10:24:39,619 [model] Posterior to be computed for parameters {'Omega_m': 0.3621397397118498}
2023-07-02 10:24:39,619 [prior] Evaluating prior at array([0.36213974])
2023-07-02 10:24:39,619 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:39,619 [model] Got input parameters: {'Omega_m': 0.3621397397118498, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:39,619 [classy] Got parameters {'Omega_m': 0.3621397397118498, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:39,619 [classy] Computing new state
2023-07-02 10:24:39,619 [classy] Setting parameters: {'Omega_m': 0.3621397397118498, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:39,673 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.67419633070068}
2023-07-02 10:24:39,673 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:39,675 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.134571
2023-07-02 10:24:39,675 [model] Computed derived parameters: {}
2023-07-02 10:24:39,675 [mcmc] New sample, #302:
Omega_m:0.4099408
2023-07-02 10:24:39,676 [model] Posterior to be computed for parameters {'Omega_m': 0.47847143593505936}
2023-07-02 10:24:39,676 [prior] Evaluating prior at array([0.47847144])
2023-07-02 10:24:39,676 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:39,676 [model] Got input parameters: {'Omega_m': 0.47847143593505936, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:39,676 [classy] Got parameters {'Omega_m': 0.47847143593505936, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:39,676 [classy] Computing new state
2023-07-02 10:24:39,676 [classy] Setting parameters: {'Omega_m': 0.47847143593505936, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:39,737 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.98205413082408}
2023-07-02 10:24:39,737 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:39,739 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.18025
2023-07-02 10:24:39,740 [model] Computed derived parameters: {}
2023-07-02 10:24:39,740 [model] Posterior to be computed for parameters {'Omega_m': 0.6864431494684358}
2023-07-02 10:24:39,740 [prior] Evaluating prior at array([0.68644315])
2023-07-02 10:24:39,740 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:39,740 [model] Got input parameters: {'Omega_m': 0.6864431494684358, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:39,740 [classy] Got parameters {'Omega_m': 0.6864431494684358, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:39,740 [classy] Computing new state
2023-07-02 10:24:39,740 [classy] Setting parameters: {'Omega_m': 0.6864431494684358, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:39,804 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 117.13677637096387}
2023-07-02 10:24:39,804 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:39,807 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.23823
2023-07-02 10:24:39,807 [model] Computed derived parameters: {}
2023-07-02 10:24:39,807 [model] Posterior to be computed for parameters {'Omega_m': 0.7014947726716416}
2023-07-02 10:24:39,807 [prior] Evaluating prior at array([0.70149477])
2023-07-02 10:24:39,807 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:39,807 [model] Got input parameters: {'Omega_m': 0.7014947726716416, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:39,807 [classy] Got parameters {'Omega_m': 0.7014947726716416, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:39,807 [classy] Computing new state
2023-07-02 10:24:39,807 [classy] Setting parameters: {'Omega_m': 0.7014947726716416, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:39,852 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 116.31299381869772}
2023-07-02 10:24:39,852 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:39,854 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.48661
2023-07-02 10:24:39,854 [model] Computed derived parameters: {}
2023-07-02 10:24:39,854 [model] Posterior to be computed for parameters {'Omega_m': 0.2562494637555342}
2023-07-02 10:24:39,854 [prior] Evaluating prior at array([0.25624946])
2023-07-02 10:24:39,854 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:39,854 [model] Got input parameters: {'Omega_m': 0.2562494637555342, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:39,854 [classy] Got parameters {'Omega_m': 0.2562494637555342, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:39,854 [classy] Computing new state
2023-07-02 10:24:39,854 [classy] Setting parameters: {'Omega_m': 0.2562494637555342, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:39,901 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 154.6241258821991}
2023-07-02 10:24:39,901 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:39,903 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.22508
2023-07-02 10:24:39,903 [model] Computed derived parameters: {}
2023-07-02 10:24:39,903 [mcmc] New sample, #303:
Omega_m:0.3621397
2023-07-02 10:24:39,903 [model] Posterior to be computed for parameters {'Omega_m': 0.3059597854037749}
2023-07-02 10:24:39,903 [prior] Evaluating prior at array([0.30595979])
2023-07-02 10:24:39,903 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:39,903 [model] Got input parameters: {'Omega_m': 0.3059597854037749, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:39,903 [classy] Got parameters {'Omega_m': 0.3059597854037749, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:39,903 [classy] Computing new state
2023-07-02 10:24:39,903 [classy] Setting parameters: {'Omega_m': 0.3059597854037749, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:39,948 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.05252228167572}
2023-07-02 10:24:39,948 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:39,951 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00285562
2023-07-02 10:24:39,951 [model] Computed derived parameters: {}
2023-07-02 10:24:39,951 [mcmc] New sample, #304:
Omega_m:0.2562495
2023-07-02 10:24:39,952 [model] Posterior to be computed for parameters {'Omega_m': -0.38169801093279976}
2023-07-02 10:24:39,952 [prior] Evaluating prior at array([-0.38169801])
2023-07-02 10:24:39,952 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:39,952 [model] Posterior to be computed for parameters {'Omega_m': 0.18361833517733994}
2023-07-02 10:24:39,952 [prior] Evaluating prior at array([0.18361834])
2023-07-02 10:24:39,952 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:39,952 [model] Got input parameters: {'Omega_m': 0.18361833517733994, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:39,952 [classy] Got parameters {'Omega_m': 0.18361833517733994, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:39,952 [classy] Computing new state
2023-07-02 10:24:39,952 [classy] Setting parameters: {'Omega_m': 0.18361833517733994, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:39,997 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 166.4160000485529}
2023-07-02 10:24:39,997 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:39,999 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.47365
2023-07-02 10:24:39,999 [model] Computed derived parameters: {}
2023-07-02 10:24:40,000 [model] Posterior to be computed for parameters {'Omega_m': 0.30746987369883133}
2023-07-02 10:24:40,000 [prior] Evaluating prior at array([0.30746987])
2023-07-02 10:24:40,000 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:40,000 [model] Got input parameters: {'Omega_m': 0.30746987369883133, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:40,000 [classy] Got parameters {'Omega_m': 0.30746987369883133, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:40,000 [classy] Computing new state
2023-07-02 10:24:40,000 [classy] Setting parameters: {'Omega_m': 0.30746987369883133, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:40,046 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.86779885979414}
2023-07-02 10:24:40,046 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:40,048 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00176361
2023-07-02 10:24:40,048 [model] Computed derived parameters: {}
2023-07-02 10:24:40,048 [mcmc] New sample, #305:
Omega_m:0.3059598
2023-07-02 10:24:40,048 [model] Posterior to be computed for parameters {'Omega_m': 0.2755324105622118}
2023-07-02 10:24:40,048 [prior] Evaluating prior at array([0.27553241])
2023-07-02 10:24:40,048 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:40,048 [model] Got input parameters: {'Omega_m': 0.2755324105622118, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:40,048 [classy] Got parameters {'Omega_m': 0.2755324105622118, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:40,048 [classy] Computing new state
2023-07-02 10:24:40,049 [classy] Setting parameters: {'Omega_m': 0.2755324105622118, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:40,096 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.95526318462245}
2023-07-02 10:24:40,096 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:40,098 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0923099
2023-07-02 10:24:40,098 [model] Computed derived parameters: {}
2023-07-02 10:24:40,098 [mcmc] New sample, #306:
Omega_m:0.3074699
2023-07-02 10:24:40,098 [model] Posterior to be computed for parameters {'Omega_m': -0.21604564226216094}
2023-07-02 10:24:40,098 [prior] Evaluating prior at array([-0.21604564])
2023-07-02 10:24:40,098 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:40,099 [model] Posterior to be computed for parameters {'Omega_m': 0.1200033593418075}
2023-07-02 10:24:40,099 [prior] Evaluating prior at array([0.12000336])
2023-07-02 10:24:40,099 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:40,099 [model] Got input parameters: {'Omega_m': 0.1200033593418075, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:40,099 [classy] Got parameters {'Omega_m': 0.1200033593418075, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:40,099 [classy] Computing new state
2023-07-02 10:24:40,099 [classy] Setting parameters: {'Omega_m': 0.1200033593418075, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:40,146 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 179.98255244615848}
2023-07-02 10:24:40,146 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:40,148 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.15055
2023-07-02 10:24:40,148 [model] Computed derived parameters: {}
2023-07-02 10:24:40,148 [model] Posterior to be computed for parameters {'Omega_m': 0.0982095829799198}
2023-07-02 10:24:40,148 [prior] Evaluating prior at array([0.09820958])
2023-07-02 10:24:40,148 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:40,148 [model] Posterior to be computed for parameters {'Omega_m': 0.445265092707658}
2023-07-02 10:24:40,148 [prior] Evaluating prior at array([0.44526509])
2023-07-02 10:24:40,148 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:40,148 [model] Got input parameters: {'Omega_m': 0.445265092707658, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:40,148 [classy] Got parameters {'Omega_m': 0.445265092707658, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:40,148 [classy] Computing new state
2023-07-02 10:24:40,148 [classy] Setting parameters: {'Omega_m': 0.445265092707658, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:40,196 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 133.75204142069379}
2023-07-02 10:24:40,196 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:40,198 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.805576
2023-07-02 10:24:40,198 [model] Computed derived parameters: {}
2023-07-02 10:24:40,198 [mcmc] New sample, #307:
Omega_m:0.2755324
2023-07-02 10:24:40,198 [model] Posterior to be computed for parameters {'Omega_m': 0.331024982230116}
2023-07-02 10:24:40,198 [prior] Evaluating prior at array([0.33102498])
2023-07-02 10:24:40,199 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:40,199 [model] Got input parameters: {'Omega_m': 0.331024982230116, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:40,199 [classy] Got parameters {'Omega_m': 0.331024982230116, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:40,199 [classy] Computing new state
2023-07-02 10:24:40,199 [classy] Setting parameters: {'Omega_m': 0.331024982230116, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:40,246 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.08612020953476}
2023-07-02 10:24:40,246 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:40,248 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0203483
2023-07-02 10:24:40,248 [model] Computed derived parameters: {}
2023-07-02 10:24:40,248 [mcmc] New sample, #308:
Omega_m:0.4452651
2023-07-02 10:24:40,248 [model] Posterior to be computed for parameters {'Omega_m': 0.451448662841972}
2023-07-02 10:24:40,248 [prior] Evaluating prior at array([0.45144866])
2023-07-02 10:24:40,248 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:40,248 [model] Got input parameters: {'Omega_m': 0.451448662841972, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:40,248 [classy] Got parameters {'Omega_m': 0.451448662841972, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:40,248 [classy] Computing new state
2023-07-02 10:24:40,248 [classy] Setting parameters: {'Omega_m': 0.451448662841972, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:40,295 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 133.2211282049}
2023-07-02 10:24:40,295 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:40,297 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.871608
2023-07-02 10:24:40,297 [model] Computed derived parameters: {}
2023-07-02 10:24:40,297 [model] Posterior to be computed for parameters {'Omega_m': 0.467586821969445}
2023-07-02 10:24:40,297 [prior] Evaluating prior at array([0.46758682])
2023-07-02 10:24:40,297 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:40,297 [model] Got input parameters: {'Omega_m': 0.467586821969445, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:40,297 [classy] Got parameters {'Omega_m': 0.467586821969445, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:40,297 [classy] Computing new state
2023-07-02 10:24:40,297 [classy] Setting parameters: {'Omega_m': 0.467586821969445, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:40,357 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 131.8685137703851}
2023-07-02 10:24:40,357 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:40,360 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.05219
2023-07-02 10:24:40,360 [model] Computed derived parameters: {}
2023-07-02 10:24:40,360 [mcmc] New sample, #309:
Omega_m:0.331025
2023-07-02 10:24:40,361 [model] Posterior to be computed for parameters {'Omega_m': -0.17501906774647458}
2023-07-02 10:24:40,361 [prior] Evaluating prior at array([-0.17501907])
2023-07-02 10:24:40,361 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:40,361 [model] Posterior to be computed for parameters {'Omega_m': 1.0428516599455153}
2023-07-02 10:24:40,361 [prior] Evaluating prior at array([1.04285166])
2023-07-02 10:24:40,361 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:40,361 [model] Posterior to be computed for parameters {'Omega_m': 0.567210580560753}
2023-07-02 10:24:40,361 [prior] Evaluating prior at array([0.56721058])
2023-07-02 10:24:40,361 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:40,361 [model] Got input parameters: {'Omega_m': 0.567210580560753, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:40,362 [classy] Got parameters {'Omega_m': 0.567210580560753, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:40,362 [classy] Computing new state
2023-07-02 10:24:40,362 [classy] Setting parameters: {'Omega_m': 0.567210580560753, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:40,439 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 124.43290208616033}
2023-07-02 10:24:40,439 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:40,442 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.37214
2023-07-02 10:24:40,442 [model] Computed derived parameters: {}
2023-07-02 10:24:40,442 [mcmc] New sample, #310:
Omega_m:0.4675868
2023-07-02 10:24:40,442 [model] Posterior to be computed for parameters {'Omega_m': 0.922418774013628}
2023-07-02 10:24:40,442 [prior] Evaluating prior at array([0.92241877])
2023-07-02 10:24:40,442 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:40,442 [model] Got input parameters: {'Omega_m': 0.922418774013628, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:40,442 [classy] Got parameters {'Omega_m': 0.922418774013628, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:40,442 [classy] Computing new state
2023-07-02 10:24:40,442 [classy] Setting parameters: {'Omega_m': 0.922418774013628, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:40,514 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 106.06250172264066}
2023-07-02 10:24:40,514 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:40,516 [bao_likelihood.baolikelihood] Computed log-likelihood = -8.26704
2023-07-02 10:24:40,517 [model] Computed derived parameters: {}
2023-07-02 10:24:40,517 [model] Posterior to be computed for parameters {'Omega_m': 0.7363846589674309}
2023-07-02 10:24:40,517 [prior] Evaluating prior at array([0.73638466])
2023-07-02 10:24:40,517 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:40,517 [model] Got input parameters: {'Omega_m': 0.7363846589674309, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:40,517 [classy] Got parameters {'Omega_m': 0.7363846589674309, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:40,517 [classy] Computing new state
2023-07-02 10:24:40,517 [classy] Setting parameters: {'Omega_m': 0.7363846589674309, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:40,563 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 114.4747815905536}
2023-07-02 10:24:40,563 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:40,564 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.06953
2023-07-02 10:24:40,564 [model] Computed derived parameters: {}
2023-07-02 10:24:40,565 [model] Posterior to be computed for parameters {'Omega_m': 0.1606649939992048}
2023-07-02 10:24:40,565 [prior] Evaluating prior at array([0.16066499])
2023-07-02 10:24:40,565 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:40,565 [model] Got input parameters: {'Omega_m': 0.1606649939992048, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:40,565 [classy] Got parameters {'Omega_m': 0.1606649939992048, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:40,565 [classy] Computing new state
2023-07-02 10:24:40,565 [classy] Setting parameters: {'Omega_m': 0.1606649939992048, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:40,611 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 170.87658302347833}
2023-07-02 10:24:40,611 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:40,613 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.21353
2023-07-02 10:24:40,614 [model] Computed derived parameters: {}
2023-07-02 10:24:40,614 [mcmc] New sample, #311:
Omega_m:0.5672106
2023-07-02 10:24:40,614 [model] Posterior to be computed for parameters {'Omega_m': -0.6189699658488845}
2023-07-02 10:24:40,614 [prior] Evaluating prior at array([-0.61896997])
2023-07-02 10:24:40,614 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:40,614 [model] Posterior to be computed for parameters {'Omega_m': -0.02835722378142355}
2023-07-02 10:24:40,614 [prior] Evaluating prior at array([-0.02835722])
2023-07-02 10:24:40,614 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:40,614 [model] Posterior to be computed for parameters {'Omega_m': -0.04433577722682486}
2023-07-02 10:24:40,614 [prior] Evaluating prior at array([-0.04433578])
2023-07-02 10:24:40,614 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:40,614 [model] Posterior to be computed for parameters {'Omega_m': -0.20862102119561377}
2023-07-02 10:24:40,614 [prior] Evaluating prior at array([-0.20862102])
2023-07-02 10:24:40,614 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:40,614 [model] Posterior to be computed for parameters {'Omega_m': 0.3971408758050733}
2023-07-02 10:24:40,614 [prior] Evaluating prior at array([0.39714088])
2023-07-02 10:24:40,614 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:40,615 [model] Got input parameters: {'Omega_m': 0.3971408758050733, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:40,615 [classy] Got parameters {'Omega_m': 0.3971408758050733, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:40,615 [classy] Computing new state
2023-07-02 10:24:40,615 [classy] Setting parameters: {'Omega_m': 0.3971408758050733, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:40,660 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 138.1467783404195}
2023-07-02 10:24:40,660 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:40,662 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.361742
2023-07-02 10:24:40,662 [model] Computed derived parameters: {}
2023-07-02 10:24:40,663 [mcmc] New sample, #312:
Omega_m:0.160665
2023-07-02 10:24:40,663 [model] Posterior to be computed for parameters {'Omega_m': 0.24512936960184933}
2023-07-02 10:24:40,663 [prior] Evaluating prior at array([0.24512937])
2023-07-02 10:24:40,663 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:40,663 [model] Got input parameters: {'Omega_m': 0.24512936960184933, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:40,663 [classy] Got parameters {'Omega_m': 0.24512936960184933, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:40,663 [classy] Computing new state
2023-07-02 10:24:40,663 [classy] Setting parameters: {'Omega_m': 0.24512936960184933, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:40,709 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 156.24039065470444}
2023-07-02 10:24:40,709 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:40,710 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.333117
2023-07-02 10:24:40,711 [model] Computed derived parameters: {}
2023-07-02 10:24:40,711 [mcmc] New sample, #313:
Omega_m:0.3971409
2023-07-02 10:24:40,711 [model] Posterior to be computed for parameters {'Omega_m': 0.8949045461365108}
2023-07-02 10:24:40,711 [prior] Evaluating prior at array([0.89490455])
2023-07-02 10:24:40,711 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:40,711 [model] Got input parameters: {'Omega_m': 0.8949045461365108, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:40,711 [classy] Got parameters {'Omega_m': 0.8949045461365108, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:40,711 [classy] Computing new state
2023-07-02 10:24:40,711 [classy] Setting parameters: {'Omega_m': 0.8949045461365108, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:40,756 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 107.18054249600104}
2023-07-02 10:24:40,756 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:40,758 [bao_likelihood.baolikelihood] Computed log-likelihood = -7.78995
2023-07-02 10:24:40,758 [model] Computed derived parameters: {}
2023-07-02 10:24:40,758 [model] Posterior to be computed for parameters {'Omega_m': 0.21592451960562065}
2023-07-02 10:24:40,758 [prior] Evaluating prior at array([0.21592452])
2023-07-02 10:24:40,758 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:40,758 [model] Got input parameters: {'Omega_m': 0.21592451960562065, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:40,758 [classy] Got parameters {'Omega_m': 0.21592451960562065, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:40,758 [classy] Computing new state
2023-07-02 10:24:40,758 [classy] Setting parameters: {'Omega_m': 0.21592451960562065, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:40,804 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 160.7881469150433}
2023-07-02 10:24:40,804 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:40,806 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.74628
2023-07-02 10:24:40,806 [model] Computed derived parameters: {}
2023-07-02 10:24:40,807 [model] Posterior to be computed for parameters {'Omega_m': -0.08285909407276681}
2023-07-02 10:24:40,807 [prior] Evaluating prior at array([-0.08285909])
2023-07-02 10:24:40,807 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:40,807 [model] Posterior to be computed for parameters {'Omega_m': 0.10162962923318036}
2023-07-02 10:24:40,807 [prior] Evaluating prior at array([0.10162963])
2023-07-02 10:24:40,807 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:40,807 [model] Got input parameters: {'Omega_m': 0.10162962923318036, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:40,807 [classy] Got parameters {'Omega_m': 0.10162962923318036, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:40,807 [classy] Computing new state
2023-07-02 10:24:40,807 [classy] Setting parameters: {'Omega_m': 0.10162962923318036, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:40,853 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 184.733553473902}
2023-07-02 10:24:40,853 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:40,855 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.37788
2023-07-02 10:24:40,855 [model] Computed derived parameters: {}
2023-07-02 10:24:40,855 [model] Posterior to be computed for parameters {'Omega_m': 0.29174086979727687}
2023-07-02 10:24:40,855 [prior] Evaluating prior at array([0.29174087])
2023-07-02 10:24:40,855 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:40,855 [model] Got input parameters: {'Omega_m': 0.29174086979727687, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:40,855 [classy] Got parameters {'Omega_m': 0.29174086979727687, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:40,855 [classy] Computing new state
2023-07-02 10:24:40,856 [classy] Setting parameters: {'Omega_m': 0.29174086979727687, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:40,902 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.83226334963538}
2023-07-02 10:24:40,902 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:40,903 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0280144
2023-07-02 10:24:40,903 [model] Computed derived parameters: {}
2023-07-02 10:24:40,904 [mcmc] New sample, #314:
Omega_m:0.2451294
2023-07-02 10:24:40,904 [model] Posterior to be computed for parameters {'Omega_m': -0.11836021496707455}
2023-07-02 10:24:40,904 [prior] Evaluating prior at array([-0.11836021])
2023-07-02 10:24:40,904 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:40,904 [model] Posterior to be computed for parameters {'Omega_m': 0.03883621754101313}
2023-07-02 10:24:40,904 [prior] Evaluating prior at array([0.03883622])
2023-07-02 10:24:40,904 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:40,904 [model] Posterior to be computed for parameters {'Omega_m': 0.0676623855364892}
2023-07-02 10:24:40,904 [prior] Evaluating prior at array([0.06766239])
2023-07-02 10:24:40,904 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:40,904 [model] Posterior to be computed for parameters {'Omega_m': -0.15589147019995037}
2023-07-02 10:24:40,904 [prior] Evaluating prior at array([-0.15589147])
2023-07-02 10:24:40,904 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:40,905 [model] Posterior to be computed for parameters {'Omega_m': 0.26381175231380855}
2023-07-02 10:24:40,905 [prior] Evaluating prior at array([0.26381175])
2023-07-02 10:24:40,905 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:40,905 [model] Got input parameters: {'Omega_m': 0.26381175231380855, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:40,905 [classy] Got parameters {'Omega_m': 0.26381175231380855, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:40,905 [classy] Computing new state
2023-07-02 10:24:40,905 [classy] Setting parameters: {'Omega_m': 0.26381175231380855, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:40,956 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.55795405981857}
2023-07-02 10:24:40,956 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:40,959 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.165173
2023-07-02 10:24:40,959 [model] Computed derived parameters: {}
2023-07-02 10:24:40,959 [mcmc] New sample, #315:
Omega_m:0.2917409
2023-07-02 10:24:40,959 [model] Posterior to be computed for parameters {'Omega_m': 0.062372495751917834}
2023-07-02 10:24:40,959 [prior] Evaluating prior at array([0.0623725])
2023-07-02 10:24:40,959 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:40,960 [model] Posterior to be computed for parameters {'Omega_m': 0.1865817377094908}
2023-07-02 10:24:40,960 [prior] Evaluating prior at array([0.18658174])
2023-07-02 10:24:40,960 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:40,960 [model] Got input parameters: {'Omega_m': 0.1865817377094908, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:40,960 [classy] Got parameters {'Omega_m': 0.1865817377094908, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:40,960 [classy] Computing new state
2023-07-02 10:24:40,960 [classy] Setting parameters: {'Omega_m': 0.1865817377094908, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:41,022 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 165.87006268004328}
2023-07-02 10:24:41,022 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:41,024 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.39289
2023-07-02 10:24:41,024 [model] Computed derived parameters: {}
2023-07-02 10:24:41,024 [model] Posterior to be computed for parameters {'Omega_m': 0.15476450403549796}
2023-07-02 10:24:41,024 [prior] Evaluating prior at array([0.1547645])
2023-07-02 10:24:41,024 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:41,024 [model] Got input parameters: {'Omega_m': 0.15476450403549796, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:41,024 [classy] Got parameters {'Omega_m': 0.15476450403549796, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:41,024 [classy] Computing new state
2023-07-02 10:24:41,024 [classy] Setting parameters: {'Omega_m': 0.15476450403549796, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:41,071 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 172.09515566520267}
2023-07-02 10:24:41,071 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:41,073 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.44005
2023-07-02 10:24:41,073 [model] Computed derived parameters: {}
2023-07-02 10:24:41,073 [model] Posterior to be computed for parameters {'Omega_m': 0.18369946149853744}
2023-07-02 10:24:41,073 [prior] Evaluating prior at array([0.18369946])
2023-07-02 10:24:41,073 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:41,074 [model] Got input parameters: {'Omega_m': 0.18369946149853744, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:41,074 [classy] Got parameters {'Omega_m': 0.18369946149853744, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:41,074 [classy] Computing new state
2023-07-02 10:24:41,074 [classy] Setting parameters: {'Omega_m': 0.18369946149853744, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:41,146 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 166.40096744961411}
2023-07-02 10:24:41,147 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:41,149 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.4714
2023-07-02 10:24:41,149 [model] Computed derived parameters: {}
2023-07-02 10:24:41,149 [mcmc] New sample, #316:
Omega_m:0.2638118
2023-07-02 10:24:41,150 [model] Posterior to be computed for parameters {'Omega_m': -0.19924607467629551}
2023-07-02 10:24:41,150 [prior] Evaluating prior at array([-0.19924607])
2023-07-02 10:24:41,150 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:41,150 [model] Posterior to be computed for parameters {'Omega_m': 0.19656628729433154}
2023-07-02 10:24:41,150 [prior] Evaluating prior at array([0.19656629])
2023-07-02 10:24:41,150 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:41,150 [model] Got input parameters: {'Omega_m': 0.19656628729433154, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:41,150 [classy] Got parameters {'Omega_m': 0.19656628729433154, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:41,150 [classy] Computing new state
2023-07-02 10:24:41,150 [classy] Setting parameters: {'Omega_m': 0.19656628729433154, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:41,224 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 164.0767304131304}
2023-07-02 10:24:41,224 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:41,226 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.14288
2023-07-02 10:24:41,226 [model] Computed derived parameters: {}
2023-07-02 10:24:41,227 [mcmc] New sample, #317:
Omega_m:0.1836995
2023-07-02 10:24:41,227 [model] Posterior to be computed for parameters {'Omega_m': -0.4809132868107351}
2023-07-02 10:24:41,227 [prior] Evaluating prior at array([-0.48091329])
2023-07-02 10:24:41,227 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:41,227 [model] Posterior to be computed for parameters {'Omega_m': 0.2576564773441015}
2023-07-02 10:24:41,227 [prior] Evaluating prior at array([0.25765648])
2023-07-02 10:24:41,227 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:41,227 [model] Got input parameters: {'Omega_m': 0.2576564773441015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:41,227 [classy] Got parameters {'Omega_m': 0.2576564773441015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:41,227 [classy] Computing new state
2023-07-02 10:24:41,227 [classy] Setting parameters: {'Omega_m': 0.2576564773441015, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:41,284 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 154.42377133575974}
2023-07-02 10:24:41,284 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:41,286 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.213129
2023-07-02 10:24:41,286 [model] Computed derived parameters: {}
2023-07-02 10:24:41,286 [mcmc] New sample, #318:
Omega_m:0.1965663
2023-07-02 10:24:41,286 [model] Posterior to be computed for parameters {'Omega_m': 0.2720018851978205}
2023-07-02 10:24:41,286 [prior] Evaluating prior at array([0.27200189])
2023-07-02 10:24:41,287 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:41,287 [model] Got input parameters: {'Omega_m': 0.2720018851978205, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:41,287 [classy] Got parameters {'Omega_m': 0.2720018851978205, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:41,287 [classy] Computing new state
2023-07-02 10:24:41,287 [classy] Setting parameters: {'Omega_m': 0.2720018851978205, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:41,334 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.43182680144588}
2023-07-02 10:24:41,334 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:41,336 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.111805
2023-07-02 10:24:41,336 [model] Computed derived parameters: {}
2023-07-02 10:24:41,336 [mcmc] New sample, #319:
Omega_m:0.2576565
2023-07-02 10:24:41,336 [model] Posterior to be computed for parameters {'Omega_m': 0.2714610695293828}
2023-07-02 10:24:41,336 [prior] Evaluating prior at array([0.27146107])
2023-07-02 10:24:41,336 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:41,336 [model] Got input parameters: {'Omega_m': 0.2714610695293828, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:41,336 [classy] Got parameters {'Omega_m': 0.2714610695293828, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:41,336 [classy] Computing new state
2023-07-02 10:24:41,336 [classy] Setting parameters: {'Omega_m': 0.2714610695293828, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:41,384 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.50530061516912}
2023-07-02 10:24:41,384 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:41,386 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.114974
2023-07-02 10:24:41,386 [model] Computed derived parameters: {}
2023-07-02 10:24:41,386 [mcmc] New sample, #320:
Omega_m:0.2720019
2023-07-02 10:24:41,386 [mcmc] Learn + convergence test @ 320 samples accepted.
2023-07-02 10:24:41,386 [mcmc] Ready to check convergence and learn a new proposal covmat
2023-07-02 10:24:41,392 [mcmc] - Acceptance rate: 0.449
2023-07-02 10:24:41,392 [mcmc] - Condition number = 1
2023-07-02 10:24:41,392 [mcmc] - Eigenvalues = array([0.03899667])
2023-07-02 10:24:41,392 [mcmc] - Convergence of means: R-1 = 0.038997 after 256 accepted steps
2023-07-02 10:24:41,393 [mcmc] - Updated covariance matrix of proposal pdf.
2023-07-02 10:24:41,393 [mcmc] array([[0.01232444]])
2023-07-02 10:24:41,403 [mcmc] Dumped checkpoint and progress info, and current covmat.
2023-07-02 10:24:41,403 [model] Posterior to be computed for parameters {'Omega_m': 0.659893301851026}
2023-07-02 10:24:41,403 [prior] Evaluating prior at array([0.6598933])
2023-07-02 10:24:41,403 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:41,403 [model] Got input parameters: {'Omega_m': 0.659893301851026, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:41,403 [classy] Got parameters {'Omega_m': 0.659893301851026, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:41,403 [classy] Computing new state
2023-07-02 10:24:41,403 [classy] Setting parameters: {'Omega_m': 0.659893301851026, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:41,450 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 118.63837735329697}
2023-07-02 10:24:41,450 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:41,451 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.8056
2023-07-02 10:24:41,452 [model] Computed derived parameters: {}
2023-07-02 10:24:41,452 [model] Posterior to be computed for parameters {'Omega_m': 0.12003370033669022}
2023-07-02 10:24:41,452 [prior] Evaluating prior at array([0.1200337])
2023-07-02 10:24:41,452 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:41,452 [model] Got input parameters: {'Omega_m': 0.12003370033669022, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:41,452 [classy] Got parameters {'Omega_m': 0.12003370033669022, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:41,452 [classy] Computing new state
2023-07-02 10:24:41,452 [classy] Setting parameters: {'Omega_m': 0.12003370033669022, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:41,499 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 179.97507439586272}
2023-07-02 10:24:41,499 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:41,501 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.14873
2023-07-02 10:24:41,501 [model] Computed derived parameters: {}
2023-07-02 10:24:41,501 [model] Posterior to be computed for parameters {'Omega_m': 0.23485902472261655}
2023-07-02 10:24:41,501 [prior] Evaluating prior at array([0.23485902])
2023-07-02 10:24:41,501 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:41,501 [model] Got input parameters: {'Omega_m': 0.23485902472261655, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:41,501 [classy] Got parameters {'Omega_m': 0.23485902472261655, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:41,501 [classy] Computing new state
2023-07-02 10:24:41,501 [classy] Setting parameters: {'Omega_m': 0.23485902472261655, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:41,548 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 157.78747411015152}
2023-07-02 10:24:41,549 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:41,550 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.455745
2023-07-02 10:24:41,550 [model] Computed derived parameters: {}
2023-07-02 10:24:41,550 [mcmc] New sample, #321:
Omega_m:0.2714611
2023-07-02 10:24:41,551 [model] Posterior to be computed for parameters {'Omega_m': 0.502925003606336}
2023-07-02 10:24:41,551 [prior] Evaluating prior at array([0.502925])
2023-07-02 10:24:41,551 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:41,551 [model] Got input parameters: {'Omega_m': 0.502925003606336, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:41,551 [classy] Got parameters {'Omega_m': 0.502925003606336, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:41,551 [classy] Computing new state
2023-07-02 10:24:41,551 [classy] Setting parameters: {'Omega_m': 0.502925003606336, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:41,600 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 129.0618220870738}
2023-07-02 10:24:41,600 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:41,602 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.48441
2023-07-02 10:24:41,602 [model] Computed derived parameters: {}
2023-07-02 10:24:41,602 [mcmc] New sample, #322:
Omega_m:0.234859
2023-07-02 10:24:41,602 [model] Posterior to be computed for parameters {'Omega_m': -0.22981471614532067}
2023-07-02 10:24:41,602 [prior] Evaluating prior at array([-0.22981472])
2023-07-02 10:24:41,602 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:41,602 [model] Posterior to be computed for parameters {'Omega_m': 0.5625522219332272}
2023-07-02 10:24:41,602 [prior] Evaluating prior at array([0.56255222])
2023-07-02 10:24:41,602 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:41,602 [model] Got input parameters: {'Omega_m': 0.5625522219332272, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:41,602 [classy] Got parameters {'Omega_m': 0.5625522219332272, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:41,602 [classy] Computing new state
2023-07-02 10:24:41,602 [classy] Setting parameters: {'Omega_m': 0.5625522219332272, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:41,658 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 124.74980142396824}
2023-07-02 10:24:41,658 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:41,659 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.30424
2023-07-02 10:24:41,660 [model] Computed derived parameters: {}
2023-07-02 10:24:41,660 [mcmc] New sample, #323:
Omega_m:0.502925
2023-07-02 10:24:41,660 [model] Posterior to be computed for parameters {'Omega_m': 1.0815829483668415}
2023-07-02 10:24:41,660 [prior] Evaluating prior at array([1.08158295])
2023-07-02 10:24:41,660 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:41,660 [model] Posterior to be computed for parameters {'Omega_m': 0.039265173032374756}
2023-07-02 10:24:41,660 [prior] Evaluating prior at array([0.03926517])
2023-07-02 10:24:41,660 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:41,660 [model] Posterior to be computed for parameters {'Omega_m': 0.85095382281302}
2023-07-02 10:24:41,660 [prior] Evaluating prior at array([0.85095382])
2023-07-02 10:24:41,660 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:41,660 [model] Got input parameters: {'Omega_m': 0.85095382281302, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:41,660 [classy] Got parameters {'Omega_m': 0.85095382281302, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:41,660 [classy] Computing new state
2023-07-02 10:24:41,660 [classy] Setting parameters: {'Omega_m': 0.85095382281302, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:41,708 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 109.04935049444734}
2023-07-02 10:24:41,708 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:41,710 [bao_likelihood.baolikelihood] Computed log-likelihood = -7.02902
2023-07-02 10:24:41,710 [model] Computed derived parameters: {}
2023-07-02 10:24:41,710 [model] Posterior to be computed for parameters {'Omega_m': -0.2596255748052363}
2023-07-02 10:24:41,710 [prior] Evaluating prior at array([-0.25962557])
2023-07-02 10:24:41,710 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:41,710 [model] Posterior to be computed for parameters {'Omega_m': 0.41983545186371785}
2023-07-02 10:24:41,710 [prior] Evaluating prior at array([0.41983545])
2023-07-02 10:24:41,710 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:41,711 [model] Got input parameters: {'Omega_m': 0.41983545186371785, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:41,711 [classy] Got parameters {'Omega_m': 0.41983545186371785, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:41,711 [classy] Computing new state
2023-07-02 10:24:41,711 [classy] Setting parameters: {'Omega_m': 0.41983545186371785, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:41,758 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 136.01378602502828}
2023-07-02 10:24:41,759 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:41,760 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.554467
2023-07-02 10:24:41,760 [model] Computed derived parameters: {}
2023-07-02 10:24:41,760 [mcmc] New sample, #324:
Omega_m:0.5625522
2023-07-02 10:24:41,760 [model] Posterior to be computed for parameters {'Omega_m': 1.3413127131380616}
2023-07-02 10:24:41,761 [prior] Evaluating prior at array([1.34131271])
2023-07-02 10:24:41,761 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:41,761 [model] Posterior to be computed for parameters {'Omega_m': 0.2133296723061989}
2023-07-02 10:24:41,761 [prior] Evaluating prior at array([0.21332967])
2023-07-02 10:24:41,761 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:41,761 [model] Got input parameters: {'Omega_m': 0.2133296723061989, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:41,761 [classy] Got parameters {'Omega_m': 0.2133296723061989, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:41,761 [classy] Computing new state
2023-07-02 10:24:41,761 [classy] Setting parameters: {'Omega_m': 0.2133296723061989, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:41,809 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 161.21539951461514}
2023-07-02 10:24:41,809 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:41,811 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.793227
2023-07-02 10:24:41,811 [model] Computed derived parameters: {}
2023-07-02 10:24:41,811 [mcmc] New sample, #325:
Omega_m:0.4198355
2023-07-02 10:24:41,811 [model] Posterior to be computed for parameters {'Omega_m': 0.7406859858846916}
2023-07-02 10:24:41,811 [prior] Evaluating prior at array([0.74068599])
2023-07-02 10:24:41,811 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:41,811 [model] Got input parameters: {'Omega_m': 0.7406859858846916, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:41,811 [classy] Got parameters {'Omega_m': 0.7406859858846916, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:41,811 [classy] Computing new state
2023-07-02 10:24:41,811 [classy] Setting parameters: {'Omega_m': 0.7406859858846916, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:41,858 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 114.2547403285463}
2023-07-02 10:24:41,858 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:41,860 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.142
2023-07-02 10:24:41,860 [model] Computed derived parameters: {}
2023-07-02 10:24:41,860 [model] Posterior to be computed for parameters {'Omega_m': -0.23294378682238262}
2023-07-02 10:24:41,860 [prior] Evaluating prior at array([-0.23294379])
2023-07-02 10:24:41,860 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:41,860 [model] Posterior to be computed for parameters {'Omega_m': 0.1363389763377238}
2023-07-02 10:24:41,860 [prior] Evaluating prior at array([0.13633898])
2023-07-02 10:24:41,860 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:41,860 [model] Got input parameters: {'Omega_m': 0.1363389763377238, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:41,861 [classy] Got parameters {'Omega_m': 0.1363389763377238, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:41,861 [classy] Computing new state
2023-07-02 10:24:41,861 [classy] Setting parameters: {'Omega_m': 0.1363389763377238, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:41,907 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 176.11461380527712}
2023-07-02 10:24:41,907 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:41,909 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.25956
2023-07-02 10:24:41,909 [model] Computed derived parameters: {}
2023-07-02 10:24:41,909 [model] Posterior to be computed for parameters {'Omega_m': 0.2771853565994251}
2023-07-02 10:24:41,909 [prior] Evaluating prior at array([0.27718536])
2023-07-02 10:24:41,909 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:41,909 [model] Got input parameters: {'Omega_m': 0.2771853565994251, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:41,909 [classy] Got parameters {'Omega_m': 0.2771853565994251, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:41,909 [classy] Computing new state
2023-07-02 10:24:41,909 [classy] Setting parameters: {'Omega_m': 0.2771853565994251, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:41,956 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.7339272146062}
2023-07-02 10:24:41,956 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:41,958 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0838835
2023-07-02 10:24:41,958 [model] Computed derived parameters: {}
2023-07-02 10:24:41,958 [mcmc] New sample, #326:
Omega_m:0.2133297
2023-07-02 10:24:41,958 [model] Posterior to be computed for parameters {'Omega_m': 0.40344838407467504}
2023-07-02 10:24:41,958 [prior] Evaluating prior at array([0.40344838])
2023-07-02 10:24:41,958 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:41,958 [model] Got input parameters: {'Omega_m': 0.40344838407467504, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:41,958 [classy] Got parameters {'Omega_m': 0.40344838407467504, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:41,958 [classy] Computing new state
2023-07-02 10:24:41,959 [classy] Setting parameters: {'Omega_m': 0.40344838407467504, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:42,006 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 137.5424875303604}
2023-07-02 10:24:42,006 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:42,008 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.412051
2023-07-02 10:24:42,008 [model] Computed derived parameters: {}
2023-07-02 10:24:42,008 [model] Posterior to be computed for parameters {'Omega_m': 0.4830273517219622}
2023-07-02 10:24:42,008 [prior] Evaluating prior at array([0.48302735])
2023-07-02 10:24:42,008 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:42,008 [model] Got input parameters: {'Omega_m': 0.4830273517219622, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:42,008 [classy] Got parameters {'Omega_m': 0.4830273517219622, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:42,009 [classy] Computing new state
2023-07-02 10:24:42,009 [classy] Setting parameters: {'Omega_m': 0.4830273517219622, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:42,060 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.6169699300859}
2023-07-02 10:24:42,060 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:42,062 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.23525
2023-07-02 10:24:42,062 [model] Computed derived parameters: {}
2023-07-02 10:24:42,062 [model] Posterior to be computed for parameters {'Omega_m': 0.29692556175969914}
2023-07-02 10:24:42,062 [prior] Evaluating prior at array([0.29692556])
2023-07-02 10:24:42,062 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:42,062 [model] Got input parameters: {'Omega_m': 0.29692556175969914, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:42,062 [classy] Got parameters {'Omega_m': 0.29692556175969914, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:42,062 [classy] Computing new state
2023-07-02 10:24:42,062 [classy] Setting parameters: {'Omega_m': 0.29692556175969914, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:42,111 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.1746903964477}
2023-07-02 10:24:42,111 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:42,113 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.015641
2023-07-02 10:24:42,113 [model] Computed derived parameters: {}
2023-07-02 10:24:42,113 [mcmc] New sample, #327:
Omega_m:0.2771854
2023-07-02 10:24:42,113 [model] Posterior to be computed for parameters {'Omega_m': 0.14384592363078158}
2023-07-02 10:24:42,114 [prior] Evaluating prior at array([0.14384592])
2023-07-02 10:24:42,114 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:42,114 [model] Got input parameters: {'Omega_m': 0.14384592363078158, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:42,114 [classy] Got parameters {'Omega_m': 0.14384592363078158, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:42,114 [classy] Computing new state
2023-07-02 10:24:42,114 [classy] Setting parameters: {'Omega_m': 0.14384592363078158, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:42,162 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 174.43598937014045}
2023-07-02 10:24:42,162 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:42,163 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.90394
2023-07-02 10:24:42,164 [model] Computed derived parameters: {}
2023-07-02 10:24:42,164 [model] Posterior to be computed for parameters {'Omega_m': 0.3735843911966811}
2023-07-02 10:24:42,164 [prior] Evaluating prior at array([0.37358439])
2023-07-02 10:24:42,164 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:42,164 [model] Got input parameters: {'Omega_m': 0.3735843911966811, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:42,164 [classy] Got parameters {'Omega_m': 0.3735843911966811, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:42,164 [classy] Computing new state
2023-07-02 10:24:42,164 [classy] Setting parameters: {'Omega_m': 0.3735843911966811, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:42,212 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.48689482797027}
2023-07-02 10:24:42,212 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:42,214 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.198477
2023-07-02 10:24:42,214 [model] Computed derived parameters: {}
2023-07-02 10:24:42,214 [mcmc] New sample, #328:
Omega_m:0.2969256
2023-07-02 10:24:42,214 [model] Posterior to be computed for parameters {'Omega_m': 0.32427887495765406}
2023-07-02 10:24:42,214 [prior] Evaluating prior at array([0.32427887])
2023-07-02 10:24:42,214 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:42,215 [model] Got input parameters: {'Omega_m': 0.32427887495765406, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:42,215 [classy] Got parameters {'Omega_m': 0.32427887495765406, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:42,215 [classy] Computing new state
2023-07-02 10:24:42,215 [classy] Setting parameters: {'Omega_m': 0.32427887495765406, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:42,262 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.8642169437191}
2023-07-02 10:24:42,262 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:42,264 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00848877
2023-07-02 10:24:42,264 [model] Computed derived parameters: {}
2023-07-02 10:24:42,264 [mcmc] New sample, #329:
Omega_m:0.3735844
2023-07-02 10:24:42,264 [model] Posterior to be computed for parameters {'Omega_m': -0.1693620989199789}
2023-07-02 10:24:42,264 [prior] Evaluating prior at array([-0.1693621])
2023-07-02 10:24:42,264 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:42,264 [model] Posterior to be computed for parameters {'Omega_m': 0.6025590133705816}
2023-07-02 10:24:42,264 [prior] Evaluating prior at array([0.60255901])
2023-07-02 10:24:42,264 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:42,264 [model] Got input parameters: {'Omega_m': 0.6025590133705816, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:42,264 [classy] Got parameters {'Omega_m': 0.6025590133705816, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:42,264 [classy] Computing new state
2023-07-02 10:24:42,264 [classy] Setting parameters: {'Omega_m': 0.6025590133705816, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:42,312 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 122.1129746221802}
2023-07-02 10:24:42,312 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:42,314 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.90192
2023-07-02 10:24:42,314 [model] Computed derived parameters: {}
2023-07-02 10:24:42,314 [model] Posterior to be computed for parameters {'Omega_m': 0.24415077334977903}
2023-07-02 10:24:42,314 [prior] Evaluating prior at array([0.24415077])
2023-07-02 10:24:42,314 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:42,314 [model] Got input parameters: {'Omega_m': 0.24415077334977903, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:42,314 [classy] Got parameters {'Omega_m': 0.24415077334977903, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:42,314 [classy] Computing new state
2023-07-02 10:24:42,314 [classy] Setting parameters: {'Omega_m': 0.24415077334977903, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:42,361 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 156.385509020039}
2023-07-02 10:24:42,361 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:42,363 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.343825
2023-07-02 10:24:42,363 [model] Computed derived parameters: {}
2023-07-02 10:24:42,363 [model] Posterior to be computed for parameters {'Omega_m': 0.3671402793651287}
2023-07-02 10:24:42,364 [prior] Evaluating prior at array([0.36714028])
2023-07-02 10:24:42,364 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:42,364 [model] Got input parameters: {'Omega_m': 0.3671402793651287, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:42,364 [classy] Got parameters {'Omega_m': 0.3671402793651287, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:42,364 [classy] Computing new state
2023-07-02 10:24:42,364 [classy] Setting parameters: {'Omega_m': 0.3671402793651287, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:42,411 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.15120918862218}
2023-07-02 10:24:42,411 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:42,412 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.161163
2023-07-02 10:24:42,413 [model] Computed derived parameters: {}
2023-07-02 10:24:42,413 [mcmc] New sample, #330:
Omega_m:0.3242789
2023-07-02 10:24:42,413 [model] Posterior to be computed for parameters {'Omega_m': 0.48740955476867676}
2023-07-02 10:24:42,413 [prior] Evaluating prior at array([0.48740955])
2023-07-02 10:24:42,413 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:42,413 [model] Got input parameters: {'Omega_m': 0.48740955476867676, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:42,413 [classy] Got parameters {'Omega_m': 0.48740955476867676, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:42,413 [classy] Computing new state
2023-07-02 10:24:42,413 [classy] Setting parameters: {'Omega_m': 0.48740955476867676, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:42,460 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.26902055142034}
2023-07-02 10:24:42,461 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:42,462 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.2889
2023-07-02 10:24:42,462 [model] Computed derived parameters: {}
2023-07-02 10:24:42,463 [model] Posterior to be computed for parameters {'Omega_m': 0.26249511098601025}
2023-07-02 10:24:42,463 [prior] Evaluating prior at array([0.26249511])
2023-07-02 10:24:42,463 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:42,463 [model] Got input parameters: {'Omega_m': 0.26249511098601025, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:42,463 [classy] Got parameters {'Omega_m': 0.26249511098601025, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:42,463 [classy] Computing new state
2023-07-02 10:24:42,463 [classy] Setting parameters: {'Omega_m': 0.26249511098601025, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:42,511 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.74172245436006}
2023-07-02 10:24:42,511 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:42,512 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.17485
2023-07-02 10:24:42,512 [model] Computed derived parameters: {}
2023-07-02 10:24:42,513 [mcmc] New sample, #331:
Omega_m:0.3671403
2023-07-02 10:24:42,513 [model] Posterior to be computed for parameters {'Omega_m': 0.1585531552195668}
2023-07-02 10:24:42,513 [prior] Evaluating prior at array([0.15855316])
2023-07-02 10:24:42,513 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:42,513 [model] Got input parameters: {'Omega_m': 0.1585531552195668, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:42,513 [classy] Got parameters {'Omega_m': 0.1585531552195668, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:42,513 [classy] Computing new state
2023-07-02 10:24:42,513 [classy] Setting parameters: {'Omega_m': 0.1585531552195668, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:42,560 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 171.3091312302472}
2023-07-02 10:24:42,560 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:42,562 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.29276
2023-07-02 10:24:42,562 [model] Computed derived parameters: {}
2023-07-02 10:24:42,562 [model] Posterior to be computed for parameters {'Omega_m': 0.4485543892027447}
2023-07-02 10:24:42,562 [prior] Evaluating prior at array([0.44855439])
2023-07-02 10:24:42,562 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:42,562 [model] Got input parameters: {'Omega_m': 0.4485543892027447, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:42,562 [classy] Got parameters {'Omega_m': 0.4485543892027447, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:42,562 [classy] Computing new state
2023-07-02 10:24:42,562 [classy] Setting parameters: {'Omega_m': 0.4485543892027447, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:42,609 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 133.46873812264752}
2023-07-02 10:24:42,609 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:42,611 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.840473
2023-07-02 10:24:42,611 [model] Computed derived parameters: {}
2023-07-02 10:24:42,611 [mcmc] New sample, #332:
Omega_m:0.2624951
2023-07-02 10:24:42,611 [model] Posterior to be computed for parameters {'Omega_m': 0.44373808913166485}
2023-07-02 10:24:42,612 [prior] Evaluating prior at array([0.44373809])
2023-07-02 10:24:42,612 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:42,612 [model] Got input parameters: {'Omega_m': 0.44373808913166485, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:42,612 [classy] Got parameters {'Omega_m': 0.44373808913166485, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:42,612 [classy] Computing new state
2023-07-02 10:24:42,612 [classy] Setting parameters: {'Omega_m': 0.44373808913166485, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:42,677 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 133.884257770616}
2023-07-02 10:24:42,677 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:42,679 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.789555
2023-07-02 10:24:42,679 [model] Computed derived parameters: {}
2023-07-02 10:24:42,680 [mcmc] New sample, #333:
Omega_m:0.4485544
2023-07-02 10:24:42,680 [model] Posterior to be computed for parameters {'Omega_m': -0.20669705696165291}
2023-07-02 10:24:42,680 [prior] Evaluating prior at array([-0.20669706])
2023-07-02 10:24:42,680 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:42,680 [model] Posterior to be computed for parameters {'Omega_m': 0.346880755918653}
2023-07-02 10:24:42,680 [prior] Evaluating prior at array([0.34688076])
2023-07-02 10:24:42,680 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:42,680 [model] Got input parameters: {'Omega_m': 0.346880755918653, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:42,680 [classy] Got parameters {'Omega_m': 0.346880755918653, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:42,680 [classy] Computing new state
2023-07-02 10:24:42,680 [classy] Setting parameters: {'Omega_m': 0.346880755918653, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:42,732 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.31242321195887}
2023-07-02 10:24:42,733 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:42,734 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0669829
2023-07-02 10:24:42,734 [model] Computed derived parameters: {}
2023-07-02 10:24:42,734 [mcmc] New sample, #334:
Omega_m:0.4437381
2023-07-02 10:24:42,735 [model] Posterior to be computed for parameters {'Omega_m': 0.07184849199864013}
2023-07-02 10:24:42,735 [prior] Evaluating prior at array([0.07184849])
2023-07-02 10:24:42,735 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:42,735 [model] Posterior to be computed for parameters {'Omega_m': 0.8718486197867703}
2023-07-02 10:24:42,735 [prior] Evaluating prior at array([0.87184862])
2023-07-02 10:24:42,735 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:42,735 [model] Got input parameters: {'Omega_m': 0.8718486197867703, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:42,735 [classy] Got parameters {'Omega_m': 0.8718486197867703, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:42,735 [classy] Computing new state
2023-07-02 10:24:42,735 [classy] Setting parameters: {'Omega_m': 0.8718486197867703, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:42,781 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 108.14770221577228}
2023-07-02 10:24:42,781 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:42,783 [bao_likelihood.baolikelihood] Computed log-likelihood = -7.39049
2023-07-02 10:24:42,783 [model] Computed derived parameters: {}
2023-07-02 10:24:42,783 [model] Posterior to be computed for parameters {'Omega_m': 0.1513696866716494}
2023-07-02 10:24:42,783 [prior] Evaluating prior at array([0.15136969])
2023-07-02 10:24:42,783 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:42,783 [model] Got input parameters: {'Omega_m': 0.1513696866716494, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:42,784 [classy] Got parameters {'Omega_m': 0.1513696866716494, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:42,784 [classy] Computing new state
2023-07-02 10:24:42,784 [classy] Setting parameters: {'Omega_m': 0.1513696866716494, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:42,831 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 172.81067875952124}
2023-07-02 10:24:42,831 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:42,832 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.57785
2023-07-02 10:24:42,833 [model] Computed derived parameters: {}
2023-07-02 10:24:42,833 [model] Posterior to be computed for parameters {'Omega_m': 0.14264891957824588}
2023-07-02 10:24:42,833 [prior] Evaluating prior at array([0.14264892])
2023-07-02 10:24:42,833 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:42,833 [model] Got input parameters: {'Omega_m': 0.14264891957824588, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:42,833 [classy] Got parameters {'Omega_m': 0.14264891957824588, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:42,833 [classy] Computing new state
2023-07-02 10:24:42,833 [classy] Setting parameters: {'Omega_m': 0.14264891957824588, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:42,881 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 174.69973183741268}
2023-07-02 10:24:42,881 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:42,883 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.95855
2023-07-02 10:24:42,883 [model] Computed derived parameters: {}
2023-07-02 10:24:42,883 [model] Posterior to be computed for parameters {'Omega_m': 0.26085620089073785}
2023-07-02 10:24:42,883 [prior] Evaluating prior at array([0.2608562])
2023-07-02 10:24:42,883 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:42,883 [model] Got input parameters: {'Omega_m': 0.26085620089073785, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:42,883 [classy] Got parameters {'Omega_m': 0.26085620089073785, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:42,883 [classy] Computing new state
2023-07-02 10:24:42,883 [classy] Setting parameters: {'Omega_m': 0.26085620089073785, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:42,932 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.9715480413894}
2023-07-02 10:24:42,932 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:42,934 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.187333
2023-07-02 10:24:42,934 [model] Computed derived parameters: {}
2023-07-02 10:24:42,934 [mcmc] New sample, #335:
Omega_m:0.3468808
2023-07-02 10:24:42,934 [model] Posterior to be computed for parameters {'Omega_m': 0.4652357747195963}
2023-07-02 10:24:42,935 [prior] Evaluating prior at array([0.46523577])
2023-07-02 10:24:42,935 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:42,935 [model] Got input parameters: {'Omega_m': 0.4652357747195963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:42,935 [classy] Got parameters {'Omega_m': 0.4652357747195963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:42,935 [classy] Computing new state
2023-07-02 10:24:42,935 [classy] Setting parameters: {'Omega_m': 0.4652357747195963, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:42,981 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 132.0626677857063}
2023-07-02 10:24:42,981 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:42,983 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.02517
2023-07-02 10:24:42,983 [model] Computed derived parameters: {}
2023-07-02 10:24:42,983 [mcmc] New sample, #336:
Omega_m:0.2608562
2023-07-02 10:24:42,983 [model] Posterior to be computed for parameters {'Omega_m': 0.5052803590097305}
2023-07-02 10:24:42,983 [prior] Evaluating prior at array([0.50528036])
2023-07-02 10:24:42,983 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:42,983 [model] Got input parameters: {'Omega_m': 0.5052803590097305, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:42,983 [classy] Got parameters {'Omega_m': 0.5052803590097305, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:42,983 [classy] Computing new state
2023-07-02 10:24:42,983 [classy] Setting parameters: {'Omega_m': 0.5052803590097305, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:43,034 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 128.88183902488632}
2023-07-02 10:24:43,035 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:43,037 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.51481
2023-07-02 10:24:43,037 [model] Computed derived parameters: {}
2023-07-02 10:24:43,037 [model] Posterior to be computed for parameters {'Omega_m': 0.45911757138097076}
2023-07-02 10:24:43,037 [prior] Evaluating prior at array([0.45911757])
2023-07-02 10:24:43,037 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:43,037 [model] Got input parameters: {'Omega_m': 0.45911757138097076, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:43,037 [classy] Got parameters {'Omega_m': 0.45911757138097076, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:43,037 [classy] Computing new state
2023-07-02 10:24:43,037 [classy] Setting parameters: {'Omega_m': 0.45911757138097076, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:43,083 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 132.57249468984796}
2023-07-02 10:24:43,083 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:43,085 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.955985
2023-07-02 10:24:43,085 [model] Computed derived parameters: {}
2023-07-02 10:24:43,085 [mcmc] New sample, #337:
Omega_m:0.4652358
2023-07-02 10:24:43,085 [model] Posterior to be computed for parameters {'Omega_m': 0.14670921660758607}
2023-07-02 10:24:43,085 [prior] Evaluating prior at array([0.14670922])
2023-07-02 10:24:43,085 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:43,085 [model] Got input parameters: {'Omega_m': 0.14670921660758607, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:43,085 [classy] Got parameters {'Omega_m': 0.14670921660758607, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:43,085 [classy] Computing new state
2023-07-02 10:24:43,085 [classy] Setting parameters: {'Omega_m': 0.14670921660758607, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:43,131 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 173.81092347338438}
2023-07-02 10:24:43,132 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:43,133 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.77639
2023-07-02 10:24:43,133 [model] Computed derived parameters: {}
2023-07-02 10:24:43,133 [model] Posterior to be computed for parameters {'Omega_m': 0.5585755368452686}
2023-07-02 10:24:43,133 [prior] Evaluating prior at array([0.55857554])
2023-07-02 10:24:43,134 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:43,134 [model] Got input parameters: {'Omega_m': 0.5585755368452686, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:43,134 [classy] Got parameters {'Omega_m': 0.5585755368452686, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:43,134 [classy] Computing new state
2023-07-02 10:24:43,134 [classy] Setting parameters: {'Omega_m': 0.5585755368452686, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:43,180 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 125.02247993634876}
2023-07-02 10:24:43,180 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:43,182 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.24666
2023-07-02 10:24:43,182 [model] Computed derived parameters: {}
2023-07-02 10:24:43,182 [model] Posterior to be computed for parameters {'Omega_m': 0.19244306846874792}
2023-07-02 10:24:43,182 [prior] Evaluating prior at array([0.19244307])
2023-07-02 10:24:43,182 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:43,182 [model] Got input parameters: {'Omega_m': 0.19244306846874792, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:43,182 [classy] Got parameters {'Omega_m': 0.19244306846874792, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:43,182 [classy] Computing new state
2023-07-02 10:24:43,182 [classy] Setting parameters: {'Omega_m': 0.19244306846874792, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:43,228 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 164.80887754914818}
2023-07-02 10:24:43,229 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:43,230 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.24211
2023-07-02 10:24:43,230 [model] Computed derived parameters: {}
2023-07-02 10:24:43,230 [model] Posterior to be computed for parameters {'Omega_m': 0.4277140357589607}
2023-07-02 10:24:43,230 [prior] Evaluating prior at array([0.42771404])
2023-07-02 10:24:43,231 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:43,231 [model] Got input parameters: {'Omega_m': 0.4277140357589607, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:43,231 [classy] Got parameters {'Omega_m': 0.4277140357589607, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:43,231 [classy] Computing new state
2023-07-02 10:24:43,231 [classy] Setting parameters: {'Omega_m': 0.4277140357589607, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:43,281 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 135.29915024059824}
2023-07-02 10:24:43,281 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:43,283 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.62856
2023-07-02 10:24:43,284 [model] Computed derived parameters: {}
2023-07-02 10:24:43,284 [mcmc] New sample, #338:
Omega_m:0.4591176
2023-07-02 10:24:43,284 [model] Posterior to be computed for parameters {'Omega_m': 0.5604789901828179}
2023-07-02 10:24:43,284 [prior] Evaluating prior at array([0.56047899])
2023-07-02 10:24:43,284 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:43,284 [model] Got input parameters: {'Omega_m': 0.5604789901828179, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:43,284 [classy] Got parameters {'Omega_m': 0.5604789901828179, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:43,284 [classy] Computing new state
2023-07-02 10:24:43,284 [classy] Setting parameters: {'Omega_m': 0.5604789901828179, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:43,354 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 124.89171456117029}
2023-07-02 10:24:43,354 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:43,357 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.27418
2023-07-02 10:24:43,357 [model] Computed derived parameters: {}
2023-07-02 10:24:43,357 [model] Posterior to be computed for parameters {'Omega_m': 1.0258895395646146}
2023-07-02 10:24:43,357 [prior] Evaluating prior at array([1.02588954])
2023-07-02 10:24:43,357 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:43,357 [model] Posterior to be computed for parameters {'Omega_m': -0.2952585729695062}
2023-07-02 10:24:43,357 [prior] Evaluating prior at array([-0.29525857])
2023-07-02 10:24:43,358 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:43,358 [model] Posterior to be computed for parameters {'Omega_m': 0.3919191848475967}
2023-07-02 10:24:43,358 [prior] Evaluating prior at array([0.39191918])
2023-07-02 10:24:43,358 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:43,358 [model] Got input parameters: {'Omega_m': 0.3919191848475967, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:43,358 [classy] Got parameters {'Omega_m': 0.3919191848475967, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:43,358 [classy] Computing new state
2023-07-02 10:24:43,358 [classy] Setting parameters: {'Omega_m': 0.3919191848475967, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:43,416 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 138.65396112785308}
2023-07-02 10:24:43,416 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:43,418 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.322116
2023-07-02 10:24:43,418 [model] Computed derived parameters: {}
2023-07-02 10:24:43,418 [mcmc] New sample, #339:
Omega_m:0.427714
2023-07-02 10:24:43,419 [model] Posterior to be computed for parameters {'Omega_m': 0.2313428560768509}
2023-07-02 10:24:43,419 [prior] Evaluating prior at array([0.23134286])
2023-07-02 10:24:43,419 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:43,419 [model] Got input parameters: {'Omega_m': 0.2313428560768509, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:43,419 [classy] Got parameters {'Omega_m': 0.2313428560768509, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:43,419 [classy] Computing new state
2023-07-02 10:24:43,419 [classy] Setting parameters: {'Omega_m': 0.2313428560768509, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:43,467 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 158.32973111199684}
2023-07-02 10:24:43,467 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:43,470 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.50313
2023-07-02 10:24:43,470 [model] Computed derived parameters: {}
2023-07-02 10:24:43,470 [mcmc] New sample, #340:
Omega_m:0.3919192
2023-07-02 10:24:43,470 [model] Posterior to be computed for parameters {'Omega_m': 0.08563871528441033}
2023-07-02 10:24:43,470 [prior] Evaluating prior at array([0.08563872])
2023-07-02 10:24:43,470 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:43,470 [model] Posterior to be computed for parameters {'Omega_m': 0.014361644866009188}
2023-07-02 10:24:43,470 [prior] Evaluating prior at array([0.01436164])
2023-07-02 10:24:43,471 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:43,471 [model] Posterior to be computed for parameters {'Omega_m': 0.5163885394599578}
2023-07-02 10:24:43,471 [prior] Evaluating prior at array([0.51638854])
2023-07-02 10:24:43,471 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:43,471 [model] Got input parameters: {'Omega_m': 0.5163885394599578, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:43,471 [classy] Got parameters {'Omega_m': 0.5163885394599578, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:43,471 [classy] Computing new state
2023-07-02 10:24:43,471 [classy] Setting parameters: {'Omega_m': 0.5163885394599578, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:43,516 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 128.04429148533478}
2023-07-02 10:24:43,516 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:43,518 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.66062
2023-07-02 10:24:43,519 [model] Computed derived parameters: {}
2023-07-02 10:24:43,519 [mcmc] New sample, #341:
Omega_m:0.2313429
2023-07-02 10:24:43,519 [model] Posterior to be computed for parameters {'Omega_m': 0.25594015048362767}
2023-07-02 10:24:43,519 [prior] Evaluating prior at array([0.25594015])
2023-07-02 10:24:43,519 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:43,519 [model] Got input parameters: {'Omega_m': 0.25594015048362767, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:43,519 [classy] Got parameters {'Omega_m': 0.25594015048362767, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:43,519 [classy] Computing new state
2023-07-02 10:24:43,520 [classy] Setting parameters: {'Omega_m': 0.25594015048362767, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:43,566 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 154.66829498730712}
2023-07-02 10:24:43,566 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:43,567 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.227758
2023-07-02 10:24:43,568 [model] Computed derived parameters: {}
2023-07-02 10:24:43,568 [mcmc] New sample, #342:
Omega_m:0.5163885
2023-07-02 10:24:43,568 [model] Posterior to be computed for parameters {'Omega_m': 0.22264926960659917}
2023-07-02 10:24:43,568 [prior] Evaluating prior at array([0.22264927])
2023-07-02 10:24:43,568 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:43,568 [model] Got input parameters: {'Omega_m': 0.22264926960659917, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:43,568 [classy] Got parameters {'Omega_m': 0.22264926960659917, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:43,568 [classy] Computing new state
2023-07-02 10:24:43,568 [classy] Setting parameters: {'Omega_m': 0.22264926960659917, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:43,614 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 159.69933398372078}
2023-07-02 10:24:43,615 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:43,616 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.632894
2023-07-02 10:24:43,616 [model] Computed derived parameters: {}
2023-07-02 10:24:43,616 [mcmc] New sample, #343:
Omega_m:0.2559402
2023-07-02 10:24:43,616 [model] Posterior to be computed for parameters {'Omega_m': 0.2549609215988391}
2023-07-02 10:24:43,617 [prior] Evaluating prior at array([0.25496092])
2023-07-02 10:24:43,617 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:43,617 [model] Got input parameters: {'Omega_m': 0.2549609215988391, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:43,617 [classy] Got parameters {'Omega_m': 0.2549609215988391, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:43,617 [classy] Computing new state
2023-07-02 10:24:43,617 [classy] Setting parameters: {'Omega_m': 0.2549609215988391, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:43,663 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 154.80841037309568}
2023-07-02 10:24:43,663 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:43,664 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.236355
2023-07-02 10:24:43,665 [model] Computed derived parameters: {}
2023-07-02 10:24:43,665 [mcmc] New sample, #344:
Omega_m:0.2226493
2023-07-02 10:24:43,665 [model] Posterior to be computed for parameters {'Omega_m': -0.5367928599403415}
2023-07-02 10:24:43,665 [prior] Evaluating prior at array([-0.53679286])
2023-07-02 10:24:43,665 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:43,665 [model] Posterior to be computed for parameters {'Omega_m': 0.04525645269292344}
2023-07-02 10:24:43,665 [prior] Evaluating prior at array([0.04525645])
2023-07-02 10:24:43,665 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:43,665 [model] Posterior to be computed for parameters {'Omega_m': 0.42214874368410904}
2023-07-02 10:24:43,665 [prior] Evaluating prior at array([0.42214874])
2023-07-02 10:24:43,665 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:43,665 [model] Got input parameters: {'Omega_m': 0.42214874368410904, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:43,665 [classy] Got parameters {'Omega_m': 0.42214874368410904, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:43,665 [classy] Computing new state
2023-07-02 10:24:43,665 [classy] Setting parameters: {'Omega_m': 0.42214874368410904, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:43,712 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 135.80261168440575}
2023-07-02 10:24:43,712 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:43,714 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.575861
2023-07-02 10:24:43,714 [model] Computed derived parameters: {}
2023-07-02 10:24:43,714 [mcmc] New sample, #345:
Omega_m:0.2549609
2023-07-02 10:24:43,714 [model] Posterior to be computed for parameters {'Omega_m': 0.7859970612437794}
2023-07-02 10:24:43,714 [prior] Evaluating prior at array([0.78599706])
2023-07-02 10:24:43,714 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:43,714 [model] Got input parameters: {'Omega_m': 0.7859970612437794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:43,714 [classy] Got parameters {'Omega_m': 0.7859970612437794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:43,714 [classy] Computing new state
2023-07-02 10:24:43,714 [classy] Setting parameters: {'Omega_m': 0.7859970612437794, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:43,765 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 112.01841101222831}
2023-07-02 10:24:43,766 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:43,769 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.91166
2023-07-02 10:24:43,770 [model] Computed derived parameters: {}
2023-07-02 10:24:43,770 [model] Posterior to be computed for parameters {'Omega_m': 0.8531588240877295}
2023-07-02 10:24:43,770 [prior] Evaluating prior at array([0.85315882])
2023-07-02 10:24:43,770 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:43,770 [model] Got input parameters: {'Omega_m': 0.8531588240877295, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:43,770 [classy] Got parameters {'Omega_m': 0.8531588240877295, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:43,770 [classy] Computing new state
2023-07-02 10:24:43,770 [classy] Setting parameters: {'Omega_m': 0.8531588240877295, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:43,827 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 108.95303468646857}
2023-07-02 10:24:43,827 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:43,829 [bao_likelihood.baolikelihood] Computed log-likelihood = -7.06713
2023-07-02 10:24:43,829 [model] Computed derived parameters: {}
2023-07-02 10:24:43,829 [model] Posterior to be computed for parameters {'Omega_m': 0.08378386579509162}
2023-07-02 10:24:43,829 [prior] Evaluating prior at array([0.08378387])
2023-07-02 10:24:43,830 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:43,830 [model] Posterior to be computed for parameters {'Omega_m': 0.10975719061785266}
2023-07-02 10:24:43,830 [prior] Evaluating prior at array([0.10975719])
2023-07-02 10:24:43,830 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:43,830 [model] Got input parameters: {'Omega_m': 0.10975719061785266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:43,830 [classy] Got parameters {'Omega_m': 0.10975719061785266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:43,830 [classy] Computing new state
2023-07-02 10:24:43,830 [classy] Setting parameters: {'Omega_m': 0.10975719061785266, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:43,881 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 182.57525948776947}
2023-07-02 10:24:43,881 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:43,883 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.80247
2023-07-02 10:24:43,883 [model] Computed derived parameters: {}
2023-07-02 10:24:43,884 [model] Posterior to be computed for parameters {'Omega_m': 0.9857292676817642}
2023-07-02 10:24:43,884 [prior] Evaluating prior at array([0.98572927])
2023-07-02 10:24:43,884 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:43,884 [model] Got input parameters: {'Omega_m': 0.9857292676817642, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:43,884 [classy] Got parameters {'Omega_m': 0.9857292676817642, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:43,884 [classy] Computing new state
2023-07-02 10:24:43,884 [classy] Setting parameters: {'Omega_m': 0.9857292676817642, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:43,932 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 103.627609636173}
2023-07-02 10:24:43,932 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:43,934 [bao_likelihood.baolikelihood] Computed log-likelihood = -9.36409
2023-07-02 10:24:43,934 [model] Computed derived parameters: {}
2023-07-02 10:24:43,934 [model] Posterior to be computed for parameters {'Omega_m': 0.1319142983723855}
2023-07-02 10:24:43,934 [prior] Evaluating prior at array([0.1319143])
2023-07-02 10:24:43,935 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:43,935 [model] Got input parameters: {'Omega_m': 0.1319142983723855, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:43,935 [classy] Got parameters {'Omega_m': 0.1319142983723855, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:43,935 [classy] Computing new state
2023-07-02 10:24:43,935 [classy] Setting parameters: {'Omega_m': 0.1319142983723855, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:43,981 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 177.1321458402311}
2023-07-02 10:24:43,981 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:43,983 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.48434
2023-07-02 10:24:43,983 [model] Computed derived parameters: {}
2023-07-02 10:24:43,983 [model] Posterior to be computed for parameters {'Omega_m': 0.27032583919259134}
2023-07-02 10:24:43,983 [prior] Evaluating prior at array([0.27032584])
2023-07-02 10:24:43,983 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:43,983 [model] Got input parameters: {'Omega_m': 0.27032583919259134, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:43,983 [classy] Got parameters {'Omega_m': 0.27032583919259134, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:43,983 [classy] Computing new state
2023-07-02 10:24:43,983 [classy] Setting parameters: {'Omega_m': 0.27032583919259134, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:44,031 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.65993466576168}
2023-07-02 10:24:44,031 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:44,032 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.121789
2023-07-02 10:24:44,032 [model] Computed derived parameters: {}
2023-07-02 10:24:44,032 [mcmc] New sample, #346:
Omega_m:0.4221487
2023-07-02 10:24:44,033 [model] Posterior to be computed for parameters {'Omega_m': 0.2802083109042294}
2023-07-02 10:24:44,033 [prior] Evaluating prior at array([0.28020831])
2023-07-02 10:24:44,033 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:44,033 [model] Got input parameters: {'Omega_m': 0.2802083109042294, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:44,033 [classy] Got parameters {'Omega_m': 0.2802083109042294, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:44,033 [classy] Computing new state
2023-07-02 10:24:44,033 [classy] Setting parameters: {'Omega_m': 0.2802083109042294, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:44,079 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.3320317736816}
2023-07-02 10:24:44,079 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:44,081 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0696039
2023-07-02 10:24:44,081 [model] Computed derived parameters: {}
2023-07-02 10:24:44,081 [mcmc] New sample, #347:
Omega_m:0.2703258
2023-07-02 10:24:44,082 [model] Posterior to be computed for parameters {'Omega_m': 0.5100726103355833}
2023-07-02 10:24:44,082 [prior] Evaluating prior at array([0.51007261])
2023-07-02 10:24:44,082 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:44,082 [model] Got input parameters: {'Omega_m': 0.5100726103355833, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:44,082 [classy] Got parameters {'Omega_m': 0.5100726103355833, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:44,082 [classy] Computing new state
2023-07-02 10:24:44,082 [classy] Setting parameters: {'Omega_m': 0.5100726103355833, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:44,130 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 128.51823021835528}
2023-07-02 10:24:44,130 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:44,132 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.57724
2023-07-02 10:24:44,132 [model] Computed derived parameters: {}
2023-07-02 10:24:44,132 [model] Posterior to be computed for parameters {'Omega_m': 0.3427387587367304}
2023-07-02 10:24:44,132 [prior] Evaluating prior at array([0.34273876])
2023-07-02 10:24:44,132 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:44,132 [model] Got input parameters: {'Omega_m': 0.3427387587367304, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:44,132 [classy] Got parameters {'Omega_m': 0.3427387587367304, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:44,132 [classy] Computing new state
2023-07-02 10:24:44,132 [classy] Setting parameters: {'Omega_m': 0.3427387587367304, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:44,179 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.76852611962065}
2023-07-02 10:24:44,179 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:44,181 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.052372
2023-07-02 10:24:44,181 [model] Computed derived parameters: {}
2023-07-02 10:24:44,181 [mcmc] New sample, #348:
Omega_m:0.2802083
2023-07-02 10:24:44,181 [model] Posterior to be computed for parameters {'Omega_m': 0.8127495723151039}
2023-07-02 10:24:44,181 [prior] Evaluating prior at array([0.81274957])
2023-07-02 10:24:44,181 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:44,181 [model] Got input parameters: {'Omega_m': 0.8127495723151039, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:44,181 [classy] Got parameters {'Omega_m': 0.8127495723151039, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:44,181 [classy] Computing new state
2023-07-02 10:24:44,181 [classy] Setting parameters: {'Omega_m': 0.8127495723151039, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:44,228 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 110.76373064153115}
2023-07-02 10:24:44,228 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:44,230 [bao_likelihood.baolikelihood] Computed log-likelihood = -6.37035
2023-07-02 10:24:44,230 [model] Computed derived parameters: {}
2023-07-02 10:24:44,230 [model] Posterior to be computed for parameters {'Omega_m': 0.6905751989782409}
2023-07-02 10:24:44,230 [prior] Evaluating prior at array([0.6905752])
2023-07-02 10:24:44,230 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:44,230 [model] Got input parameters: {'Omega_m': 0.6905751989782409, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:44,231 [classy] Got parameters {'Omega_m': 0.6905751989782409, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:44,231 [classy] Computing new state
2023-07-02 10:24:44,231 [classy] Setting parameters: {'Omega_m': 0.6905751989782409, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:44,277 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 116.90871220796458}
2023-07-02 10:24:44,277 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:44,278 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.3062
2023-07-02 10:24:44,279 [model] Computed derived parameters: {}
2023-07-02 10:24:44,279 [model] Posterior to be computed for parameters {'Omega_m': -0.010868163143254672}
2023-07-02 10:24:44,279 [prior] Evaluating prior at array([-0.01086816])
2023-07-02 10:24:44,279 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:44,279 [model] Posterior to be computed for parameters {'Omega_m': 0.5158900310035739}
2023-07-02 10:24:44,279 [prior] Evaluating prior at array([0.51589003])
2023-07-02 10:24:44,279 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:44,279 [model] Got input parameters: {'Omega_m': 0.5158900310035739, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:44,279 [classy] Got parameters {'Omega_m': 0.5158900310035739, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:44,279 [classy] Computing new state
2023-07-02 10:24:44,279 [classy] Setting parameters: {'Omega_m': 0.5158900310035739, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:44,326 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 128.0814860662557}
2023-07-02 10:24:44,326 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:44,328 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.654
2023-07-02 10:24:44,328 [model] Computed derived parameters: {}
2023-07-02 10:24:44,328 [mcmc] New sample, #349:
Omega_m:0.3427388
2023-07-02 10:24:44,328 [model] Posterior to be computed for parameters {'Omega_m': 0.633032507668241}
2023-07-02 10:24:44,328 [prior] Evaluating prior at array([0.63303251])
2023-07-02 10:24:44,328 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:44,328 [model] Got input parameters: {'Omega_m': 0.633032507668241, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:44,328 [classy] Got parameters {'Omega_m': 0.633032507668241, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:44,328 [classy] Computing new state
2023-07-02 10:24:44,328 [classy] Setting parameters: {'Omega_m': 0.633032507668241, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:44,375 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 120.22468677171638}
2023-07-02 10:24:44,375 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:44,377 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.37636
2023-07-02 10:24:44,377 [model] Computed derived parameters: {}
2023-07-02 10:24:44,377 [model] Posterior to be computed for parameters {'Omega_m': 0.5351123470039459}
2023-07-02 10:24:44,377 [prior] Evaluating prior at array([0.53511235])
2023-07-02 10:24:44,378 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:44,378 [model] Got input parameters: {'Omega_m': 0.5351123470039459, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:44,378 [classy] Got parameters {'Omega_m': 0.5351123470039459, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:44,378 [classy] Computing new state
2023-07-02 10:24:44,378 [classy] Setting parameters: {'Omega_m': 0.5351123470039459, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:44,424 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 126.67308895188961}
2023-07-02 10:24:44,424 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:44,426 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.91482
2023-07-02 10:24:44,426 [model] Computed derived parameters: {}
2023-07-02 10:24:44,426 [mcmc] New sample, #350:
Omega_m:0.51589
2023-07-02 10:24:44,427 [model] Posterior to be computed for parameters {'Omega_m': 0.593840642476892}
2023-07-02 10:24:44,427 [prior] Evaluating prior at array([0.59384064])
2023-07-02 10:24:44,427 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:44,427 [model] Got input parameters: {'Omega_m': 0.593840642476892, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:44,427 [classy] Got parameters {'Omega_m': 0.593840642476892, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:44,427 [classy] Computing new state
2023-07-02 10:24:44,427 [classy] Setting parameters: {'Omega_m': 0.593840642476892, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:44,474 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 122.67172950465041}
2023-07-02 10:24:44,474 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:44,476 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.76901
2023-07-02 10:24:44,476 [model] Computed derived parameters: {}
2023-07-02 10:24:44,476 [model] Posterior to be computed for parameters {'Omega_m': 0.8487991676140274}
2023-07-02 10:24:44,476 [prior] Evaluating prior at array([0.84879917])
2023-07-02 10:24:44,476 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:44,476 [model] Got input parameters: {'Omega_m': 0.8487991676140274, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:44,476 [classy] Got parameters {'Omega_m': 0.8487991676140274, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:44,476 [classy] Computing new state
2023-07-02 10:24:44,476 [classy] Setting parameters: {'Omega_m': 0.8487991676140274, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:44,523 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 109.14373464339094}
2023-07-02 10:24:44,523 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:44,525 [bao_likelihood.baolikelihood] Computed log-likelihood = -6.99178
2023-07-02 10:24:44,525 [model] Computed derived parameters: {}
2023-07-02 10:24:44,525 [model] Posterior to be computed for parameters {'Omega_m': -0.039649836427738894}
2023-07-02 10:24:44,525 [prior] Evaluating prior at array([-0.03964984])
2023-07-02 10:24:44,525 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:44,525 [model] Posterior to be computed for parameters {'Omega_m': 0.5352412902503053}
2023-07-02 10:24:44,525 [prior] Evaluating prior at array([0.53524129])
2023-07-02 10:24:44,525 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:44,525 [model] Got input parameters: {'Omega_m': 0.5352412902503053, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:44,525 [classy] Got parameters {'Omega_m': 0.5352412902503053, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:44,525 [classy] Computing new state
2023-07-02 10:24:44,526 [classy] Setting parameters: {'Omega_m': 0.5352412902503053, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:44,574 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 126.66381831345583}
2023-07-02 10:24:44,574 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:44,575 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.9166
2023-07-02 10:24:44,575 [model] Computed derived parameters: {}
2023-07-02 10:24:44,575 [mcmc] New sample, #351:
Omega_m:0.5351123
2023-07-02 10:24:44,576 [model] Posterior to be computed for parameters {'Omega_m': 0.6621716215042605}
2023-07-02 10:24:44,576 [prior] Evaluating prior at array([0.66217162])
2023-07-02 10:24:44,576 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:44,576 [model] Got input parameters: {'Omega_m': 0.6621716215042605, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:44,576 [classy] Got parameters {'Omega_m': 0.6621716215042605, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:44,576 [classy] Computing new state
2023-07-02 10:24:44,576 [classy] Setting parameters: {'Omega_m': 0.6621716215042605, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:44,624 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 118.50700134686988}
2023-07-02 10:24:44,624 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:44,625 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.84242
2023-07-02 10:24:44,626 [model] Computed derived parameters: {}
2023-07-02 10:24:44,626 [model] Posterior to be computed for parameters {'Omega_m': 0.7879682746358245}
2023-07-02 10:24:44,626 [prior] Evaluating prior at array([0.78796827])
2023-07-02 10:24:44,626 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:44,626 [model] Got input parameters: {'Omega_m': 0.7879682746358245, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:44,626 [classy] Got parameters {'Omega_m': 0.7879682746358245, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:44,626 [classy] Computing new state
2023-07-02 10:24:44,626 [classy] Setting parameters: {'Omega_m': 0.7879682746358245, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:44,675 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 111.92435925673924}
2023-07-02 10:24:44,675 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:44,677 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.94537
2023-07-02 10:24:44,677 [model] Computed derived parameters: {}
2023-07-02 10:24:44,677 [model] Posterior to be computed for parameters {'Omega_m': 0.8034765891747773}
2023-07-02 10:24:44,677 [prior] Evaluating prior at array([0.80347659])
2023-07-02 10:24:44,678 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:44,678 [model] Got input parameters: {'Omega_m': 0.8034765891747773, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:44,678 [classy] Got parameters {'Omega_m': 0.8034765891747773, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:44,678 [classy] Computing new state
2023-07-02 10:24:44,678 [classy] Setting parameters: {'Omega_m': 0.8034765891747773, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:44,726 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 111.19339252737063}
2023-07-02 10:24:44,726 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:44,727 [bao_likelihood.baolikelihood] Computed log-likelihood = -6.21106
2023-07-02 10:24:44,728 [model] Computed derived parameters: {}
2023-07-02 10:24:44,728 [mcmc] New sample, #352:
Omega_m:0.5352413
2023-07-02 10:24:44,728 [model] Posterior to be computed for parameters {'Omega_m': 0.5424985376793106}
2023-07-02 10:24:44,728 [prior] Evaluating prior at array([0.54249854])
2023-07-02 10:24:44,728 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:44,728 [model] Got input parameters: {'Omega_m': 0.5424985376793106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:44,728 [classy] Got parameters {'Omega_m': 0.5424985376793106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:44,728 [classy] Computing new state
2023-07-02 10:24:44,728 [classy] Setting parameters: {'Omega_m': 0.5424985376793106, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:44,779 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 126.14559277972083}
2023-07-02 10:24:44,780 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:44,781 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.01778
2023-07-02 10:24:44,781 [model] Computed derived parameters: {}
2023-07-02 10:24:44,781 [mcmc] New sample, #353:
Omega_m:0.8034766
2023-07-02 10:24:44,782 [model] Posterior to be computed for parameters {'Omega_m': 0.9765924049746053}
2023-07-02 10:24:44,782 [prior] Evaluating prior at array([0.9765924])
2023-07-02 10:24:44,782 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:44,782 [model] Got input parameters: {'Omega_m': 0.9765924049746053, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:44,782 [classy] Got parameters {'Omega_m': 0.9765924049746053, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:44,782 [classy] Computing new state
2023-07-02 10:24:44,782 [classy] Setting parameters: {'Omega_m': 0.9765924049746053, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:44,828 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 103.96780801672365}
2023-07-02 10:24:44,828 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:44,830 [bao_likelihood.baolikelihood] Computed log-likelihood = -9.20597
2023-07-02 10:24:44,830 [model] Computed derived parameters: {}
2023-07-02 10:24:44,830 [model] Posterior to be computed for parameters {'Omega_m': 0.500729709420488}
2023-07-02 10:24:44,830 [prior] Evaluating prior at array([0.50072971])
2023-07-02 10:24:44,830 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:44,830 [model] Got input parameters: {'Omega_m': 0.500729709420488, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:44,830 [classy] Got parameters {'Omega_m': 0.500729709420488, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:44,830 [classy] Computing new state
2023-07-02 10:24:44,830 [classy] Setting parameters: {'Omega_m': 0.500729709420488, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:44,879 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 129.2303385722492}
2023-07-02 10:24:44,879 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:44,881 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.45624
2023-07-02 10:24:44,881 [model] Computed derived parameters: {}
2023-07-02 10:24:44,881 [mcmc] New sample, #354:
Omega_m:0.5424985
2023-07-02 10:24:44,881 [model] Posterior to be computed for parameters {'Omega_m': 0.2890519350608233}
2023-07-02 10:24:44,881 [prior] Evaluating prior at array([0.28905194])
2023-07-02 10:24:44,881 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:44,881 [model] Got input parameters: {'Omega_m': 0.2890519350608233, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:44,881 [classy] Got parameters {'Omega_m': 0.2890519350608233, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:44,881 [classy] Computing new state
2023-07-02 10:24:44,881 [classy] Setting parameters: {'Omega_m': 0.2890519350608233, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:44,928 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.1772958027618}
2023-07-02 10:24:44,928 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:44,930 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0359406
2023-07-02 10:24:44,930 [model] Computed derived parameters: {}
2023-07-02 10:24:44,930 [mcmc] New sample, #355:
Omega_m:0.5007297
2023-07-02 10:24:44,930 [model] Posterior to be computed for parameters {'Omega_m': -0.010780879644781916}
2023-07-02 10:24:44,930 [prior] Evaluating prior at array([-0.01078088])
2023-07-02 10:24:44,930 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:44,930 [model] Posterior to be computed for parameters {'Omega_m': 0.05213690248323974}
2023-07-02 10:24:44,930 [prior] Evaluating prior at array([0.0521369])
2023-07-02 10:24:44,930 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:44,930 [model] Posterior to be computed for parameters {'Omega_m': 0.669256904499597}
2023-07-02 10:24:44,930 [prior] Evaluating prior at array([0.6692569])
2023-07-02 10:24:44,931 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:44,931 [model] Got input parameters: {'Omega_m': 0.669256904499597, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:44,931 [classy] Got parameters {'Omega_m': 0.669256904499597, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:44,931 [classy] Computing new state
2023-07-02 10:24:44,931 [classy] Setting parameters: {'Omega_m': 0.669256904499597, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:44,977 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 118.10152242592675}
2023-07-02 10:24:44,977 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:44,978 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.95731
2023-07-02 10:24:44,979 [model] Computed derived parameters: {}
2023-07-02 10:24:44,979 [model] Posterior to be computed for parameters {'Omega_m': 0.555618471759565}
2023-07-02 10:24:44,979 [prior] Evaluating prior at array([0.55561847])
2023-07-02 10:24:44,979 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:44,979 [model] Got input parameters: {'Omega_m': 0.555618471759565, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:44,979 [classy] Got parameters {'Omega_m': 0.555618471759565, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:44,979 [classy] Computing new state
2023-07-02 10:24:44,979 [classy] Setting parameters: {'Omega_m': 0.555618471759565, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:45,026 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 125.22653830654869}
2023-07-02 10:24:45,026 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:45,028 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.20409
2023-07-02 10:24:45,028 [model] Computed derived parameters: {}
2023-07-02 10:24:45,028 [model] Posterior to be computed for parameters {'Omega_m': -0.0021427189608299035}
2023-07-02 10:24:45,028 [prior] Evaluating prior at array([-0.00214272])
2023-07-02 10:24:45,028 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:45,028 [model] Posterior to be computed for parameters {'Omega_m': 0.7696399707263206}
2023-07-02 10:24:45,028 [prior] Evaluating prior at array([0.76963997])
2023-07-02 10:24:45,028 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:45,028 [model] Got input parameters: {'Omega_m': 0.7696399707263206, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:45,028 [classy] Got parameters {'Omega_m': 0.7696399707263206, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:45,028 [classy] Computing new state
2023-07-02 10:24:45,028 [classy] Setting parameters: {'Omega_m': 0.7696399707263206, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:45,073 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 112.80898357916952}
2023-07-02 10:24:45,073 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:45,075 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.63263
2023-07-02 10:24:45,075 [model] Computed derived parameters: {}
2023-07-02 10:24:45,075 [model] Posterior to be computed for parameters {'Omega_m': 0.43774918469304214}
2023-07-02 10:24:45,075 [prior] Evaluating prior at array([0.43774918])
2023-07-02 10:24:45,075 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:45,075 [model] Got input parameters: {'Omega_m': 0.43774918469304214, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:45,075 [classy] Got parameters {'Omega_m': 0.43774918469304214, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:45,075 [classy] Computing new state
2023-07-02 10:24:45,075 [classy] Setting parameters: {'Omega_m': 0.43774918469304214, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:45,122 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 134.40715448534678}
2023-07-02 10:24:45,122 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:45,124 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.727831
2023-07-02 10:24:45,124 [model] Computed derived parameters: {}
2023-07-02 10:24:45,124 [mcmc] New sample, #356:
Omega_m:0.2890519
2023-07-02 10:24:45,124 [model] Posterior to be computed for parameters {'Omega_m': 0.43892656897882126}
2023-07-02 10:24:45,124 [prior] Evaluating prior at array([0.43892657])
2023-07-02 10:24:45,124 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:45,124 [model] Got input parameters: {'Omega_m': 0.43892656897882126, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:45,124 [classy] Got parameters {'Omega_m': 0.43892656897882126, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:45,124 [classy] Computing new state
2023-07-02 10:24:45,124 [classy] Setting parameters: {'Omega_m': 0.43892656897882126, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:45,170 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 134.30379850852572}
2023-07-02 10:24:45,170 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:45,172 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.739825
2023-07-02 10:24:45,172 [model] Computed derived parameters: {}
2023-07-02 10:24:45,172 [mcmc] New sample, #357:
Omega_m:0.4377492
2023-07-02 10:24:45,172 [model] Posterior to be computed for parameters {'Omega_m': -0.18028925982478644}
2023-07-02 10:24:45,172 [prior] Evaluating prior at array([-0.18028926])
2023-07-02 10:24:45,172 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:45,172 [model] Posterior to be computed for parameters {'Omega_m': 0.8557982885876529}
2023-07-02 10:24:45,172 [prior] Evaluating prior at array([0.85579829])
2023-07-02 10:24:45,172 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:45,172 [model] Got input parameters: {'Omega_m': 0.8557982885876529, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:45,172 [classy] Got parameters {'Omega_m': 0.8557982885876529, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:45,172 [classy] Computing new state
2023-07-02 10:24:45,172 [classy] Setting parameters: {'Omega_m': 0.8557982885876529, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:45,218 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 108.83810467499187}
2023-07-02 10:24:45,218 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:45,220 [bao_likelihood.baolikelihood] Computed log-likelihood = -7.11277
2023-07-02 10:24:45,220 [model] Computed derived parameters: {}
2023-07-02 10:24:45,220 [model] Posterior to be computed for parameters {'Omega_m': 0.4414296910401034}
2023-07-02 10:24:45,220 [prior] Evaluating prior at array([0.44142969])
2023-07-02 10:24:45,220 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:45,220 [model] Got input parameters: {'Omega_m': 0.4414296910401034, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:45,221 [classy] Got parameters {'Omega_m': 0.4414296910401034, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:45,221 [classy] Computing new state
2023-07-02 10:24:45,221 [classy] Setting parameters: {'Omega_m': 0.4414296910401034, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:45,266 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 134.0849722180762}
2023-07-02 10:24:45,266 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:45,268 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.765554
2023-07-02 10:24:45,268 [model] Computed derived parameters: {}
2023-07-02 10:24:45,269 [mcmc] New sample, #358:
Omega_m:0.4389266
2023-07-02 10:24:45,269 [model] Posterior to be computed for parameters {'Omega_m': 0.90058341504644}
2023-07-02 10:24:45,269 [prior] Evaluating prior at array([0.90058342])
2023-07-02 10:24:45,269 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:45,269 [model] Got input parameters: {'Omega_m': 0.90058341504644, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:45,269 [classy] Got parameters {'Omega_m': 0.90058341504644, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:45,269 [classy] Computing new state
2023-07-02 10:24:45,269 [classy] Setting parameters: {'Omega_m': 0.90058341504644, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:45,316 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 106.94662591533205}
2023-07-02 10:24:45,316 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:45,318 [bao_likelihood.baolikelihood] Computed log-likelihood = -7.8884
2023-07-02 10:24:45,318 [model] Computed derived parameters: {}
2023-07-02 10:24:45,318 [model] Posterior to be computed for parameters {'Omega_m': 0.599568566639542}
2023-07-02 10:24:45,318 [prior] Evaluating prior at array([0.59956857])
2023-07-02 10:24:45,318 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:45,318 [model] Got input parameters: {'Omega_m': 0.599568566639542, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:45,318 [classy] Got parameters {'Omega_m': 0.599568566639542, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:45,318 [classy] Computing new state
2023-07-02 10:24:45,318 [classy] Setting parameters: {'Omega_m': 0.599568566639542, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:45,367 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 122.30367591248512}
2023-07-02 10:24:45,367 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:45,368 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.85617
2023-07-02 10:24:45,368 [model] Computed derived parameters: {}
2023-07-02 10:24:45,369 [model] Posterior to be computed for parameters {'Omega_m': 0.5561954653678962}
2023-07-02 10:24:45,369 [prior] Evaluating prior at array([0.55619547])
2023-07-02 10:24:45,369 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:45,369 [model] Got input parameters: {'Omega_m': 0.5561954653678962, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:45,369 [classy] Got parameters {'Omega_m': 0.5561954653678962, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:45,369 [classy] Computing new state
2023-07-02 10:24:45,369 [classy] Setting parameters: {'Omega_m': 0.5561954653678962, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:45,418 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 125.18663492667822}
2023-07-02 10:24:45,419 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:45,421 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.21238
2023-07-02 10:24:45,421 [model] Computed derived parameters: {}
2023-07-02 10:24:45,421 [model] Posterior to be computed for parameters {'Omega_m': 0.7314348829752193}
2023-07-02 10:24:45,421 [prior] Evaluating prior at array([0.73143488])
2023-07-02 10:24:45,421 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:45,421 [model] Got input parameters: {'Omega_m': 0.7314348829752193, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:45,421 [classy] Got parameters {'Omega_m': 0.7314348829752193, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:45,422 [classy] Computing new state
2023-07-02 10:24:45,422 [classy] Setting parameters: {'Omega_m': 0.7314348829752193, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:45,468 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 114.72972836373765}
2023-07-02 10:24:45,469 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:45,470 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.9863
2023-07-02 10:24:45,470 [model] Computed derived parameters: {}
2023-07-02 10:24:45,471 [model] Posterior to be computed for parameters {'Omega_m': 0.39058575834802817}
2023-07-02 10:24:45,471 [prior] Evaluating prior at array([0.39058576])
2023-07-02 10:24:45,471 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:45,471 [model] Got input parameters: {'Omega_m': 0.39058575834802817, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:45,471 [classy] Got parameters {'Omega_m': 0.39058575834802817, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:45,471 [classy] Computing new state
2023-07-02 10:24:45,471 [classy] Setting parameters: {'Omega_m': 0.39058575834802817, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:45,519 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 138.78450988854124}
2023-07-02 10:24:45,519 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:45,521 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.312298
2023-07-02 10:24:45,521 [model] Computed derived parameters: {}
2023-07-02 10:24:45,521 [mcmc] New sample, #359:
Omega_m:0.4414297
2023-07-02 10:24:45,521 [model] Posterior to be computed for parameters {'Omega_m': 0.7074844631995114}
2023-07-02 10:24:45,521 [prior] Evaluating prior at array([0.70748446])
2023-07-02 10:24:45,522 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:45,522 [model] Got input parameters: {'Omega_m': 0.7074844631995114, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:45,522 [classy] Got parameters {'Omega_m': 0.7074844631995114, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:45,522 [classy] Computing new state
2023-07-02 10:24:45,522 [classy] Setting parameters: {'Omega_m': 0.7074844631995114, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:45,570 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 115.99044947367614}
2023-07-02 10:24:45,570 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:45,572 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.58602
2023-07-02 10:24:45,572 [model] Computed derived parameters: {}
2023-07-02 10:24:45,572 [model] Posterior to be computed for parameters {'Omega_m': 0.44207595533050464}
2023-07-02 10:24:45,572 [prior] Evaluating prior at array([0.44207596])
2023-07-02 10:24:45,572 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:45,572 [model] Got input parameters: {'Omega_m': 0.44207595533050464, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:45,572 [classy] Got parameters {'Omega_m': 0.44207595533050464, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:45,572 [classy] Computing new state
2023-07-02 10:24:45,572 [classy] Setting parameters: {'Omega_m': 0.44207595533050464, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:45,621 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 134.02867735407992}
2023-07-02 10:24:45,621 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:45,623 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.772247
2023-07-02 10:24:45,623 [model] Computed derived parameters: {}
2023-07-02 10:24:45,623 [mcmc] New sample, #360:
Omega_m:0.3905858
2023-07-02 10:24:45,623 [mcmc] Learn + convergence test @ 360 samples accepted.
2023-07-02 10:24:45,624 [mcmc] Ready to check convergence and learn a new proposal covmat
2023-07-02 10:24:45,630 [mcmc] - Acceptance rate: 0.432
2023-07-02 10:24:45,631 [mcmc] - Condition number = 1
2023-07-02 10:24:45,631 [mcmc] - Eigenvalues = array([0.02178049])
2023-07-02 10:24:45,631 [mcmc] - Convergence of means: R-1 = 0.021780 after 288 accepted steps
2023-07-02 10:24:45,631 [mcmc] - Updated covariance matrix of proposal pdf.
2023-07-02 10:24:45,631 [mcmc] array([[0.01227921]])
2023-07-02 10:24:45,642 [mcmc] Dumped checkpoint and progress info, and current covmat.
2023-07-02 10:24:45,642 [model] Posterior to be computed for parameters {'Omega_m': 0.8435970413490674}
2023-07-02 10:24:45,642 [prior] Evaluating prior at array([0.84359704])
2023-07-02 10:24:45,642 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:45,642 [model] Got input parameters: {'Omega_m': 0.8435970413490674, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:45,642 [classy] Got parameters {'Omega_m': 0.8435970413490674, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:45,642 [classy] Computing new state
2023-07-02 10:24:45,642 [classy] Setting parameters: {'Omega_m': 0.8435970413490674, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:45,691 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 109.3727185737638}
2023-07-02 10:24:45,691 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:45,693 [bao_likelihood.baolikelihood] Computed log-likelihood = -6.90193
2023-07-02 10:24:45,693 [model] Computed derived parameters: {}
2023-07-02 10:24:45,693 [model] Posterior to be computed for parameters {'Omega_m': 0.4064486755755495}
2023-07-02 10:24:45,693 [prior] Evaluating prior at array([0.40644868])
2023-07-02 10:24:45,693 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:45,693 [model] Got input parameters: {'Omega_m': 0.4064486755755495, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:45,693 [classy] Got parameters {'Omega_m': 0.4064486755755495, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:45,693 [classy] Computing new state
2023-07-02 10:24:45,693 [classy] Setting parameters: {'Omega_m': 0.4064486755755495, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:45,739 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 137.25818631690277}
2023-07-02 10:24:45,739 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:45,742 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.43689
2023-07-02 10:24:45,742 [model] Computed derived parameters: {}
2023-07-02 10:24:45,742 [mcmc] New sample, #361:
Omega_m:0.442076
2023-07-02 10:24:45,742 [model] Posterior to be computed for parameters {'Omega_m': 0.3542198243687988}
2023-07-02 10:24:45,742 [prior] Evaluating prior at array([0.35421982])
2023-07-02 10:24:45,742 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:45,742 [model] Got input parameters: {'Omega_m': 0.3542198243687988, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:45,742 [classy] Got parameters {'Omega_m': 0.3542198243687988, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:45,742 [classy] Computing new state
2023-07-02 10:24:45,743 [classy] Setting parameters: {'Omega_m': 0.3542198243687988, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:45,789 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.516392738315}
2023-07-02 10:24:45,790 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:45,792 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0968603
2023-07-02 10:24:45,792 [model] Computed derived parameters: {}
2023-07-02 10:24:45,792 [mcmc] New sample, #362:
Omega_m:0.4064487
2023-07-02 10:24:45,793 [model] Posterior to be computed for parameters {'Omega_m': -0.825210572759129}
2023-07-02 10:24:45,793 [prior] Evaluating prior at array([-0.82521057])
2023-07-02 10:24:45,793 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:45,793 [model] Posterior to be computed for parameters {'Omega_m': 0.6301092151028064}
2023-07-02 10:24:45,793 [prior] Evaluating prior at array([0.63010922])
2023-07-02 10:24:45,793 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:45,793 [model] Got input parameters: {'Omega_m': 0.6301092151028064, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:45,793 [classy] Got parameters {'Omega_m': 0.6301092151028064, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:45,793 [classy] Computing new state
2023-07-02 10:24:45,793 [classy] Setting parameters: {'Omega_m': 0.6301092151028064, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:45,840 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 120.4016185920272}
2023-07-02 10:24:45,840 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:45,843 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.33023
2023-07-02 10:24:45,843 [model] Computed derived parameters: {}
2023-07-02 10:24:45,843 [model] Posterior to be computed for parameters {'Omega_m': 0.36541186440924106}
2023-07-02 10:24:45,843 [prior] Evaluating prior at array([0.36541186])
2023-07-02 10:24:45,843 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:45,843 [model] Got input parameters: {'Omega_m': 0.36541186440924106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:45,843 [classy] Got parameters {'Omega_m': 0.36541186440924106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:45,843 [classy] Computing new state
2023-07-02 10:24:45,843 [classy] Setting parameters: {'Omega_m': 0.36541186440924106, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:45,891 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.3312261925746}
2023-07-02 10:24:45,891 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:45,894 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.151734
2023-07-02 10:24:45,894 [model] Computed derived parameters: {}
2023-07-02 10:24:45,894 [mcmc] New sample, #363:
Omega_m:0.3542198
2023-07-02 10:24:45,894 [model] Posterior to be computed for parameters {'Omega_m': 0.31810889303016626}
2023-07-02 10:24:45,894 [prior] Evaluating prior at array([0.31810889])
2023-07-02 10:24:45,894 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:45,894 [model] Got input parameters: {'Omega_m': 0.31810889303016626, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:45,894 [classy] Got parameters {'Omega_m': 0.31810889303016626, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:45,894 [classy] Computing new state
2023-07-02 10:24:45,894 [classy] Setting parameters: {'Omega_m': 0.31810889303016626, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:45,942 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.58866582691934}
2023-07-02 10:24:45,942 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:45,944 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00211558
2023-07-02 10:24:45,945 [model] Computed derived parameters: {}
2023-07-02 10:24:45,945 [mcmc] New sample, #364:
Omega_m:0.3654119
2023-07-02 10:24:45,945 [model] Posterior to be computed for parameters {'Omega_m': 0.3858272350607616}
2023-07-02 10:24:45,945 [prior] Evaluating prior at array([0.38582724])
2023-07-02 10:24:45,945 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:45,945 [model] Got input parameters: {'Omega_m': 0.3858272350607616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:45,945 [classy] Got parameters {'Omega_m': 0.3858272350607616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:45,945 [classy] Computing new state
2023-07-02 10:24:45,945 [classy] Setting parameters: {'Omega_m': 0.3858272350607616, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:45,992 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 139.2538704097351}
2023-07-02 10:24:45,993 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:45,995 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.278284
2023-07-02 10:24:45,995 [model] Computed derived parameters: {}
2023-07-02 10:24:45,995 [mcmc] New sample, #365:
Omega_m:0.3181089
2023-07-02 10:24:45,995 [model] Posterior to be computed for parameters {'Omega_m': 0.23990994328428356}
2023-07-02 10:24:45,995 [prior] Evaluating prior at array([0.23990994])
2023-07-02 10:24:45,995 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:45,995 [model] Got input parameters: {'Omega_m': 0.23990994328428356, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:45,995 [classy] Got parameters {'Omega_m': 0.23990994328428356, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:45,996 [classy] Computing new state
2023-07-02 10:24:45,996 [classy] Setting parameters: {'Omega_m': 0.23990994328428356, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:46,044 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 157.01991793320798}
2023-07-02 10:24:46,044 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:46,045 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.392574
2023-07-02 10:24:46,046 [model] Computed derived parameters: {}
2023-07-02 10:24:46,046 [mcmc] New sample, #366:
Omega_m:0.3858272
2023-07-02 10:24:46,046 [model] Posterior to be computed for parameters {'Omega_m': -0.06002103424233951}
2023-07-02 10:24:46,046 [prior] Evaluating prior at array([-0.06002103])
2023-07-02 10:24:46,046 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:46,046 [model] Posterior to be computed for parameters {'Omega_m': 0.19074137997623872}
2023-07-02 10:24:46,046 [prior] Evaluating prior at array([0.19074138])
2023-07-02 10:24:46,046 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:46,046 [model] Got input parameters: {'Omega_m': 0.19074137997623872, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:46,046 [classy] Got parameters {'Omega_m': 0.19074137997623872, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:46,046 [classy] Computing new state
2023-07-02 10:24:46,046 [classy] Setting parameters: {'Omega_m': 0.19074137997623872, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:46,095 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 165.11446630524884}
2023-07-02 10:24:46,095 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:46,097 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.28469
2023-07-02 10:24:46,097 [model] Computed derived parameters: {}
2023-07-02 10:24:46,097 [model] Posterior to be computed for parameters {'Omega_m': -0.6661765573925307}
2023-07-02 10:24:46,097 [prior] Evaluating prior at array([-0.66617656])
2023-07-02 10:24:46,097 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:46,097 [model] Posterior to be computed for parameters {'Omega_m': -0.42227852613169975}
2023-07-02 10:24:46,098 [prior] Evaluating prior at array([-0.42227853])
2023-07-02 10:24:46,098 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:46,098 [model] Posterior to be computed for parameters {'Omega_m': 0.3236637659425725}
2023-07-02 10:24:46,098 [prior] Evaluating prior at array([0.32366377])
2023-07-02 10:24:46,098 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:46,098 [model] Got input parameters: {'Omega_m': 0.3236637659425725, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:46,098 [classy] Got parameters {'Omega_m': 0.3236637659425725, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:46,098 [classy] Computing new state
2023-07-02 10:24:46,098 [classy] Setting parameters: {'Omega_m': 0.3236637659425725, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:46,146 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.9358856363259}
2023-07-02 10:24:46,146 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:46,148 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00765812
2023-07-02 10:24:46,148 [model] Computed derived parameters: {}
2023-07-02 10:24:46,148 [mcmc] New sample, #367:
Omega_m:0.2399099
2023-07-02 10:24:46,148 [model] Posterior to be computed for parameters {'Omega_m': -0.053288318087928666}
2023-07-02 10:24:46,148 [prior] Evaluating prior at array([-0.05328832])
2023-07-02 10:24:46,148 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:46,148 [model] Posterior to be computed for parameters {'Omega_m': 0.3625688242758681}
2023-07-02 10:24:46,148 [prior] Evaluating prior at array([0.36256882])
2023-07-02 10:24:46,148 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:46,148 [model] Got input parameters: {'Omega_m': 0.3625688242758681, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:46,148 [classy] Got parameters {'Omega_m': 0.3625688242758681, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:46,148 [classy] Computing new state
2023-07-02 10:24:46,149 [classy] Setting parameters: {'Omega_m': 0.3625688242758681, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:46,197 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.6290574700278}
2023-07-02 10:24:46,197 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:46,199 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.13677
2023-07-02 10:24:46,199 [model] Computed derived parameters: {}
2023-07-02 10:24:46,199 [mcmc] New sample, #368:
Omega_m:0.3236638
2023-07-02 10:24:46,199 [model] Posterior to be computed for parameters {'Omega_m': 0.7279382574665947}
2023-07-02 10:24:46,200 [prior] Evaluating prior at array([0.72793826])
2023-07-02 10:24:46,200 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:46,200 [model] Got input parameters: {'Omega_m': 0.7279382574665947, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:46,200 [classy] Got parameters {'Omega_m': 0.7279382574665947, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:46,200 [classy] Computing new state
2023-07-02 10:24:46,200 [classy] Setting parameters: {'Omega_m': 0.7279382574665947, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:46,248 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 114.91095653141669}
2023-07-02 10:24:46,248 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:46,250 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.92761
2023-07-02 10:24:46,250 [model] Computed derived parameters: {}
2023-07-02 10:24:46,251 [model] Posterior to be computed for parameters {'Omega_m': 0.5291711558914336}
2023-07-02 10:24:46,251 [prior] Evaluating prior at array([0.52917116])
2023-07-02 10:24:46,251 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:46,251 [model] Got input parameters: {'Omega_m': 0.5291711558914336, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:46,251 [classy] Got parameters {'Omega_m': 0.5291711558914336, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:46,251 [classy] Computing new state
2023-07-02 10:24:46,251 [classy] Setting parameters: {'Omega_m': 0.5291711558914336, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:46,300 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 127.10279554865743}
2023-07-02 10:24:46,300 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:46,302 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.83308
2023-07-02 10:24:46,302 [model] Computed derived parameters: {}
2023-07-02 10:24:46,302 [mcmc] New sample, #369:
Omega_m:0.3625688
2023-07-02 10:24:46,302 [model] Posterior to be computed for parameters {'Omega_m': 0.513741759927027}
2023-07-02 10:24:46,302 [prior] Evaluating prior at array([0.51374176])
2023-07-02 10:24:46,303 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:46,303 [model] Got input parameters: {'Omega_m': 0.513741759927027, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:46,303 [classy] Got parameters {'Omega_m': 0.513741759927027, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:46,303 [classy] Computing new state
2023-07-02 10:24:46,303 [classy] Setting parameters: {'Omega_m': 0.513741759927027, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:46,348 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 128.24218302279536}
2023-07-02 10:24:46,348 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:46,351 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.62553
2023-07-02 10:24:46,351 [model] Computed derived parameters: {}
2023-07-02 10:24:46,351 [mcmc] New sample, #370:
Omega_m:0.5291712
2023-07-02 10:24:46,351 [model] Posterior to be computed for parameters {'Omega_m': 0.3273789263356756}
2023-07-02 10:24:46,351 [prior] Evaluating prior at array([0.32737893])
2023-07-02 10:24:46,351 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:46,352 [model] Got input parameters: {'Omega_m': 0.3273789263356756, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:46,352 [classy] Got parameters {'Omega_m': 0.3273789263356756, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:46,352 [classy] Computing new state
2023-07-02 10:24:46,352 [classy] Setting parameters: {'Omega_m': 0.3273789263356756, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:46,403 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.50485987672872}
2023-07-02 10:24:46,403 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:46,406 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0133186
2023-07-02 10:24:46,406 [model] Computed derived parameters: {}
2023-07-02 10:24:46,406 [mcmc] New sample, #371:
Omega_m:0.5137418
2023-07-02 10:24:46,406 [model] Posterior to be computed for parameters {'Omega_m': 0.46274783822488363}
2023-07-02 10:24:46,406 [prior] Evaluating prior at array([0.46274784])
2023-07-02 10:24:46,406 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:46,406 [model] Got input parameters: {'Omega_m': 0.46274783822488363, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:46,406 [classy] Got parameters {'Omega_m': 0.46274783822488363, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:46,406 [classy] Computing new state
2023-07-02 10:24:46,407 [classy] Setting parameters: {'Omega_m': 0.46274783822488363, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:46,455 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 132.26918809551628}
2023-07-02 10:24:46,456 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:46,458 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.99684
2023-07-02 10:24:46,458 [model] Computed derived parameters: {}
2023-07-02 10:24:46,458 [model] Posterior to be computed for parameters {'Omega_m': 0.7870876928577524}
2023-07-02 10:24:46,458 [prior] Evaluating prior at array([0.78708769])
2023-07-02 10:24:46,458 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:46,458 [model] Got input parameters: {'Omega_m': 0.7870876928577524, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:46,458 [classy] Got parameters {'Omega_m': 0.7870876928577524, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:46,458 [classy] Computing new state
2023-07-02 10:24:46,458 [classy] Setting parameters: {'Omega_m': 0.7870876928577524, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:46,506 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 111.96634165199276}
2023-07-02 10:24:46,506 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:46,508 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.93031
2023-07-02 10:24:46,508 [model] Computed derived parameters: {}
2023-07-02 10:24:46,508 [model] Posterior to be computed for parameters {'Omega_m': -0.1134078998319436}
2023-07-02 10:24:46,508 [prior] Evaluating prior at array([-0.1134079])
2023-07-02 10:24:46,508 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:46,508 [model] Posterior to be computed for parameters {'Omega_m': 0.29685351775962004}
2023-07-02 10:24:46,508 [prior] Evaluating prior at array([0.29685352])
2023-07-02 10:24:46,508 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:46,508 [model] Got input parameters: {'Omega_m': 0.29685351775962004, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:46,508 [classy] Got parameters {'Omega_m': 0.29685351775962004, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:46,508 [classy] Computing new state
2023-07-02 10:24:46,508 [classy] Setting parameters: {'Omega_m': 0.29685351775962004, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:46,557 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.18375893023773}
2023-07-02 10:24:46,557 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:46,559 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0157872
2023-07-02 10:24:46,559 [model] Computed derived parameters: {}
2023-07-02 10:24:46,559 [mcmc] New sample, #372:
Omega_m:0.3273789
2023-07-02 10:24:46,559 [model] Posterior to be computed for parameters {'Omega_m': 0.19825351859332874}
2023-07-02 10:24:46,559 [prior] Evaluating prior at array([0.19825352])
2023-07-02 10:24:46,559 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:46,559 [model] Got input parameters: {'Omega_m': 0.19825351859332874, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:46,560 [classy] Got parameters {'Omega_m': 0.19825351859332874, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:46,560 [classy] Computing new state
2023-07-02 10:24:46,560 [classy] Setting parameters: {'Omega_m': 0.19825351859332874, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:46,607 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 163.7804993267242}
2023-07-02 10:24:46,607 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:46,609 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.10386
2023-07-02 10:24:46,609 [model] Computed derived parameters: {}
2023-07-02 10:24:46,609 [model] Posterior to be computed for parameters {'Omega_m': 0.49574491218329597}
2023-07-02 10:24:46,609 [prior] Evaluating prior at array([0.49574491])
2023-07-02 10:24:46,609 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:46,609 [model] Got input parameters: {'Omega_m': 0.49574491218329597, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:46,609 [classy] Got parameters {'Omega_m': 0.49574491218329597, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:46,609 [classy] Computing new state
2023-07-02 10:24:46,609 [classy] Setting parameters: {'Omega_m': 0.49574491218329597, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:46,656 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 129.61574886231938}
2023-07-02 10:24:46,656 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:46,658 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.39288
2023-07-02 10:24:46,658 [model] Computed derived parameters: {}
2023-07-02 10:24:46,658 [model] Posterior to be computed for parameters {'Omega_m': 0.36113974782840286}
2023-07-02 10:24:46,658 [prior] Evaluating prior at array([0.36113975])
2023-07-02 10:24:46,659 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:46,659 [model] Got input parameters: {'Omega_m': 0.36113974782840286, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:46,659 [classy] Got parameters {'Omega_m': 0.36113974782840286, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:46,659 [classy] Computing new state
2023-07-02 10:24:46,659 [classy] Setting parameters: {'Omega_m': 0.36113974782840286, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:46,706 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.77958037711784}
2023-07-02 10:24:46,706 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:46,708 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.129508
2023-07-02 10:24:46,708 [model] Computed derived parameters: {}
2023-07-02 10:24:46,708 [mcmc] New sample, #373:
Omega_m:0.2968535
2023-07-02 10:24:46,708 [model] Posterior to be computed for parameters {'Omega_m': 0.7078616666284414}
2023-07-02 10:24:46,708 [prior] Evaluating prior at array([0.70786167])
2023-07-02 10:24:46,708 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:46,708 [model] Got input parameters: {'Omega_m': 0.7078616666284414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:46,709 [classy] Got parameters {'Omega_m': 0.7078616666284414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:46,709 [classy] Computing new state
2023-07-02 10:24:46,709 [classy] Setting parameters: {'Omega_m': 0.7078616666284414, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:46,754 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 115.9702379771254}
2023-07-02 10:24:46,754 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:46,756 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.59229
2023-07-02 10:24:46,756 [model] Computed derived parameters: {}
2023-07-02 10:24:46,756 [model] Posterior to be computed for parameters {'Omega_m': 0.44567217453858965}
2023-07-02 10:24:46,756 [prior] Evaluating prior at array([0.44567217])
2023-07-02 10:24:46,756 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:46,756 [model] Got input parameters: {'Omega_m': 0.44567217453858965, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:46,756 [classy] Got parameters {'Omega_m': 0.44567217453858965, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:46,757 [classy] Computing new state
2023-07-02 10:24:46,757 [classy] Setting parameters: {'Omega_m': 0.44567217453858965, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:46,803 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 133.7168709517539}
2023-07-02 10:24:46,803 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:46,805 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.809866
2023-07-02 10:24:46,805 [model] Computed derived parameters: {}
2023-07-02 10:24:46,805 [model] Posterior to be computed for parameters {'Omega_m': 0.8070386978968211}
2023-07-02 10:24:46,805 [prior] Evaluating prior at array([0.8070387])
2023-07-02 10:24:46,805 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:46,805 [model] Got input parameters: {'Omega_m': 0.8070386978968211, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:46,805 [classy] Got parameters {'Omega_m': 0.8070386978968211, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:46,805 [classy] Computing new state
2023-07-02 10:24:46,805 [classy] Setting parameters: {'Omega_m': 0.8070386978968211, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:46,851 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 111.02770122093526}
2023-07-02 10:24:46,851 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:46,853 [bao_likelihood.baolikelihood] Computed log-likelihood = -6.27221
2023-07-02 10:24:46,853 [model] Computed derived parameters: {}
2023-07-02 10:24:46,853 [model] Posterior to be computed for parameters {'Omega_m': 0.49356300379523177}
2023-07-02 10:24:46,853 [prior] Evaluating prior at array([0.493563])
2023-07-02 10:24:46,853 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:46,853 [model] Got input parameters: {'Omega_m': 0.49356300379523177, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:46,853 [classy] Got parameters {'Omega_m': 0.49356300379523177, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:46,853 [classy] Computing new state
2023-07-02 10:24:46,853 [classy] Setting parameters: {'Omega_m': 0.49356300379523177, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:46,900 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 129.78566909774568}
2023-07-02 10:24:46,900 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:46,902 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.36543
2023-07-02 10:24:46,902 [model] Computed derived parameters: {}
2023-07-02 10:24:46,902 [mcmc] New sample, #374:
Omega_m:0.3611397
2023-07-02 10:24:46,903 [model] Posterior to be computed for parameters {'Omega_m': 0.3533511950696836}
2023-07-02 10:24:46,903 [prior] Evaluating prior at array([0.3533512])
2023-07-02 10:24:46,903 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:46,903 [model] Got input parameters: {'Omega_m': 0.3533511950696836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:46,903 [classy] Got parameters {'Omega_m': 0.3533511950696836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:46,903 [classy] Computing new state
2023-07-02 10:24:46,903 [classy] Setting parameters: {'Omega_m': 0.3533511950696836, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:46,950 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.60981628767135}
2023-07-02 10:24:46,950 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:46,952 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0930644
2023-07-02 10:24:46,952 [model] Computed derived parameters: {}
2023-07-02 10:24:46,952 [mcmc] New sample, #375:
Omega_m:0.493563
2023-07-02 10:24:46,952 [model] Posterior to be computed for parameters {'Omega_m': 0.48853501364072716}
2023-07-02 10:24:46,952 [prior] Evaluating prior at array([0.48853501])
2023-07-02 10:24:46,953 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:46,953 [model] Got input parameters: {'Omega_m': 0.48853501364072716, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:46,953 [classy] Got parameters {'Omega_m': 0.48853501364072716, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:46,953 [classy] Computing new state
2023-07-02 10:24:46,953 [classy] Setting parameters: {'Omega_m': 0.48853501364072716, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:47,000 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.18016375046466}
2023-07-02 10:24:47,001 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:47,003 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.30279
2023-07-02 10:24:47,003 [model] Computed derived parameters: {}
2023-07-02 10:24:47,003 [model] Posterior to be computed for parameters {'Omega_m': 0.24802296155161552}
2023-07-02 10:24:47,003 [prior] Evaluating prior at array([0.24802296])
2023-07-02 10:24:47,003 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:47,003 [model] Got input parameters: {'Omega_m': 0.24802296155161552, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:47,003 [classy] Got parameters {'Omega_m': 0.24802296155161552, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:47,003 [classy] Computing new state
2023-07-02 10:24:47,003 [classy] Setting parameters: {'Omega_m': 0.24802296155161552, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:47,054 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 155.81409607927193}
2023-07-02 10:24:47,054 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:47,056 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.30262
2023-07-02 10:24:47,056 [model] Computed derived parameters: {}
2023-07-02 10:24:47,056 [model] Posterior to be computed for parameters {'Omega_m': 0.4685508887790934}
2023-07-02 10:24:47,056 [prior] Evaluating prior at array([0.46855089])
2023-07-02 10:24:47,057 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:47,057 [model] Got input parameters: {'Omega_m': 0.4685508887790934, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:47,057 [classy] Got parameters {'Omega_m': 0.4685508887790934, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:47,057 [classy] Computing new state
2023-07-02 10:24:47,057 [classy] Setting parameters: {'Omega_m': 0.4685508887790934, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:47,104 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 131.7891743339365}
2023-07-02 10:24:47,104 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:47,106 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.06334
2023-07-02 10:24:47,106 [model] Computed derived parameters: {}
2023-07-02 10:24:47,106 [model] Posterior to be computed for parameters {'Omega_m': 0.2900957373277737}
2023-07-02 10:24:47,106 [prior] Evaluating prior at array([0.29009574])
2023-07-02 10:24:47,106 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:47,106 [model] Got input parameters: {'Omega_m': 0.2900957373277737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:47,106 [classy] Got parameters {'Omega_m': 0.2900957373277737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:47,106 [classy] Computing new state
2023-07-02 10:24:47,106 [classy] Setting parameters: {'Omega_m': 0.2900957373277737, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:47,153 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.04303273934713}
2023-07-02 10:24:47,153 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:47,155 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0327393
2023-07-02 10:24:47,155 [model] Computed derived parameters: {}
2023-07-02 10:24:47,155 [mcmc] New sample, #376:
Omega_m:0.3533512
2023-07-02 10:24:47,155 [model] Posterior to be computed for parameters {'Omega_m': 0.29086613306917863}
2023-07-02 10:24:47,155 [prior] Evaluating prior at array([0.29086613])
2023-07-02 10:24:47,155 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:47,155 [model] Got input parameters: {'Omega_m': 0.29086613306917863, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:47,155 [classy] Got parameters {'Omega_m': 0.29086613306917863, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:47,155 [classy] Computing new state
2023-07-02 10:24:47,155 [classy] Setting parameters: {'Omega_m': 0.29086613306917863, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:47,201 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.94420415465325}
2023-07-02 10:24:47,202 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:47,204 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0304781
2023-07-02 10:24:47,204 [model] Computed derived parameters: {}
2023-07-02 10:24:47,204 [mcmc] New sample, #377:
Omega_m:0.2900957
2023-07-02 10:24:47,204 [model] Posterior to be computed for parameters {'Omega_m': 0.16643799559835912}
2023-07-02 10:24:47,204 [prior] Evaluating prior at array([0.166438])
2023-07-02 10:24:47,204 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:47,204 [model] Got input parameters: {'Omega_m': 0.16643799559835912, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:47,204 [classy] Got parameters {'Omega_m': 0.16643799559835912, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:47,204 [classy] Computing new state
2023-07-02 10:24:47,204 [classy] Setting parameters: {'Omega_m': 0.16643799559835912, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:47,251 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 169.7140955961042}
2023-07-02 10:24:47,251 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:47,253 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.00712
2023-07-02 10:24:47,253 [model] Computed derived parameters: {}
2023-07-02 10:24:47,253 [model] Posterior to be computed for parameters {'Omega_m': 0.019484940426982178}
2023-07-02 10:24:47,253 [prior] Evaluating prior at array([0.01948494])
2023-07-02 10:24:47,253 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:47,253 [model] Posterior to be computed for parameters {'Omega_m': 0.29936881835201934}
2023-07-02 10:24:47,253 [prior] Evaluating prior at array([0.29936882])
2023-07-02 10:24:47,253 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:47,253 [model] Got input parameters: {'Omega_m': 0.29936881835201934, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:47,253 [classy] Got parameters {'Omega_m': 0.29936881835201934, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:47,253 [classy] Computing new state
2023-07-02 10:24:47,253 [classy] Setting parameters: {'Omega_m': 0.29936881835201934, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:47,300 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.8682649386721}
2023-07-02 10:24:47,300 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:47,302 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0111041
2023-07-02 10:24:47,302 [model] Computed derived parameters: {}
2023-07-02 10:24:47,302 [mcmc] New sample, #378:
Omega_m:0.2908661
2023-07-02 10:24:47,302 [model] Posterior to be computed for parameters {'Omega_m': 0.10610276849223887}
2023-07-02 10:24:47,302 [prior] Evaluating prior at array([0.10610277])
2023-07-02 10:24:47,302 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:47,302 [model] Got input parameters: {'Omega_m': 0.10610276849223887, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:47,303 [classy] Got parameters {'Omega_m': 0.10610276849223887, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:47,303 [classy] Computing new state
2023-07-02 10:24:47,303 [classy] Setting parameters: {'Omega_m': 0.10610276849223887, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:47,350 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 183.53410145110618}
2023-07-02 10:24:47,350 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:47,352 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.05448
2023-07-02 10:24:47,352 [model] Computed derived parameters: {}
2023-07-02 10:24:47,352 [model] Posterior to be computed for parameters {'Omega_m': -0.04894469503475479}
2023-07-02 10:24:47,352 [prior] Evaluating prior at array([-0.0489447])
2023-07-02 10:24:47,352 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:47,352 [model] Posterior to be computed for parameters {'Omega_m': 0.3589213280872786}
2023-07-02 10:24:47,352 [prior] Evaluating prior at array([0.35892133])
2023-07-02 10:24:47,352 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:47,352 [model] Got input parameters: {'Omega_m': 0.3589213280872786, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:47,352 [classy] Got parameters {'Omega_m': 0.3589213280872786, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:47,352 [classy] Computing new state
2023-07-02 10:24:47,352 [classy] Setting parameters: {'Omega_m': 0.3589213280872786, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:47,399 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.01435276346368}
2023-07-02 10:24:47,399 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:47,401 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.118583
2023-07-02 10:24:47,401 [model] Computed derived parameters: {}
2023-07-02 10:24:47,401 [mcmc] New sample, #379:
Omega_m:0.2993688
2023-07-02 10:24:47,401 [model] Posterior to be computed for parameters {'Omega_m': 0.23314310403140961}
2023-07-02 10:24:47,401 [prior] Evaluating prior at array([0.2331431])
2023-07-02 10:24:47,401 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:47,401 [model] Got input parameters: {'Omega_m': 0.23314310403140961, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:47,401 [classy] Got parameters {'Omega_m': 0.23314310403140961, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:47,401 [classy] Computing new state
2023-07-02 10:24:47,401 [classy] Setting parameters: {'Omega_m': 0.23314310403140961, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:47,447 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 158.05126272450426}
2023-07-02 10:24:47,447 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:47,449 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.478511
2023-07-02 10:24:47,449 [model] Computed derived parameters: {}
2023-07-02 10:24:47,449 [mcmc] New sample, #380:
Omega_m:0.3589213
2023-07-02 10:24:47,449 [model] Posterior to be computed for parameters {'Omega_m': 0.1594760680290367}
2023-07-02 10:24:47,449 [prior] Evaluating prior at array([0.15947607])
2023-07-02 10:24:47,449 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:47,449 [model] Got input parameters: {'Omega_m': 0.1594760680290367, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:47,449 [classy] Got parameters {'Omega_m': 0.1594760680290367, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:47,449 [classy] Computing new state
2023-07-02 10:24:47,449 [classy] Setting parameters: {'Omega_m': 0.1594760680290367, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:47,495 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 171.1196155937437}
2023-07-02 10:24:47,495 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:47,497 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.25789
2023-07-02 10:24:47,497 [model] Computed derived parameters: {}
2023-07-02 10:24:47,497 [model] Posterior to be computed for parameters {'Omega_m': 0.29087528165249904}
2023-07-02 10:24:47,497 [prior] Evaluating prior at array([0.29087528])
2023-07-02 10:24:47,497 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:47,497 [model] Got input parameters: {'Omega_m': 0.29087528165249904, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:47,497 [classy] Got parameters {'Omega_m': 0.29087528165249904, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:47,497 [classy] Computing new state
2023-07-02 10:24:47,497 [classy] Setting parameters: {'Omega_m': 0.29087528165249904, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:47,544 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.94302977693494}
2023-07-02 10:24:47,544 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:47,546 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0304516
2023-07-02 10:24:47,546 [model] Computed derived parameters: {}
2023-07-02 10:24:47,546 [mcmc] New sample, #381:
Omega_m:0.2331431
2023-07-02 10:24:47,546 [model] Posterior to be computed for parameters {'Omega_m': 0.3586233326772683}
2023-07-02 10:24:47,546 [prior] Evaluating prior at array([0.35862333])
2023-07-02 10:24:47,546 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:47,546 [model] Got input parameters: {'Omega_m': 0.3586233326772683, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:47,546 [classy] Got parameters {'Omega_m': 0.3586233326772683, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:47,546 [classy] Computing new state
2023-07-02 10:24:47,546 [classy] Setting parameters: {'Omega_m': 0.3586233326772683, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:47,593 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.04599362070954}
2023-07-02 10:24:47,593 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:47,595 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.117148
2023-07-02 10:24:47,595 [model] Computed derived parameters: {}
2023-07-02 10:24:47,595 [mcmc] New sample, #382:
Omega_m:0.2908753
2023-07-02 10:24:47,595 [model] Posterior to be computed for parameters {'Omega_m': 0.4357743522455158}
2023-07-02 10:24:47,595 [prior] Evaluating prior at array([0.43577435])
2023-07-02 10:24:47,595 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:47,595 [model] Got input parameters: {'Omega_m': 0.4357743522455158, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:47,596 [classy] Got parameters {'Omega_m': 0.4357743522455158, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:47,596 [classy] Computing new state
2023-07-02 10:24:47,596 [classy] Setting parameters: {'Omega_m': 0.4357743522455158, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:47,643 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 134.58111385476712}
2023-07-02 10:24:47,643 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:47,645 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.707876
2023-07-02 10:24:47,645 [model] Computed derived parameters: {}
2023-07-02 10:24:47,645 [model] Posterior to be computed for parameters {'Omega_m': 0.18445325114990346}
2023-07-02 10:24:47,645 [prior] Evaluating prior at array([0.18445325])
2023-07-02 10:24:47,645 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:47,645 [model] Got input parameters: {'Omega_m': 0.18445325114990346, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:47,645 [classy] Got parameters {'Omega_m': 0.18445325114990346, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:47,645 [classy] Computing new state
2023-07-02 10:24:47,645 [classy] Setting parameters: {'Omega_m': 0.18445325114990346, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:47,692 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 166.26151766317363}
2023-07-02 10:24:47,692 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:47,694 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.45058
2023-07-02 10:24:47,694 [model] Computed derived parameters: {}
2023-07-02 10:24:47,694 [mcmc] New sample, #383:
Omega_m:0.3586233
2023-07-02 10:24:47,694 [model] Posterior to be computed for parameters {'Omega_m': 0.10190578484306648}
2023-07-02 10:24:47,694 [prior] Evaluating prior at array([0.10190578])
2023-07-02 10:24:47,694 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:47,694 [model] Got input parameters: {'Omega_m': 0.10190578484306648, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:47,694 [classy] Got parameters {'Omega_m': 0.10190578484306648, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:47,694 [classy] Computing new state
2023-07-02 10:24:47,694 [classy] Setting parameters: {'Omega_m': 0.10190578484306648, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:47,741 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 184.65866008830082}
2023-07-02 10:24:47,741 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:47,743 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.35742
2023-07-02 10:24:47,743 [model] Computed derived parameters: {}
2023-07-02 10:24:47,743 [model] Posterior to be computed for parameters {'Omega_m': -0.014892118732253323}
2023-07-02 10:24:47,743 [prior] Evaluating prior at array([-0.01489212])
2023-07-02 10:24:47,744 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:47,744 [model] Posterior to be computed for parameters {'Omega_m': 0.3027699542997853}
2023-07-02 10:24:47,744 [prior] Evaluating prior at array([0.30276995])
2023-07-02 10:24:47,744 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:47,744 [model] Got input parameters: {'Omega_m': 0.3027699542997853, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:47,744 [classy] Got parameters {'Omega_m': 0.3027699542997853, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:47,744 [classy] Computing new state
2023-07-02 10:24:47,744 [classy] Setting parameters: {'Omega_m': 0.3027699542997853, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:47,791 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.44536602041893}
2023-07-02 10:24:47,791 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:47,793 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0061316
2023-07-02 10:24:47,793 [model] Computed derived parameters: {}
2023-07-02 10:24:47,793 [mcmc] New sample, #384:
Omega_m:0.1844533
2023-07-02 10:24:47,793 [model] Posterior to be computed for parameters {'Omega_m': 0.5221497456283342}
2023-07-02 10:24:47,793 [prior] Evaluating prior at array([0.52214975])
2023-07-02 10:24:47,793 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:47,793 [model] Got input parameters: {'Omega_m': 0.5221497456283342, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:47,793 [classy] Got parameters {'Omega_m': 0.5221497456283342, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:47,793 [classy] Computing new state
2023-07-02 10:24:47,793 [classy] Setting parameters: {'Omega_m': 0.5221497456283342, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:47,841 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 127.61706684688846}
2023-07-02 10:24:47,841 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:47,842 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.73775
2023-07-02 10:24:47,842 [model] Computed derived parameters: {}
2023-07-02 10:24:47,843 [model] Posterior to be computed for parameters {'Omega_m': 0.27016429433800965}
2023-07-02 10:24:47,843 [prior] Evaluating prior at array([0.27016429])
2023-07-02 10:24:47,843 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:47,843 [model] Got input parameters: {'Omega_m': 0.27016429433800965, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:47,843 [classy] Got parameters {'Omega_m': 0.27016429433800965, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:47,843 [classy] Computing new state
2023-07-02 10:24:47,843 [classy] Setting parameters: {'Omega_m': 0.27016429433800965, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:47,889 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.6819830276757}
2023-07-02 10:24:47,889 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:47,891 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.122776
2023-07-02 10:24:47,891 [model] Computed derived parameters: {}
2023-07-02 10:24:47,891 [mcmc] New sample, #385:
Omega_m:0.30277
2023-07-02 10:24:47,891 [model] Posterior to be computed for parameters {'Omega_m': -0.047168943017101006}
2023-07-02 10:24:47,891 [prior] Evaluating prior at array([-0.04716894])
2023-07-02 10:24:47,891 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:47,892 [model] Posterior to be computed for parameters {'Omega_m': 0.5418758249274245}
2023-07-02 10:24:47,892 [prior] Evaluating prior at array([0.54187582])
2023-07-02 10:24:47,892 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:47,892 [model] Got input parameters: {'Omega_m': 0.5418758249274245, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:47,892 [classy] Got parameters {'Omega_m': 0.5418758249274245, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:47,892 [classy] Computing new state
2023-07-02 10:24:47,892 [classy] Setting parameters: {'Omega_m': 0.5418758249274245, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:47,940 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 126.18978289073908}
2023-07-02 10:24:47,940 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:47,941 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.00904
2023-07-02 10:24:47,941 [model] Computed derived parameters: {}
2023-07-02 10:24:47,942 [model] Posterior to be computed for parameters {'Omega_m': 0.38469457092988335}
2023-07-02 10:24:47,942 [prior] Evaluating prior at array([0.38469457])
2023-07-02 10:24:47,942 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:47,942 [model] Got input parameters: {'Omega_m': 0.38469457092988335, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:47,942 [classy] Got parameters {'Omega_m': 0.38469457092988335, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:47,942 [classy] Computing new state
2023-07-02 10:24:47,942 [classy] Setting parameters: {'Omega_m': 0.38469457092988335, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:47,988 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 139.36639399621245}
2023-07-02 10:24:47,989 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:47,990 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.270429
2023-07-02 10:24:47,990 [model] Computed derived parameters: {}
2023-07-02 10:24:47,990 [mcmc] New sample, #386:
Omega_m:0.2701643
2023-07-02 10:24:47,990 [model] Posterior to be computed for parameters {'Omega_m': 0.6330271362405097}
2023-07-02 10:24:47,991 [prior] Evaluating prior at array([0.63302714])
2023-07-02 10:24:47,991 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:47,991 [model] Got input parameters: {'Omega_m': 0.6330271362405097, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:47,991 [classy] Got parameters {'Omega_m': 0.6330271362405097, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:47,991 [classy] Computing new state
2023-07-02 10:24:47,991 [classy] Setting parameters: {'Omega_m': 0.6330271362405097, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:48,037 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 120.22501072059242}
2023-07-02 10:24:48,038 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:48,039 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.37627
2023-07-02 10:24:48,039 [model] Computed derived parameters: {}
2023-07-02 10:24:48,039 [model] Posterior to be computed for parameters {'Omega_m': 0.4557561577607229}
2023-07-02 10:24:48,039 [prior] Evaluating prior at array([0.45575616])
2023-07-02 10:24:48,040 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:48,040 [model] Got input parameters: {'Omega_m': 0.4557561577607229, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:48,040 [classy] Got parameters {'Omega_m': 0.4557561577607229, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:48,040 [classy] Computing new state
2023-07-02 10:24:48,040 [classy] Setting parameters: {'Omega_m': 0.4557561577607229, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:48,087 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 132.85547616605194}
2023-07-02 10:24:48,087 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:48,089 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.918672
2023-07-02 10:24:48,089 [model] Computed derived parameters: {}
2023-07-02 10:24:48,089 [mcmc] New sample, #387:
Omega_m:0.3846946
2023-07-02 10:24:48,089 [model] Posterior to be computed for parameters {'Omega_m': 0.5469857827901178}
2023-07-02 10:24:48,089 [prior] Evaluating prior at array([0.54698578])
2023-07-02 10:24:48,089 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:48,089 [model] Got input parameters: {'Omega_m': 0.5469857827901178, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:48,089 [classy] Got parameters {'Omega_m': 0.5469857827901178, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:48,089 [classy] Computing new state
2023-07-02 10:24:48,089 [classy] Setting parameters: {'Omega_m': 0.5469857827901178, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:48,137 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 125.82869805368978}
2023-07-02 10:24:48,137 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:48,139 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.08103
2023-07-02 10:24:48,139 [model] Computed derived parameters: {}
2023-07-02 10:24:48,139 [model] Posterior to be computed for parameters {'Omega_m': 0.7040085374841394}
2023-07-02 10:24:48,139 [prior] Evaluating prior at array([0.70400854])
2023-07-02 10:24:48,139 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:48,139 [model] Got input parameters: {'Omega_m': 0.7040085374841394, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:48,139 [classy] Got parameters {'Omega_m': 0.7040085374841394, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:48,139 [classy] Computing new state
2023-07-02 10:24:48,139 [classy] Setting parameters: {'Omega_m': 0.7040085374841394, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:48,185 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 116.1772644949938}
2023-07-02 10:24:48,185 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:48,188 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.52829
2023-07-02 10:24:48,188 [model] Computed derived parameters: {}
2023-07-02 10:24:48,188 [model] Posterior to be computed for parameters {'Omega_m': 0.9312133826516412}
2023-07-02 10:24:48,188 [prior] Evaluating prior at array([0.93121338])
2023-07-02 10:24:48,188 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:48,188 [model] Got input parameters: {'Omega_m': 0.9312133826516412, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:48,188 [classy] Got parameters {'Omega_m': 0.9312133826516412, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:48,188 [classy] Computing new state
2023-07-02 10:24:48,188 [classy] Setting parameters: {'Omega_m': 0.9312133826516412, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:48,234 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 105.71305946488376}
2023-07-02 10:24:48,234 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:48,237 [bao_likelihood.baolikelihood] Computed log-likelihood = -8.41957
2023-07-02 10:24:48,237 [model] Computed derived parameters: {}
2023-07-02 10:24:48,237 [model] Posterior to be computed for parameters {'Omega_m': 0.6496109474993732}
2023-07-02 10:24:48,237 [prior] Evaluating prior at array([0.64961095])
2023-07-02 10:24:48,237 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:48,238 [model] Got input parameters: {'Omega_m': 0.6496109474993732, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:48,238 [classy] Got parameters {'Omega_m': 0.6496109474993732, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:48,238 [classy] Computing new state
2023-07-02 10:24:48,238 [classy] Setting parameters: {'Omega_m': 0.6496109474993732, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:48,284 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 119.23735929186631}
2023-07-02 10:24:48,284 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:48,287 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.64019
2023-07-02 10:24:48,287 [model] Computed derived parameters: {}
2023-07-02 10:24:48,287 [model] Posterior to be computed for parameters {'Omega_m': 0.5467948292106004}
2023-07-02 10:24:48,287 [prior] Evaluating prior at array([0.54679483])
2023-07-02 10:24:48,287 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:48,287 [model] Got input parameters: {'Omega_m': 0.5467948292106004, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:48,287 [classy] Got parameters {'Omega_m': 0.5467948292106004, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:48,287 [classy] Computing new state
2023-07-02 10:24:48,287 [classy] Setting parameters: {'Omega_m': 0.5467948292106004, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:48,334 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 125.84212936529887}
2023-07-02 10:24:48,334 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:48,337 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.07832
2023-07-02 10:24:48,337 [model] Computed derived parameters: {}
2023-07-02 10:24:48,337 [model] Posterior to be computed for parameters {'Omega_m': 0.5310523264166135}
2023-07-02 10:24:48,337 [prior] Evaluating prior at array([0.53105233])
2023-07-02 10:24:48,337 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:48,337 [model] Got input parameters: {'Omega_m': 0.5310523264166135, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:48,337 [classy] Got parameters {'Omega_m': 0.5310523264166135, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:48,337 [classy] Computing new state
2023-07-02 10:24:48,337 [classy] Setting parameters: {'Omega_m': 0.5310523264166135, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:48,384 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 126.96620851441739}
2023-07-02 10:24:48,384 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:48,387 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.85885
2023-07-02 10:24:48,387 [model] Computed derived parameters: {}
2023-07-02 10:24:48,387 [mcmc] New sample, #388:
Omega_m:0.4557562
2023-07-02 10:24:48,387 [model] Posterior to be computed for parameters {'Omega_m': 0.7031421232719388}
2023-07-02 10:24:48,387 [prior] Evaluating prior at array([0.70314212])
2023-07-02 10:24:48,387 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:48,387 [model] Got input parameters: {'Omega_m': 0.7031421232719388, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:48,388 [classy] Got parameters {'Omega_m': 0.7031421232719388, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:48,388 [classy] Computing new state
2023-07-02 10:24:48,388 [classy] Setting parameters: {'Omega_m': 0.7031421232719388, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:48,433 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 116.22398792518273}
2023-07-02 10:24:48,433 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:48,436 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.51392
2023-07-02 10:24:48,436 [model] Computed derived parameters: {}
2023-07-02 10:24:48,436 [model] Posterior to be computed for parameters {'Omega_m': -0.5380137777268591}
2023-07-02 10:24:48,436 [prior] Evaluating prior at array([-0.53801378])
2023-07-02 10:24:48,436 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:48,437 [model] Posterior to be computed for parameters {'Omega_m': 0.4783950117711401}
2023-07-02 10:24:48,437 [prior] Evaluating prior at array([0.47839501])
2023-07-02 10:24:48,437 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:48,437 [model] Got input parameters: {'Omega_m': 0.4783950117711401, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:48,437 [classy] Got parameters {'Omega_m': 0.4783950117711401, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:48,437 [classy] Computing new state
2023-07-02 10:24:48,437 [classy] Setting parameters: {'Omega_m': 0.4783950117711401, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:48,484 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.98820605751007}
2023-07-02 10:24:48,484 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:48,487 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.17934
2023-07-02 10:24:48,487 [model] Computed derived parameters: {}
2023-07-02 10:24:48,487 [mcmc] New sample, #389:
Omega_m:0.5310523
2023-07-02 10:24:48,487 [model] Posterior to be computed for parameters {'Omega_m': 0.7454899986882226}
2023-07-02 10:24:48,487 [prior] Evaluating prior at array([0.74549])
2023-07-02 10:24:48,487 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:48,487 [model] Got input parameters: {'Omega_m': 0.7454899986882226, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:48,487 [classy] Got parameters {'Omega_m': 0.7454899986882226, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:48,487 [classy] Computing new state
2023-07-02 10:24:48,487 [classy] Setting parameters: {'Omega_m': 0.7454899986882226, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:48,534 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 114.01062253454151}
2023-07-02 10:24:48,534 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:48,537 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.22308
2023-07-02 10:24:48,537 [model] Computed derived parameters: {}
2023-07-02 10:24:48,537 [model] Posterior to be computed for parameters {'Omega_m': 1.081436441863225}
2023-07-02 10:24:48,537 [prior] Evaluating prior at array([1.08143644])
2023-07-02 10:24:48,537 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:48,537 [model] Posterior to be computed for parameters {'Omega_m': 0.696663626285269}
2023-07-02 10:24:48,537 [prior] Evaluating prior at array([0.69666363])
2023-07-02 10:24:48,537 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:48,537 [model] Got input parameters: {'Omega_m': 0.696663626285269, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:48,537 [classy] Got parameters {'Omega_m': 0.696663626285269, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:48,537 [classy] Computing new state
2023-07-02 10:24:48,537 [classy] Setting parameters: {'Omega_m': 0.696663626285269, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:48,584 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 116.57531985859782}
2023-07-02 10:24:48,584 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:48,587 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.40665
2023-07-02 10:24:48,587 [model] Computed derived parameters: {}
2023-07-02 10:24:48,587 [model] Posterior to be computed for parameters {'Omega_m': 0.27887498202671995}
2023-07-02 10:24:48,587 [prior] Evaluating prior at array([0.27887498])
2023-07-02 10:24:48,587 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:48,587 [model] Got input parameters: {'Omega_m': 0.27887498202671995, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:48,587 [classy] Got parameters {'Omega_m': 0.27887498202671995, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:48,587 [classy] Computing new state
2023-07-02 10:24:48,587 [classy] Setting parameters: {'Omega_m': 0.27887498202671995, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:48,634 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.50883676425246}
2023-07-02 10:24:48,634 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:48,637 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0757235
2023-07-02 10:24:48,637 [model] Computed derived parameters: {}
2023-07-02 10:24:48,637 [mcmc] New sample, #390:
Omega_m:0.478395
2023-07-02 10:24:48,637 [model] Posterior to be computed for parameters {'Omega_m': 0.2941860937882571}
2023-07-02 10:24:48,637 [prior] Evaluating prior at array([0.29418609])
2023-07-02 10:24:48,637 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:48,637 [model] Got input parameters: {'Omega_m': 0.2941860937882571, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:48,637 [classy] Got parameters {'Omega_m': 0.2941860937882571, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:48,637 [classy] Computing new state
2023-07-02 10:24:48,637 [classy] Setting parameters: {'Omega_m': 0.2941860937882571, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:48,684 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.52088401724643}
2023-07-02 10:24:48,684 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:48,687 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0217076
2023-07-02 10:24:48,687 [model] Computed derived parameters: {}
2023-07-02 10:24:48,687 [mcmc] New sample, #391:
Omega_m:0.278875
2023-07-02 10:24:48,687 [model] Posterior to be computed for parameters {'Omega_m': 0.36798854525088553}
2023-07-02 10:24:48,687 [prior] Evaluating prior at array([0.36798855])
2023-07-02 10:24:48,687 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:48,687 [model] Got input parameters: {'Omega_m': 0.36798854525088553, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:48,687 [classy] Got parameters {'Omega_m': 0.36798854525088553, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:48,687 [classy] Computing new state
2023-07-02 10:24:48,687 [classy] Setting parameters: {'Omega_m': 0.36798854525088553, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:48,734 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.06314619278507}
2023-07-02 10:24:48,734 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:48,737 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.165882
2023-07-02 10:24:48,737 [model] Computed derived parameters: {}
2023-07-02 10:24:48,737 [model] Posterior to be computed for parameters {'Omega_m': 0.4545153353113559}
2023-07-02 10:24:48,737 [prior] Evaluating prior at array([0.45451534])
2023-07-02 10:24:48,737 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:48,737 [model] Got input parameters: {'Omega_m': 0.4545153353113559, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:48,737 [classy] Got parameters {'Omega_m': 0.4545153353113559, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:48,737 [classy] Computing new state
2023-07-02 10:24:48,737 [classy] Setting parameters: {'Omega_m': 0.4545153353113559, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:48,783 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 132.96045809368576}
2023-07-02 10:24:48,783 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:48,786 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.905027
2023-07-02 10:24:48,786 [model] Computed derived parameters: {}
2023-07-02 10:24:48,787 [model] Posterior to be computed for parameters {'Omega_m': 0.2611661950495352}
2023-07-02 10:24:48,787 [prior] Evaluating prior at array([0.2611662])
2023-07-02 10:24:48,787 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:48,787 [model] Got input parameters: {'Omega_m': 0.2611661950495352, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:48,787 [classy] Got parameters {'Omega_m': 0.2611661950495352, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:48,787 [classy] Computing new state
2023-07-02 10:24:48,787 [classy] Setting parameters: {'Omega_m': 0.2611661950495352, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:48,833 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.92798583384817}
2023-07-02 10:24:48,833 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:48,836 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.184935
2023-07-02 10:24:48,836 [model] Computed derived parameters: {}
2023-07-02 10:24:48,836 [mcmc] New sample, #392:
Omega_m:0.2941861
2023-07-02 10:24:48,837 [model] Posterior to be computed for parameters {'Omega_m': 0.32728529125526973}
2023-07-02 10:24:48,837 [prior] Evaluating prior at array([0.32728529])
2023-07-02 10:24:48,837 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:48,837 [model] Got input parameters: {'Omega_m': 0.32728529125526973, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:48,837 [classy] Got parameters {'Omega_m': 0.32728529125526973, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:48,837 [classy] Computing new state
2023-07-02 10:24:48,837 [classy] Setting parameters: {'Omega_m': 0.32728529125526973, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:48,885 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.51566818217103}
2023-07-02 10:24:48,886 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:48,888 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0131572
2023-07-02 10:24:48,888 [model] Computed derived parameters: {}
2023-07-02 10:24:48,888 [mcmc] New sample, #393:
Omega_m:0.2611662
2023-07-02 10:24:48,888 [model] Posterior to be computed for parameters {'Omega_m': 0.7312041061605647}
2023-07-02 10:24:48,888 [prior] Evaluating prior at array([0.73120411])
2023-07-02 10:24:48,888 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:48,888 [model] Got input parameters: {'Omega_m': 0.7312041061605647, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:48,889 [classy] Got parameters {'Omega_m': 0.7312041061605647, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:48,889 [classy] Computing new state
2023-07-02 10:24:48,889 [classy] Setting parameters: {'Omega_m': 0.7312041061605647, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:48,935 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 114.74165994241817}
2023-07-02 10:24:48,936 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:48,938 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.98242
2023-07-02 10:24:48,938 [model] Computed derived parameters: {}
2023-07-02 10:24:48,938 [model] Posterior to be computed for parameters {'Omega_m': -0.044729229513257696}
2023-07-02 10:24:48,938 [prior] Evaluating prior at array([-0.04472923])
2023-07-02 10:24:48,938 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:48,938 [model] Posterior to be computed for parameters {'Omega_m': 0.24009070711674252}
2023-07-02 10:24:48,938 [prior] Evaluating prior at array([0.24009071])
2023-07-02 10:24:48,938 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:48,939 [model] Got input parameters: {'Omega_m': 0.24009070711674252, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:48,939 [classy] Got parameters {'Omega_m': 0.24009070711674252, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:48,939 [classy] Computing new state
2023-07-02 10:24:48,939 [classy] Setting parameters: {'Omega_m': 0.24009070711674252, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:48,989 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 156.99268791526384}
2023-07-02 10:24:48,989 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:48,991 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.390416
2023-07-02 10:24:48,991 [model] Computed derived parameters: {}
2023-07-02 10:24:48,991 [mcmc] New sample, #394:
Omega_m:0.3272853
2023-07-02 10:24:48,991 [model] Posterior to be computed for parameters {'Omega_m': 0.6793341865097531}
2023-07-02 10:24:48,991 [prior] Evaluating prior at array([0.67933419])
2023-07-02 10:24:48,991 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:48,991 [model] Got input parameters: {'Omega_m': 0.6793341865097531, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:48,991 [classy] Got parameters {'Omega_m': 0.6793341865097531, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:48,991 [classy] Computing new state
2023-07-02 10:24:48,991 [classy] Setting parameters: {'Omega_m': 0.6793341865097531, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:49,037 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 117.53266867246151}
2023-07-02 10:24:49,037 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:49,039 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.12165
2023-07-02 10:24:49,039 [model] Computed derived parameters: {}
2023-07-02 10:24:49,039 [model] Posterior to be computed for parameters {'Omega_m': -0.027327308202302003}
2023-07-02 10:24:49,039 [prior] Evaluating prior at array([-0.02732731])
2023-07-02 10:24:49,039 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:49,039 [model] Posterior to be computed for parameters {'Omega_m': 0.0330945783975482}
2023-07-02 10:24:49,039 [prior] Evaluating prior at array([0.03309458])
2023-07-02 10:24:49,040 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:49,040 [model] Posterior to be computed for parameters {'Omega_m': 0.5650737732058642}
2023-07-02 10:24:49,040 [prior] Evaluating prior at array([0.56507377])
2023-07-02 10:24:49,040 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:49,040 [model] Got input parameters: {'Omega_m': 0.5650737732058642, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:49,040 [classy] Got parameters {'Omega_m': 0.5650737732058642, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:49,040 [classy] Computing new state
2023-07-02 10:24:49,040 [classy] Setting parameters: {'Omega_m': 0.5650737732058642, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:49,087 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 124.57792773550864}
2023-07-02 10:24:49,087 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:49,088 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.34094
2023-07-02 10:24:49,089 [model] Computed derived parameters: {}
2023-07-02 10:24:49,089 [mcmc] New sample, #395:
Omega_m:0.2400907
2023-07-02 10:24:49,089 [model] Posterior to be computed for parameters {'Omega_m': 0.46744491292460083}
2023-07-02 10:24:49,089 [prior] Evaluating prior at array([0.46744491])
2023-07-02 10:24:49,089 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:49,089 [model] Got input parameters: {'Omega_m': 0.46744491292460083, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:49,089 [classy] Got parameters {'Omega_m': 0.46744491292460083, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:49,089 [classy] Computing new state
2023-07-02 10:24:49,089 [classy] Setting parameters: {'Omega_m': 0.46744491292460083, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:49,137 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 131.8802048494339}
2023-07-02 10:24:49,137 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:49,139 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.05055
2023-07-02 10:24:49,139 [model] Computed derived parameters: {}
2023-07-02 10:24:49,139 [mcmc] New sample, #396:
Omega_m:0.5650738
2023-07-02 10:24:49,139 [model] Posterior to be computed for parameters {'Omega_m': 0.5846058438915025}
2023-07-02 10:24:49,139 [prior] Evaluating prior at array([0.58460584])
2023-07-02 10:24:49,139 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:49,139 [model] Got input parameters: {'Omega_m': 0.5846058438915025, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:49,139 [classy] Got parameters {'Omega_m': 0.5846058438915025, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:49,139 [classy] Computing new state
2023-07-02 10:24:49,139 [classy] Setting parameters: {'Omega_m': 0.5846058438915025, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:49,187 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 123.27297936945887}
2023-07-02 10:24:49,187 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:49,188 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.62978
2023-07-02 10:24:49,188 [model] Computed derived parameters: {}
2023-07-02 10:24:49,189 [model] Posterior to be computed for parameters {'Omega_m': 0.21738675539582347}
2023-07-02 10:24:49,189 [prior] Evaluating prior at array([0.21738676])
2023-07-02 10:24:49,189 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:49,189 [model] Got input parameters: {'Omega_m': 0.21738675539582347, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:49,189 [classy] Got parameters {'Omega_m': 0.21738675539582347, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:49,189 [classy] Computing new state
2023-07-02 10:24:49,189 [classy] Setting parameters: {'Omega_m': 0.21738675539582347, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:49,234 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 160.54914640346664}
2023-07-02 10:24:49,234 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:49,236 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.720619
2023-07-02 10:24:49,236 [model] Computed derived parameters: {}
2023-07-02 10:24:49,236 [mcmc] New sample, #397:
Omega_m:0.4674449
2023-07-02 10:24:49,236 [model] Posterior to be computed for parameters {'Omega_m': 0.332379591583703}
2023-07-02 10:24:49,236 [prior] Evaluating prior at array([0.33237959])
2023-07-02 10:24:49,236 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:49,236 [model] Got input parameters: {'Omega_m': 0.332379591583703, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:49,236 [classy] Got parameters {'Omega_m': 0.332379591583703, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:49,236 [classy] Computing new state
2023-07-02 10:24:49,236 [classy] Setting parameters: {'Omega_m': 0.332379591583703, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:49,284 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.93161587286653}
2023-07-02 10:24:49,284 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:49,287 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.023324
2023-07-02 10:24:49,287 [model] Computed derived parameters: {}
2023-07-02 10:24:49,287 [mcmc] New sample, #398:
Omega_m:0.2173868
2023-07-02 10:24:49,287 [model] Posterior to be computed for parameters {'Omega_m': 0.5126746121058726}
2023-07-02 10:24:49,287 [prior] Evaluating prior at array([0.51267461])
2023-07-02 10:24:49,287 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:49,287 [model] Got input parameters: {'Omega_m': 0.5126746121058726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:49,287 [classy] Got parameters {'Omega_m': 0.5126746121058726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:49,287 [classy] Computing new state
2023-07-02 10:24:49,287 [classy] Setting parameters: {'Omega_m': 0.5126746121058726, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:49,333 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 128.32226001409953}
2023-07-02 10:24:49,334 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:49,336 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.61144
2023-07-02 10:24:49,336 [model] Computed derived parameters: {}
2023-07-02 10:24:49,336 [model] Posterior to be computed for parameters {'Omega_m': 0.46515782750976054}
2023-07-02 10:24:49,336 [prior] Evaluating prior at array([0.46515783])
2023-07-02 10:24:49,337 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:49,337 [model] Got input parameters: {'Omega_m': 0.46515782750976054, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:49,337 [classy] Got parameters {'Omega_m': 0.46515782750976054, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:49,337 [classy] Computing new state
2023-07-02 10:24:49,337 [classy] Setting parameters: {'Omega_m': 0.46515782750976054, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:49,383 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 132.0691208440315}
2023-07-02 10:24:49,384 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:49,385 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.02428
2023-07-02 10:24:49,385 [model] Computed derived parameters: {}
2023-07-02 10:24:49,386 [mcmc] New sample, #399:
Omega_m:0.3323796
2023-07-02 10:24:49,386 [model] Posterior to be computed for parameters {'Omega_m': 0.8646800805279174}
2023-07-02 10:24:49,386 [prior] Evaluating prior at array([0.86468008])
2023-07-02 10:24:49,386 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:49,386 [model] Got input parameters: {'Omega_m': 0.8646800805279174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:49,386 [classy] Got parameters {'Omega_m': 0.8646800805279174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:49,386 [classy] Computing new state
2023-07-02 10:24:49,386 [classy] Setting parameters: {'Omega_m': 0.8646800805279174, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:49,432 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 108.45427406585448}
2023-07-02 10:24:49,432 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:49,434 [bao_likelihood.baolikelihood] Computed log-likelihood = -7.26642
2023-07-02 10:24:49,434 [model] Computed derived parameters: {}
2023-07-02 10:24:49,434 [model] Posterior to be computed for parameters {'Omega_m': 0.4616593268998967}
2023-07-02 10:24:49,434 [prior] Evaluating prior at array([0.46165933])
2023-07-02 10:24:49,434 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:49,434 [model] Got input parameters: {'Omega_m': 0.4616593268998967, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:49,435 [classy] Got parameters {'Omega_m': 0.4616593268998967, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:49,435 [classy] Computing new state
2023-07-02 10:24:49,435 [classy] Setting parameters: {'Omega_m': 0.4616593268998967, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:49,481 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 132.35988810911462}
2023-07-02 10:24:49,481 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:49,483 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.984528
2023-07-02 10:24:49,483 [model] Computed derived parameters: {}
2023-07-02 10:24:49,483 [mcmc] New sample, #400:
Omega_m:0.4651578
2023-07-02 10:24:49,483 [mcmc] Learn + convergence test @ 400 samples accepted.
2023-07-02 10:24:49,483 [mcmc] Ready to check convergence and learn a new proposal covmat
2023-07-02 10:24:49,488 [mcmc] - Acceptance rate: 0.427
2023-07-02 10:24:49,489 [mcmc] - Condition number = 1
2023-07-02 10:24:49,489 [mcmc] - Eigenvalues = array([0.03276477])
2023-07-02 10:24:49,489 [mcmc] - Convergence of means: R-1 = 0.032765 after 320 accepted steps
2023-07-02 10:24:49,489 [mcmc] - Updated covariance matrix of proposal pdf.
2023-07-02 10:24:49,489 [mcmc] array([[0.01200069]])
2023-07-02 10:24:49,499 [mcmc] Dumped checkpoint and progress info, and current covmat.
2023-07-02 10:24:49,499 [model] Posterior to be computed for parameters {'Omega_m': 0.32676862470983375}
2023-07-02 10:24:49,499 [prior] Evaluating prior at array([0.32676862])
2023-07-02 10:24:49,499 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:49,500 [model] Got input parameters: {'Omega_m': 0.32676862470983375, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:49,500 [classy] Got parameters {'Omega_m': 0.32676862470983375, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:49,500 [classy] Computing new state
2023-07-02 10:24:49,500 [classy] Setting parameters: {'Omega_m': 0.32676862470983375, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:49,546 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.57536458753657}
2023-07-02 10:24:49,546 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:49,549 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0122835
2023-07-02 10:24:49,549 [model] Computed derived parameters: {}
2023-07-02 10:24:49,549 [mcmc] New sample, #401:
Omega_m:0.4616593
2023-07-02 10:24:49,549 [model] Posterior to be computed for parameters {'Omega_m': 0.3427794086215481}
2023-07-02 10:24:49,549 [prior] Evaluating prior at array([0.34277941])
2023-07-02 10:24:49,549 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:49,549 [model] Got input parameters: {'Omega_m': 0.3427794086215481, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:49,549 [classy] Got parameters {'Omega_m': 0.3427794086215481, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:49,549 [classy] Computing new state
2023-07-02 10:24:49,549 [classy] Setting parameters: {'Omega_m': 0.3427794086215481, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:49,596 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.76402837295277}
2023-07-02 10:24:49,596 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:49,598 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0525071
2023-07-02 10:24:49,598 [model] Computed derived parameters: {}
2023-07-02 10:24:49,599 [model] Posterior to be computed for parameters {'Omega_m': 0.10512836904135917}
2023-07-02 10:24:49,599 [prior] Evaluating prior at array([0.10512837])
2023-07-02 10:24:49,599 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:49,599 [model] Got input parameters: {'Omega_m': 0.10512836904135917, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:49,599 [classy] Got parameters {'Omega_m': 0.10512836904135917, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:49,599 [classy] Computing new state
2023-07-02 10:24:49,599 [classy] Setting parameters: {'Omega_m': 0.10512836904135917, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:49,649 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 183.79292737264674}
2023-07-02 10:24:49,649 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:49,652 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.1235
2023-07-02 10:24:49,652 [model] Computed derived parameters: {}
2023-07-02 10:24:49,652 [model] Posterior to be computed for parameters {'Omega_m': 0.5317220814329515}
2023-07-02 10:24:49,652 [prior] Evaluating prior at array([0.53172208])
2023-07-02 10:24:49,652 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:49,652 [model] Got input parameters: {'Omega_m': 0.5317220814329515, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:49,652 [classy] Got parameters {'Omega_m': 0.5317220814329515, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:49,652 [classy] Computing new state
2023-07-02 10:24:49,652 [classy] Setting parameters: {'Omega_m': 0.5317220814329515, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:49,704 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 126.9176976149968}
2023-07-02 10:24:49,704 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:49,706 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.86806
2023-07-02 10:24:49,706 [model] Computed derived parameters: {}
2023-07-02 10:24:49,706 [model] Posterior to be computed for parameters {'Omega_m': 0.19353301860060468}
2023-07-02 10:24:49,706 [prior] Evaluating prior at array([0.19353302])
2023-07-02 10:24:49,706 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:49,706 [model] Got input parameters: {'Omega_m': 0.19353301860060468, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:49,706 [classy] Got parameters {'Omega_m': 0.19353301860060468, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:49,706 [classy] Computing new state
2023-07-02 10:24:49,706 [classy] Setting parameters: {'Omega_m': 0.19353301860060468, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:49,759 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 164.61419919364698}
2023-07-02 10:24:49,759 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:49,761 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.21534
2023-07-02 10:24:49,761 [model] Computed derived parameters: {}
2023-07-02 10:24:49,761 [model] Posterior to be computed for parameters {'Omega_m': 0.3430779851713183}
2023-07-02 10:24:49,761 [prior] Evaluating prior at array([0.34307799])
2023-07-02 10:24:49,761 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:49,761 [model] Got input parameters: {'Omega_m': 0.3430779851713183, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:49,761 [classy] Got parameters {'Omega_m': 0.3430779851713183, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:49,761 [classy] Computing new state
2023-07-02 10:24:49,761 [classy] Setting parameters: {'Omega_m': 0.3430779851713183, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:49,809 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.7309806700128}
2023-07-02 10:24:49,809 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:49,811 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0535061
2023-07-02 10:24:49,811 [model] Computed derived parameters: {}
2023-07-02 10:24:49,811 [mcmc] New sample, #402:
Omega_m:0.3267686
2023-07-02 10:24:49,811 [model] Posterior to be computed for parameters {'Omega_m': 0.5899227145380558}
2023-07-02 10:24:49,811 [prior] Evaluating prior at array([0.58992271])
2023-07-02 10:24:49,811 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:49,811 [model] Got input parameters: {'Omega_m': 0.5899227145380558, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:49,811 [classy] Got parameters {'Omega_m': 0.5899227145380558, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:49,811 [classy] Computing new state
2023-07-02 10:24:49,811 [classy] Setting parameters: {'Omega_m': 0.5899227145380558, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:49,858 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 122.92561510823374}
2023-07-02 10:24:49,858 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:49,860 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.70974
2023-07-02 10:24:49,860 [model] Computed derived parameters: {}
2023-07-02 10:24:49,860 [model] Posterior to be computed for parameters {'Omega_m': 0.48855354045875765}
2023-07-02 10:24:49,860 [prior] Evaluating prior at array([0.48855354])
2023-07-02 10:24:49,860 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:49,860 [model] Got input parameters: {'Omega_m': 0.48855354045875765, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:49,860 [classy] Got parameters {'Omega_m': 0.48855354045875765, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:49,860 [classy] Computing new state
2023-07-02 10:24:49,860 [classy] Setting parameters: {'Omega_m': 0.48855354045875765, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:49,907 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.1787013667199}
2023-07-02 10:24:49,907 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:49,909 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.30302
2023-07-02 10:24:49,909 [model] Computed derived parameters: {}
2023-07-02 10:24:49,909 [model] Posterior to be computed for parameters {'Omega_m': 0.34425707421128554}
2023-07-02 10:24:49,909 [prior] Evaluating prior at array([0.34425707])
2023-07-02 10:24:49,909 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:49,909 [model] Got input parameters: {'Omega_m': 0.34425707421128554, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:49,910 [classy] Got parameters {'Omega_m': 0.34425707421128554, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:49,910 [classy] Computing new state
2023-07-02 10:24:49,910 [classy] Setting parameters: {'Omega_m': 0.34425707421128554, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:49,956 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.60074091632578}
2023-07-02 10:24:49,956 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:49,958 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0575356
2023-07-02 10:24:49,958 [model] Computed derived parameters: {}
2023-07-02 10:24:49,958 [mcmc] New sample, #403:
Omega_m:0.343078
2023-07-02 10:24:49,958 [model] Posterior to be computed for parameters {'Omega_m': 0.836930120958044}
2023-07-02 10:24:49,958 [prior] Evaluating prior at array([0.83693012])
2023-07-02 10:24:49,958 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:49,959 [model] Got input parameters: {'Omega_m': 0.836930120958044, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:49,959 [classy] Got parameters {'Omega_m': 0.836930120958044, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:49,959 [classy] Computing new state
2023-07-02 10:24:49,959 [classy] Setting parameters: {'Omega_m': 0.836930120958044, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:50,005 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 109.66848746897219}
2023-07-02 10:24:50,005 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:50,007 [bao_likelihood.baolikelihood] Computed log-likelihood = -6.78685
2023-07-02 10:24:50,007 [model] Computed derived parameters: {}
2023-07-02 10:24:50,007 [model] Posterior to be computed for parameters {'Omega_m': 0.20576761183048878}
2023-07-02 10:24:50,007 [prior] Evaluating prior at array([0.20576761])
2023-07-02 10:24:50,007 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:50,007 [model] Got input parameters: {'Omega_m': 0.20576761183048878, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:50,007 [classy] Got parameters {'Omega_m': 0.20576761183048878, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:50,007 [classy] Computing new state
2023-07-02 10:24:50,007 [classy] Setting parameters: {'Omega_m': 0.20576761183048878, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:50,058 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 162.48396704406545}
2023-07-02 10:24:50,058 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:50,059 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.940712
2023-07-02 10:24:50,059 [model] Computed derived parameters: {}
2023-07-02 10:24:50,060 [mcmc] New sample, #404:
Omega_m:0.3442571
2023-07-02 10:24:50,060 [model] Posterior to be computed for parameters {'Omega_m': 0.02918154655298144}
2023-07-02 10:24:50,060 [prior] Evaluating prior at array([0.02918155])
2023-07-02 10:24:50,060 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:50,060 [model] Posterior to be computed for parameters {'Omega_m': 0.6108762565689925}
2023-07-02 10:24:50,060 [prior] Evaluating prior at array([0.61087626])
2023-07-02 10:24:50,060 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:50,060 [model] Got input parameters: {'Omega_m': 0.6108762565689925, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:50,060 [classy] Got parameters {'Omega_m': 0.6108762565689925, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:50,060 [classy] Computing new state
2023-07-02 10:24:50,060 [classy] Setting parameters: {'Omega_m': 0.6108762565689925, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:50,110 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 121.58779075286111}
2023-07-02 10:24:50,110 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:50,111 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.02993
2023-07-02 10:24:50,111 [model] Computed derived parameters: {}
2023-07-02 10:24:50,112 [model] Posterior to be computed for parameters {'Omega_m': 0.17514637902339814}
2023-07-02 10:24:50,112 [prior] Evaluating prior at array([0.17514638])
2023-07-02 10:24:50,112 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:50,112 [model] Got input parameters: {'Omega_m': 0.17514637902339814, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:50,112 [classy] Got parameters {'Omega_m': 0.17514637902339814, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:50,112 [classy] Computing new state
2023-07-02 10:24:50,112 [classy] Setting parameters: {'Omega_m': 0.17514637902339814, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:50,159 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 168.01322003614166}
2023-07-02 10:24:50,159 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:50,161 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.7223
2023-07-02 10:24:50,161 [model] Computed derived parameters: {}
2023-07-02 10:24:50,161 [model] Posterior to be computed for parameters {'Omega_m': 0.11459836405881604}
2023-07-02 10:24:50,162 [prior] Evaluating prior at array([0.11459836])
2023-07-02 10:24:50,162 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:50,162 [model] Got input parameters: {'Omega_m': 0.11459836405881604, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:50,162 [classy] Got parameters {'Omega_m': 0.11459836405881604, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:50,162 [classy] Computing new state
2023-07-02 10:24:50,162 [classy] Setting parameters: {'Omega_m': 0.11459836405881604, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:50,208 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 181.333180885917}
2023-07-02 10:24:50,208 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:50,210 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.48476
2023-07-02 10:24:50,210 [model] Computed derived parameters: {}
2023-07-02 10:24:50,210 [model] Posterior to be computed for parameters {'Omega_m': 0.27337782827443013}
2023-07-02 10:24:50,210 [prior] Evaluating prior at array([0.27337783])
2023-07-02 10:24:50,210 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:50,211 [model] Got input parameters: {'Omega_m': 0.27337782827443013, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:50,211 [classy] Got parameters {'Omega_m': 0.27337782827443013, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:50,211 [classy] Computing new state
2023-07-02 10:24:50,211 [classy] Setting parameters: {'Omega_m': 0.27337782827443013, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:50,257 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.24546834018247}
2023-07-02 10:24:50,257 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:50,259 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.103962
2023-07-02 10:24:50,259 [model] Computed derived parameters: {}
2023-07-02 10:24:50,259 [mcmc] New sample, #405:
Omega_m:0.2057676
2023-07-02 10:24:50,259 [model] Posterior to be computed for parameters {'Omega_m': 0.06543828708372013}
2023-07-02 10:24:50,259 [prior] Evaluating prior at array([0.06543829])
2023-07-02 10:24:50,259 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:50,259 [model] Posterior to be computed for parameters {'Omega_m': 0.20548040072543283}
2023-07-02 10:24:50,259 [prior] Evaluating prior at array([0.2054804])
2023-07-02 10:24:50,260 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:50,260 [model] Got input parameters: {'Omega_m': 0.20548040072543283, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:50,260 [classy] Got parameters {'Omega_m': 0.20548040072543283, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:50,260 [classy] Computing new state
2023-07-02 10:24:50,260 [classy] Setting parameters: {'Omega_m': 0.20548040072543283, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:50,307 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 162.5328560491312}
2023-07-02 10:24:50,307 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:50,309 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.946637
2023-07-02 10:24:50,309 [model] Computed derived parameters: {}
2023-07-02 10:24:50,309 [model] Posterior to be computed for parameters {'Omega_m': 0.2856377556595243}
2023-07-02 10:24:50,309 [prior] Evaluating prior at array([0.28563776])
2023-07-02 10:24:50,309 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:50,309 [model] Got input parameters: {'Omega_m': 0.2856377556595243, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:50,309 [classy] Got parameters {'Omega_m': 0.2856377556595243, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:50,309 [classy] Computing new state
2023-07-02 10:24:50,309 [classy] Setting parameters: {'Omega_m': 0.2856377556595243, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:50,357 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.6194210467605}
2023-07-02 10:24:50,357 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:50,359 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0475339
2023-07-02 10:24:50,359 [model] Computed derived parameters: {}
2023-07-02 10:24:50,359 [mcmc] New sample, #406:
Omega_m:0.2733778
2023-07-02 10:24:50,359 [model] Posterior to be computed for parameters {'Omega_m': 0.11620963555030883}
2023-07-02 10:24:50,359 [prior] Evaluating prior at array([0.11620964])
2023-07-02 10:24:50,360 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:50,360 [model] Got input parameters: {'Omega_m': 0.11620963555030883, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:50,360 [classy] Got parameters {'Omega_m': 0.11620963555030883, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:50,360 [classy] Computing new state
2023-07-02 10:24:50,360 [classy] Setting parameters: {'Omega_m': 0.11620963555030883, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:50,410 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 180.92664751335647}
2023-07-02 10:24:50,410 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:50,412 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.38293
2023-07-02 10:24:50,412 [model] Computed derived parameters: {}
2023-07-02 10:24:50,412 [model] Posterior to be computed for parameters {'Omega_m': -0.12282832034375685}
2023-07-02 10:24:50,412 [prior] Evaluating prior at array([-0.12282832])
2023-07-02 10:24:50,413 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:50,413 [model] Posterior to be computed for parameters {'Omega_m': 0.6561637762467107}
2023-07-02 10:24:50,413 [prior] Evaluating prior at array([0.65616378])
2023-07-02 10:24:50,413 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:50,413 [model] Got input parameters: {'Omega_m': 0.6561637762467107, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:50,413 [classy] Got parameters {'Omega_m': 0.6561637762467107, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:50,413 [classy] Computing new state
2023-07-02 10:24:50,413 [classy] Setting parameters: {'Omega_m': 0.6561637762467107, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:50,464 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 118.85448393076001}
2023-07-02 10:24:50,464 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:50,466 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.74545
2023-07-02 10:24:50,466 [model] Computed derived parameters: {}
2023-07-02 10:24:50,466 [model] Posterior to be computed for parameters {'Omega_m': 0.5860648575297149}
2023-07-02 10:24:50,466 [prior] Evaluating prior at array([0.58606486])
2023-07-02 10:24:50,467 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:50,467 [model] Got input parameters: {'Omega_m': 0.5860648575297149, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:50,467 [classy] Got parameters {'Omega_m': 0.5860648575297149, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:50,467 [classy] Computing new state
2023-07-02 10:24:50,467 [classy] Setting parameters: {'Omega_m': 0.5860648575297149, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:50,515 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 123.1773244551881}
2023-07-02 10:24:50,516 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:50,518 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.65168
2023-07-02 10:24:50,519 [model] Computed derived parameters: {}
2023-07-02 10:24:50,519 [mcmc] New sample, #407:
Omega_m:0.2856378
2023-07-02 10:24:50,519 [model] Posterior to be computed for parameters {'Omega_m': 0.741787022984269}
2023-07-02 10:24:50,519 [prior] Evaluating prior at array([0.74178702])
2023-07-02 10:24:50,519 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:50,519 [model] Got input parameters: {'Omega_m': 0.741787022984269, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:50,519 [classy] Got parameters {'Omega_m': 0.741787022984269, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:50,519 [classy] Computing new state
2023-07-02 10:24:50,519 [classy] Setting parameters: {'Omega_m': 0.741787022984269, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:50,565 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 114.19864184456952}
2023-07-02 10:24:50,565 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:50,568 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.16057
2023-07-02 10:24:50,568 [model] Computed derived parameters: {}
2023-07-02 10:24:50,568 [model] Posterior to be computed for parameters {'Omega_m': 0.6191618831458678}
2023-07-02 10:24:50,569 [prior] Evaluating prior at array([0.61916188])
2023-07-02 10:24:50,569 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:50,569 [model] Got input parameters: {'Omega_m': 0.6191618831458678, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:50,569 [classy] Got parameters {'Omega_m': 0.6191618831458678, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:50,569 [classy] Computing new state
2023-07-02 10:24:50,569 [classy] Setting parameters: {'Omega_m': 0.6191618831458678, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:50,617 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 121.07202655109462}
2023-07-02 10:24:50,618 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:50,620 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.1586
2023-07-02 10:24:50,620 [model] Computed derived parameters: {}
2023-07-02 10:24:50,620 [model] Posterior to be computed for parameters {'Omega_m': 0.815521316179243}
2023-07-02 10:24:50,620 [prior] Evaluating prior at array([0.81552132])
2023-07-02 10:24:50,620 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:50,620 [model] Got input parameters: {'Omega_m': 0.815521316179243, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:50,620 [classy] Got parameters {'Omega_m': 0.815521316179243, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:50,620 [classy] Computing new state
2023-07-02 10:24:50,620 [classy] Setting parameters: {'Omega_m': 0.815521316179243, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:50,668 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 110.63635163027793}
2023-07-02 10:24:50,669 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:50,670 [bao_likelihood.baolikelihood] Computed log-likelihood = -6.41802
2023-07-02 10:24:50,670 [model] Computed derived parameters: {}
2023-07-02 10:24:50,671 [model] Posterior to be computed for parameters {'Omega_m': 0.45823077352968233}
2023-07-02 10:24:50,671 [prior] Evaluating prior at array([0.45823077])
2023-07-02 10:24:50,671 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:50,671 [model] Got input parameters: {'Omega_m': 0.45823077352968233, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:50,671 [classy] Got parameters {'Omega_m': 0.45823077352968233, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:50,671 [classy] Computing new state
2023-07-02 10:24:50,671 [classy] Setting parameters: {'Omega_m': 0.45823077352968233, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:50,720 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 132.64694478746662}
2023-07-02 10:24:50,720 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:50,722 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.946094
2023-07-02 10:24:50,722 [model] Computed derived parameters: {}
2023-07-02 10:24:50,722 [mcmc] New sample, #408:
Omega_m:0.5860649
2023-07-02 10:24:50,722 [model] Posterior to be computed for parameters {'Omega_m': 0.8787783384084056}
2023-07-02 10:24:50,722 [prior] Evaluating prior at array([0.87877834])
2023-07-02 10:24:50,722 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:50,722 [model] Got input parameters: {'Omega_m': 0.8787783384084056, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:50,722 [classy] Got parameters {'Omega_m': 0.8787783384084056, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:50,722 [classy] Computing new state
2023-07-02 10:24:50,722 [classy] Setting parameters: {'Omega_m': 0.8787783384084056, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:50,770 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 107.85400903458876}
2023-07-02 10:24:50,770 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:50,771 [bao_likelihood.baolikelihood] Computed log-likelihood = -7.51051
2023-07-02 10:24:50,771 [model] Computed derived parameters: {}
2023-07-02 10:24:50,772 [model] Posterior to be computed for parameters {'Omega_m': 0.5830156049981488}
2023-07-02 10:24:50,772 [prior] Evaluating prior at array([0.5830156])
2023-07-02 10:24:50,772 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:50,772 [model] Got input parameters: {'Omega_m': 0.5830156049981488, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:50,772 [classy] Got parameters {'Omega_m': 0.5830156049981488, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:50,772 [classy] Computing new state
2023-07-02 10:24:50,772 [classy] Setting parameters: {'Omega_m': 0.5830156049981488, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:50,820 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 123.3775227686365}
2023-07-02 10:24:50,820 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:50,822 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.60597
2023-07-02 10:24:50,822 [model] Computed derived parameters: {}
2023-07-02 10:24:50,822 [model] Posterior to be computed for parameters {'Omega_m': 0.6848629463642}
2023-07-02 10:24:50,822 [prior] Evaluating prior at array([0.68486295])
2023-07-02 10:24:50,822 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:50,822 [model] Got input parameters: {'Omega_m': 0.6848629463642, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:50,822 [classy] Got parameters {'Omega_m': 0.6848629463642, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:50,822 [classy] Computing new state
2023-07-02 10:24:50,822 [classy] Setting parameters: {'Omega_m': 0.6848629463642, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:50,870 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 117.22439275875857}
2023-07-02 10:24:50,870 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:50,871 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.21228
2023-07-02 10:24:50,871 [model] Computed derived parameters: {}
2023-07-02 10:24:50,872 [model] Posterior to be computed for parameters {'Omega_m': 0.47991352672268056}
2023-07-02 10:24:50,872 [prior] Evaluating prior at array([0.47991353])
2023-07-02 10:24:50,872 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:50,872 [model] Got input parameters: {'Omega_m': 0.47991352672268056, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:50,872 [classy] Got parameters {'Omega_m': 0.47991352672268056, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:50,872 [classy] Computing new state
2023-07-02 10:24:50,872 [classy] Setting parameters: {'Omega_m': 0.47991352672268056, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:50,920 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.8661198169364}
2023-07-02 10:24:50,920 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:50,922 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.19757
2023-07-02 10:24:50,922 [model] Computed derived parameters: {}
2023-07-02 10:24:50,922 [mcmc] New sample, #409:
Omega_m:0.4582308
2023-07-02 10:24:50,922 [model] Posterior to be computed for parameters {'Omega_m': 0.5127997041626268}
2023-07-02 10:24:50,922 [prior] Evaluating prior at array([0.5127997])
2023-07-02 10:24:50,922 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:50,922 [model] Got input parameters: {'Omega_m': 0.5127997041626268, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:50,922 [classy] Got parameters {'Omega_m': 0.5127997041626268, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:50,923 [classy] Computing new state
2023-07-02 10:24:50,923 [classy] Setting parameters: {'Omega_m': 0.5127997041626268, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:50,970 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 128.3128650034056}
2023-07-02 10:24:50,970 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:50,972 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.61309
2023-07-02 10:24:50,972 [model] Computed derived parameters: {}
2023-07-02 10:24:50,972 [model] Posterior to be computed for parameters {'Omega_m': 0.5797714435016257}
2023-07-02 10:24:50,972 [prior] Evaluating prior at array([0.57977144])
2023-07-02 10:24:50,972 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:50,972 [model] Got input parameters: {'Omega_m': 0.5797714435016257, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:50,972 [classy] Got parameters {'Omega_m': 0.5797714435016257, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:50,972 [classy] Computing new state
2023-07-02 10:24:50,972 [classy] Setting parameters: {'Omega_m': 0.5797714435016257, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:51,020 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 123.5917187630541}
2023-07-02 10:24:51,020 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:51,022 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.55755
2023-07-02 10:24:51,022 [model] Computed derived parameters: {}
2023-07-02 10:24:51,022 [model] Posterior to be computed for parameters {'Omega_m': 0.21028387720293723}
2023-07-02 10:24:51,022 [prior] Evaluating prior at array([0.21028388])
2023-07-02 10:24:51,022 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:51,022 [model] Got input parameters: {'Omega_m': 0.21028387720293723, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:51,022 [classy] Got parameters {'Omega_m': 0.21028387720293723, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:51,022 [classy] Computing new state
2023-07-02 10:24:51,022 [classy] Setting parameters: {'Omega_m': 0.21028387720293723, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:51,069 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 161.72208141976742}
2023-07-02 10:24:51,070 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:51,071 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.850685
2023-07-02 10:24:51,071 [model] Computed derived parameters: {}
2023-07-02 10:24:51,071 [mcmc] New sample, #410:
Omega_m:0.4799135
2023-07-02 10:24:51,072 [model] Posterior to be computed for parameters {'Omega_m': 0.32375120716287425}
2023-07-02 10:24:51,072 [prior] Evaluating prior at array([0.32375121])
2023-07-02 10:24:51,072 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:51,072 [model] Got input parameters: {'Omega_m': 0.32375120716287425, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:51,072 [classy] Got parameters {'Omega_m': 0.32375120716287425, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:51,072 [classy] Computing new state
2023-07-02 10:24:51,072 [classy] Setting parameters: {'Omega_m': 0.32375120716287425, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:51,120 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.92568870784214}
2023-07-02 10:24:51,120 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:51,121 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00777363
2023-07-02 10:24:51,122 [model] Computed derived parameters: {}
2023-07-02 10:24:51,122 [mcmc] New sample, #411:
Omega_m:0.2102839
2023-07-02 10:24:51,122 [model] Posterior to be computed for parameters {'Omega_m': 0.07919556872374156}
2023-07-02 10:24:51,122 [prior] Evaluating prior at array([0.07919557])
2023-07-02 10:24:51,122 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:51,122 [model] Posterior to be computed for parameters {'Omega_m': 0.5843471994423544}
2023-07-02 10:24:51,122 [prior] Evaluating prior at array([0.5843472])
2023-07-02 10:24:51,122 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:51,122 [model] Got input parameters: {'Omega_m': 0.5843471994423544, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:51,122 [classy] Got parameters {'Omega_m': 0.5843471994423544, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:51,122 [classy] Computing new state
2023-07-02 10:24:51,122 [classy] Setting parameters: {'Omega_m': 0.5843471994423544, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:51,171 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 123.28996213032066}
2023-07-02 10:24:51,171 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:51,173 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.62591
2023-07-02 10:24:51,173 [model] Computed derived parameters: {}
2023-07-02 10:24:51,173 [model] Posterior to be computed for parameters {'Omega_m': -0.023713783748902095}
2023-07-02 10:24:51,173 [prior] Evaluating prior at array([-0.02371378])
2023-07-02 10:24:51,173 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:51,173 [model] Posterior to be computed for parameters {'Omega_m': 0.23140780681585238}
2023-07-02 10:24:51,173 [prior] Evaluating prior at array([0.23140781])
2023-07-02 10:24:51,173 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:51,173 [model] Got input parameters: {'Omega_m': 0.23140780681585238, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:51,173 [classy] Got parameters {'Omega_m': 0.23140780681585238, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:51,173 [classy] Computing new state
2023-07-02 10:24:51,173 [classy] Setting parameters: {'Omega_m': 0.23140780681585238, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:51,222 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 158.3196531874321}
2023-07-02 10:24:51,223 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:51,224 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.502228
2023-07-02 10:24:51,224 [model] Computed derived parameters: {}
2023-07-02 10:24:51,224 [mcmc] New sample, #412:
Omega_m:0.3237512
2023-07-02 10:24:51,224 [model] Posterior to be computed for parameters {'Omega_m': 0.22171335447387375}
2023-07-02 10:24:51,225 [prior] Evaluating prior at array([0.22171335])
2023-07-02 10:24:51,225 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:51,225 [model] Got input parameters: {'Omega_m': 0.22171335447387375, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:51,225 [classy] Got parameters {'Omega_m': 0.22171335447387375, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:51,225 [classy] Computing new state
2023-07-02 10:24:51,225 [classy] Setting parameters: {'Omega_m': 0.22171335447387375, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:51,273 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 159.8492933806491}
2023-07-02 10:24:51,273 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:51,275 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.647974
2023-07-02 10:24:51,275 [model] Computed derived parameters: {}
2023-07-02 10:24:51,275 [mcmc] New sample, #413:
Omega_m:0.2314078
2023-07-02 10:24:51,275 [model] Posterior to be computed for parameters {'Omega_m': 0.036911028921373046}
2023-07-02 10:24:51,275 [prior] Evaluating prior at array([0.03691103])
2023-07-02 10:24:51,275 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:51,275 [model] Posterior to be computed for parameters {'Omega_m': 0.4403621962358777}
2023-07-02 10:24:51,275 [prior] Evaluating prior at array([0.4403622])
2023-07-02 10:24:51,275 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:51,275 [model] Got input parameters: {'Omega_m': 0.4403621962358777, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:51,275 [classy] Got parameters {'Omega_m': 0.4403621962358777, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:51,275 [classy] Computing new state
2023-07-02 10:24:51,275 [classy] Setting parameters: {'Omega_m': 0.4403621962358777, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:51,324 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 134.1781430129762}
2023-07-02 10:24:51,324 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:51,326 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.754544
2023-07-02 10:24:51,326 [model] Computed derived parameters: {}
2023-07-02 10:24:51,326 [mcmc] New sample, #414:
Omega_m:0.2217134
2023-07-02 10:24:51,326 [model] Posterior to be computed for parameters {'Omega_m': 0.508242296226595}
2023-07-02 10:24:51,326 [prior] Evaluating prior at array([0.5082423])
2023-07-02 10:24:51,326 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:51,326 [model] Got input parameters: {'Omega_m': 0.508242296226595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:51,326 [classy] Got parameters {'Omega_m': 0.508242296226595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:51,326 [classy] Computing new state
2023-07-02 10:24:51,326 [classy] Setting parameters: {'Omega_m': 0.508242296226595, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:51,374 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 128.65669616063835}
2023-07-02 10:24:51,374 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:51,376 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.55331
2023-07-02 10:24:51,376 [model] Computed derived parameters: {}
2023-07-02 10:24:51,376 [mcmc] New sample, #415:
Omega_m:0.4403622
2023-07-02 10:24:51,376 [model] Posterior to be computed for parameters {'Omega_m': 0.3614251845518407}
2023-07-02 10:24:51,376 [prior] Evaluating prior at array([0.36142518])
2023-07-02 10:24:51,376 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:51,376 [model] Got input parameters: {'Omega_m': 0.3614251845518407, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:51,376 [classy] Got parameters {'Omega_m': 0.3614251845518407, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:51,376 [classy] Computing new state
2023-07-02 10:24:51,376 [classy] Setting parameters: {'Omega_m': 0.3614251845518407, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:51,425 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.7494722607087}
2023-07-02 10:24:51,425 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:51,427 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.130944
2023-07-02 10:24:51,427 [model] Computed derived parameters: {}
2023-07-02 10:24:51,427 [mcmc] New sample, #416:
Omega_m:0.5082423
2023-07-02 10:24:51,427 [model] Posterior to be computed for parameters {'Omega_m': 0.15001178474665575}
2023-07-02 10:24:51,427 [prior] Evaluating prior at array([0.15001178])
2023-07-02 10:24:51,427 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:51,427 [model] Got input parameters: {'Omega_m': 0.15001178474665575, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:51,427 [classy] Got parameters {'Omega_m': 0.15001178474665575, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:51,427 [classy] Computing new state
2023-07-02 10:24:51,427 [classy] Setting parameters: {'Omega_m': 0.15001178474665575, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:51,475 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 173.09995122394395}
2023-07-02 10:24:51,475 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:51,477 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.63456
2023-07-02 10:24:51,477 [model] Computed derived parameters: {}
2023-07-02 10:24:51,477 [model] Posterior to be computed for parameters {'Omega_m': 0.3443193306891126}
2023-07-02 10:24:51,477 [prior] Evaluating prior at array([0.34431933])
2023-07-02 10:24:51,477 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:51,477 [model] Got input parameters: {'Omega_m': 0.3443193306891126, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:51,477 [classy] Got parameters {'Omega_m': 0.3443193306891126, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:51,477 [classy] Computing new state
2023-07-02 10:24:51,477 [classy] Setting parameters: {'Omega_m': 0.3443193306891126, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:51,525 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.59387526439167}
2023-07-02 10:24:51,525 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:51,527 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0577521
2023-07-02 10:24:51,527 [model] Computed derived parameters: {}
2023-07-02 10:24:51,527 [mcmc] New sample, #417:
Omega_m:0.3614252
2023-07-02 10:24:51,527 [model] Posterior to be computed for parameters {'Omega_m': 0.87421690913155}
2023-07-02 10:24:51,527 [prior] Evaluating prior at array([0.87421691])
2023-07-02 10:24:51,527 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:51,527 [model] Got input parameters: {'Omega_m': 0.87421690913155, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:51,527 [classy] Got parameters {'Omega_m': 0.87421690913155, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:51,528 [classy] Computing new state
2023-07-02 10:24:51,528 [classy] Setting parameters: {'Omega_m': 0.87421690913155, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:51,575 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 108.04703666505206}
2023-07-02 10:24:51,575 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:51,577 [bao_likelihood.baolikelihood] Computed log-likelihood = -7.4315
2023-07-02 10:24:51,577 [model] Computed derived parameters: {}
2023-07-02 10:24:51,577 [model] Posterior to be computed for parameters {'Omega_m': 0.2806338643456273}
2023-07-02 10:24:51,577 [prior] Evaluating prior at array([0.28063386])
2023-07-02 10:24:51,577 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:51,577 [model] Got input parameters: {'Omega_m': 0.2806338643456273, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:51,577 [classy] Got parameters {'Omega_m': 0.2806338643456273, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:51,577 [classy] Computing new state
2023-07-02 10:24:51,578 [classy] Setting parameters: {'Omega_m': 0.2806338643456273, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:51,625 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.27575194931487}
2023-07-02 10:24:51,625 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:51,627 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0677095
2023-07-02 10:24:51,627 [model] Computed derived parameters: {}
2023-07-02 10:24:51,627 [mcmc] New sample, #418:
Omega_m:0.3443193
2023-07-02 10:24:51,627 [model] Posterior to be computed for parameters {'Omega_m': 0.32923797554627726}
2023-07-02 10:24:51,627 [prior] Evaluating prior at array([0.32923798])
2023-07-02 10:24:51,627 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:51,627 [model] Got input parameters: {'Omega_m': 0.32923797554627726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:51,627 [classy] Got parameters {'Omega_m': 0.32923797554627726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:51,627 [classy] Computing new state
2023-07-02 10:24:51,627 [classy] Setting parameters: {'Omega_m': 0.32923797554627726, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:51,676 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.29081874657084}
2023-07-02 10:24:51,676 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:51,678 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0167233
2023-07-02 10:24:51,678 [model] Computed derived parameters: {}
2023-07-02 10:24:51,678 [mcmc] New sample, #419:
Omega_m:0.2806339
2023-07-02 10:24:51,678 [model] Posterior to be computed for parameters {'Omega_m': 0.6025795779497076}
2023-07-02 10:24:51,678 [prior] Evaluating prior at array([0.60257958])
2023-07-02 10:24:51,678 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:51,678 [model] Got input parameters: {'Omega_m': 0.6025795779497076, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:51,678 [classy] Got parameters {'Omega_m': 0.6025795779497076, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:51,678 [classy] Computing new state
2023-07-02 10:24:51,678 [classy] Setting parameters: {'Omega_m': 0.6025795779497076, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:51,727 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 122.11166858673302}
2023-07-02 10:24:51,727 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:51,730 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.90223
2023-07-02 10:24:51,730 [model] Computed derived parameters: {}
2023-07-02 10:24:51,730 [model] Posterior to be computed for parameters {'Omega_m': 0.2023026033897107}
2023-07-02 10:24:51,730 [prior] Evaluating prior at array([0.2023026])
2023-07-02 10:24:51,730 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:51,730 [model] Got input parameters: {'Omega_m': 0.2023026033897107, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:51,730 [classy] Got parameters {'Omega_m': 0.2023026033897107, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:51,730 [classy] Computing new state
2023-07-02 10:24:51,730 [classy] Setting parameters: {'Omega_m': 0.2023026033897107, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:51,777 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 163.07729046721232}
2023-07-02 10:24:51,777 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:51,780 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.01383
2023-07-02 10:24:51,780 [model] Computed derived parameters: {}
2023-07-02 10:24:51,780 [mcmc] New sample, #420:
Omega_m:0.329238
2023-07-02 10:24:51,780 [model] Posterior to be computed for parameters {'Omega_m': 0.5419348073468846}
2023-07-02 10:24:51,780 [prior] Evaluating prior at array([0.54193481])
2023-07-02 10:24:51,780 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:51,780 [model] Got input parameters: {'Omega_m': 0.5419348073468846, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:51,780 [classy] Got parameters {'Omega_m': 0.5419348073468846, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:51,780 [classy] Computing new state
2023-07-02 10:24:51,780 [classy] Setting parameters: {'Omega_m': 0.5419348073468846, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:51,827 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 126.18559373674135}
2023-07-02 10:24:51,828 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:51,830 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.00987
2023-07-02 10:24:51,830 [model] Computed derived parameters: {}
2023-07-02 10:24:51,830 [model] Posterior to be computed for parameters {'Omega_m': 0.5066237293406393}
2023-07-02 10:24:51,830 [prior] Evaluating prior at array([0.50662373])
2023-07-02 10:24:51,830 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:51,830 [model] Got input parameters: {'Omega_m': 0.5066237293406393, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:51,830 [classy] Got parameters {'Omega_m': 0.5066237293406393, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:51,830 [classy] Computing new state
2023-07-02 10:24:51,830 [classy] Setting parameters: {'Omega_m': 0.5066237293406393, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:51,877 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 128.77956314268334}
2023-07-02 10:24:51,878 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:51,880 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.53224
2023-07-02 10:24:51,880 [model] Computed derived parameters: {}
2023-07-02 10:24:51,880 [mcmc] New sample, #421:
Omega_m:0.2023026
2023-07-02 10:24:51,880 [model] Posterior to be computed for parameters {'Omega_m': 1.197500045254602}
2023-07-02 10:24:51,880 [prior] Evaluating prior at array([1.19750005])
2023-07-02 10:24:51,880 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:51,880 [model] Posterior to be computed for parameters {'Omega_m': 0.4699972885092816}
2023-07-02 10:24:51,880 [prior] Evaluating prior at array([0.46999729])
2023-07-02 10:24:51,880 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:51,881 [model] Got input parameters: {'Omega_m': 0.4699972885092816, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:51,881 [classy] Got parameters {'Omega_m': 0.4699972885092816, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:51,881 [classy] Computing new state
2023-07-02 10:24:51,881 [classy] Setting parameters: {'Omega_m': 0.4699972885092816, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:51,928 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 131.67044549921172}
2023-07-02 10:24:51,928 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:51,930 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.08013
2023-07-02 10:24:51,930 [model] Computed derived parameters: {}
2023-07-02 10:24:51,931 [mcmc] New sample, #422:
Omega_m:0.5066237
2023-07-02 10:24:51,931 [model] Posterior to be computed for parameters {'Omega_m': 0.7694356774850792}
2023-07-02 10:24:51,931 [prior] Evaluating prior at array([0.76943568])
2023-07-02 10:24:51,931 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:51,931 [model] Got input parameters: {'Omega_m': 0.7694356774850792, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:51,931 [classy] Got parameters {'Omega_m': 0.7694356774850792, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:51,931 [classy] Computing new state
2023-07-02 10:24:51,931 [classy] Setting parameters: {'Omega_m': 0.7694356774850792, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:51,977 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 112.81897686489529}
2023-07-02 10:24:51,978 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:51,980 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.62915
2023-07-02 10:24:51,980 [model] Computed derived parameters: {}
2023-07-02 10:24:51,980 [model] Posterior to be computed for parameters {'Omega_m': 0.833578088297452}
2023-07-02 10:24:51,980 [prior] Evaluating prior at array([0.83357809])
2023-07-02 10:24:51,981 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:51,981 [model] Got input parameters: {'Omega_m': 0.833578088297452, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:51,981 [classy] Got parameters {'Omega_m': 0.833578088297452, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:51,981 [classy] Computing new state
2023-07-02 10:24:51,981 [classy] Setting parameters: {'Omega_m': 0.833578088297452, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:52,036 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 109.81820859135057}
2023-07-02 10:24:52,036 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:52,038 [bao_likelihood.baolikelihood] Computed log-likelihood = -6.72902
2023-07-02 10:24:52,038 [model] Computed derived parameters: {}
2023-07-02 10:24:52,038 [model] Posterior to be computed for parameters {'Omega_m': 0.7839807322063569}
2023-07-02 10:24:52,038 [prior] Evaluating prior at array([0.78398073])
2023-07-02 10:24:52,038 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:52,038 [model] Got input parameters: {'Omega_m': 0.7839807322063569, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:52,038 [classy] Got parameters {'Omega_m': 0.7839807322063569, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:52,038 [classy] Computing new state
2023-07-02 10:24:52,039 [classy] Setting parameters: {'Omega_m': 0.7839807322063569, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:52,087 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 112.11488315905197}
2023-07-02 10:24:52,087 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:52,089 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.8772
2023-07-02 10:24:52,089 [model] Computed derived parameters: {}
2023-07-02 10:24:52,089 [model] Posterior to be computed for parameters {'Omega_m': 0.4399397764328308}
2023-07-02 10:24:52,089 [prior] Evaluating prior at array([0.43993978])
2023-07-02 10:24:52,089 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:52,089 [model] Got input parameters: {'Omega_m': 0.4399397764328308, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:52,089 [classy] Got parameters {'Omega_m': 0.4399397764328308, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:52,089 [classy] Computing new state
2023-07-02 10:24:52,089 [classy] Setting parameters: {'Omega_m': 0.4399397764328308, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:52,139 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 134.21507472043444}
2023-07-02 10:24:52,139 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:52,141 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.750202
2023-07-02 10:24:52,141 [model] Computed derived parameters: {}
2023-07-02 10:24:52,141 [mcmc] New sample, #423:
Omega_m:0.4699973
2023-07-02 10:24:52,141 [model] Posterior to be computed for parameters {'Omega_m': 0.43529853234449734}
2023-07-02 10:24:52,141 [prior] Evaluating prior at array([0.43529853])
2023-07-02 10:24:52,141 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:52,141 [model] Got input parameters: {'Omega_m': 0.43529853234449734, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:52,141 [classy] Got parameters {'Omega_m': 0.43529853234449734, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:52,141 [classy] Computing new state
2023-07-02 10:24:52,141 [classy] Setting parameters: {'Omega_m': 0.43529853234449734, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:52,190 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 134.62314468456552}
2023-07-02 10:24:52,190 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:52,192 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.703097
2023-07-02 10:24:52,192 [model] Computed derived parameters: {}
2023-07-02 10:24:52,192 [mcmc] New sample, #424:
Omega_m:0.4399398
2023-07-02 10:24:52,192 [model] Posterior to be computed for parameters {'Omega_m': 0.42970801125083347}
2023-07-02 10:24:52,192 [prior] Evaluating prior at array([0.42970801])
2023-07-02 10:24:52,192 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:52,192 [model] Got input parameters: {'Omega_m': 0.42970801125083347, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:52,192 [classy] Got parameters {'Omega_m': 0.42970801125083347, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:52,192 [classy] Computing new state
2023-07-02 10:24:52,193 [classy] Setting parameters: {'Omega_m': 0.42970801125083347, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:52,241 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 135.1203113760143}
2023-07-02 10:24:52,242 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:52,243 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.647856
2023-07-02 10:24:52,243 [model] Computed derived parameters: {}
2023-07-02 10:24:52,243 [mcmc] New sample, #425:
Omega_m:0.4352985
2023-07-02 10:24:52,243 [model] Posterior to be computed for parameters {'Omega_m': 0.5874781931486645}
2023-07-02 10:24:52,243 [prior] Evaluating prior at array([0.58747819])
2023-07-02 10:24:52,244 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:52,244 [model] Got input parameters: {'Omega_m': 0.5874781931486645, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:52,244 [classy] Got parameters {'Omega_m': 0.5874781931486645, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:52,244 [classy] Computing new state
2023-07-02 10:24:52,244 [classy] Setting parameters: {'Omega_m': 0.5874781931486645, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:52,292 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 123.08490706643138}
2023-07-02 10:24:52,292 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:52,294 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.67292
2023-07-02 10:24:52,294 [model] Computed derived parameters: {}
2023-07-02 10:24:52,294 [mcmc] New sample, #426:
Omega_m:0.429708
2023-07-02 10:24:52,294 [model] Posterior to be computed for parameters {'Omega_m': 0.7731889371190399}
2023-07-02 10:24:52,294 [prior] Evaluating prior at array([0.77318894])
2023-07-02 10:24:52,295 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:52,295 [model] Got input parameters: {'Omega_m': 0.7731889371190399, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:52,295 [classy] Got parameters {'Omega_m': 0.7731889371190399, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:52,295 [classy] Computing new state
2023-07-02 10:24:52,295 [classy] Setting parameters: {'Omega_m': 0.7731889371190399, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:52,343 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 112.63589192344611}
2023-07-02 10:24:52,343 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:52,345 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.69307
2023-07-02 10:24:52,345 [model] Computed derived parameters: {}
2023-07-02 10:24:52,345 [model] Posterior to be computed for parameters {'Omega_m': 1.3548471072314854}
2023-07-02 10:24:52,345 [prior] Evaluating prior at array([1.35484711])
2023-07-02 10:24:52,346 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:52,346 [model] Posterior to be computed for parameters {'Omega_m': 0.6800621098437819}
2023-07-02 10:24:52,346 [prior] Evaluating prior at array([0.68006211])
2023-07-02 10:24:52,346 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:52,346 [model] Got input parameters: {'Omega_m': 0.6800621098437819, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:52,346 [classy] Got parameters {'Omega_m': 0.6800621098437819, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:52,346 [classy] Computing new state
2023-07-02 10:24:52,346 [classy] Setting parameters: {'Omega_m': 0.6800621098437819, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:52,393 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 117.49192764542691}
2023-07-02 10:24:52,393 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:52,395 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.13357
2023-07-02 10:24:52,395 [model] Computed derived parameters: {}
2023-07-02 10:24:52,395 [mcmc] New sample, #427:
Omega_m:0.5874782
2023-07-02 10:24:52,395 [model] Posterior to be computed for parameters {'Omega_m': 0.7073102493066185}
2023-07-02 10:24:52,395 [prior] Evaluating prior at array([0.70731025])
2023-07-02 10:24:52,395 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:52,395 [model] Got input parameters: {'Omega_m': 0.7073102493066185, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:52,395 [classy] Got parameters {'Omega_m': 0.7073102493066185, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:52,395 [classy] Computing new state
2023-07-02 10:24:52,396 [classy] Setting parameters: {'Omega_m': 0.7073102493066185, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:52,443 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 115.99978828224823}
2023-07-02 10:24:52,443 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:52,445 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.58312
2023-07-02 10:24:52,445 [model] Computed derived parameters: {}
2023-07-02 10:24:52,445 [model] Posterior to be computed for parameters {'Omega_m': 0.4613570781872015}
2023-07-02 10:24:52,445 [prior] Evaluating prior at array([0.46135708])
2023-07-02 10:24:52,445 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:52,445 [model] Got input parameters: {'Omega_m': 0.4613570781872015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:52,445 [classy] Got parameters {'Omega_m': 0.4613570781872015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:52,445 [classy] Computing new state
2023-07-02 10:24:52,445 [classy] Setting parameters: {'Omega_m': 0.4613570781872015, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:52,494 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 132.3851071583867}
2023-07-02 10:24:52,494 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:52,496 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.98112
2023-07-02 10:24:52,496 [model] Computed derived parameters: {}
2023-07-02 10:24:52,496 [mcmc] New sample, #428:
Omega_m:0.6800621
2023-07-02 10:24:52,496 [model] Posterior to be computed for parameters {'Omega_m': 1.2965372910821473}
2023-07-02 10:24:52,496 [prior] Evaluating prior at array([1.29653729])
2023-07-02 10:24:52,496 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:52,496 [model] Posterior to be computed for parameters {'Omega_m': 0.433751590711657}
2023-07-02 10:24:52,496 [prior] Evaluating prior at array([0.43375159])
2023-07-02 10:24:52,497 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:52,497 [model] Got input parameters: {'Omega_m': 0.433751590711657, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:52,497 [classy] Got parameters {'Omega_m': 0.433751590711657, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:52,497 [classy] Computing new state
2023-07-02 10:24:52,497 [classy] Setting parameters: {'Omega_m': 0.433751590711657, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:52,545 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 134.76009381562315}
2023-07-02 10:24:52,545 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:52,547 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.687646
2023-07-02 10:24:52,547 [model] Computed derived parameters: {}
2023-07-02 10:24:52,547 [mcmc] New sample, #429:
Omega_m:0.4613571
2023-07-02 10:24:52,547 [model] Posterior to be computed for parameters {'Omega_m': 0.6356044176458548}
2023-07-02 10:24:52,547 [prior] Evaluating prior at array([0.63560442])
2023-07-02 10:24:52,547 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:52,547 [model] Got input parameters: {'Omega_m': 0.6356044176458548, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:52,547 [classy] Got parameters {'Omega_m': 0.6356044176458548, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:52,547 [classy] Computing new state
2023-07-02 10:24:52,547 [classy] Setting parameters: {'Omega_m': 0.6356044176458548, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:52,593 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 120.06973189124147}
2023-07-02 10:24:52,593 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:52,596 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.41704
2023-07-02 10:24:52,596 [model] Computed derived parameters: {}
2023-07-02 10:24:52,596 [model] Posterior to be computed for parameters {'Omega_m': 0.22830072177813987}
2023-07-02 10:24:52,596 [prior] Evaluating prior at array([0.22830072])
2023-07-02 10:24:52,596 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:52,596 [model] Got input parameters: {'Omega_m': 0.22830072177813987, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:52,596 [classy] Got parameters {'Omega_m': 0.22830072177813987, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:52,596 [classy] Computing new state
2023-07-02 10:24:52,596 [classy] Setting parameters: {'Omega_m': 0.22830072177813987, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:52,645 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 158.8042634028049}
2023-07-02 10:24:52,645 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:52,647 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.54646
2023-07-02 10:24:52,647 [model] Computed derived parameters: {}
2023-07-02 10:24:52,647 [mcmc] New sample, #430:
Omega_m:0.4337516
2023-07-02 10:24:52,647 [model] Posterior to be computed for parameters {'Omega_m': 0.3304817502187113}
2023-07-02 10:24:52,647 [prior] Evaluating prior at array([0.33048175])
2023-07-02 10:24:52,647 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:52,647 [model] Got input parameters: {'Omega_m': 0.3304817502187113, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:52,647 [classy] Got parameters {'Omega_m': 0.3304817502187113, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:52,648 [classy] Computing new state
2023-07-02 10:24:52,648 [classy] Setting parameters: {'Omega_m': 0.3304817502187113, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:52,694 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.14823956229984}
2023-07-02 10:24:52,695 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:52,697 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0192101
2023-07-02 10:24:52,697 [model] Computed derived parameters: {}
2023-07-02 10:24:52,697 [mcmc] New sample, #431:
Omega_m:0.2283007
2023-07-02 10:24:52,697 [model] Posterior to be computed for parameters {'Omega_m': 0.42739131906829947}
2023-07-02 10:24:52,697 [prior] Evaluating prior at array([0.42739132])
2023-07-02 10:24:52,697 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:52,697 [model] Got input parameters: {'Omega_m': 0.42739131906829947, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:52,697 [classy] Got parameters {'Omega_m': 0.42739131906829947, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:52,697 [classy] Computing new state
2023-07-02 10:24:52,697 [classy] Setting parameters: {'Omega_m': 0.42739131906829947, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:52,745 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 135.328169915425}
2023-07-02 10:24:52,745 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:52,747 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.625457
2023-07-02 10:24:52,747 [model] Computed derived parameters: {}
2023-07-02 10:24:52,747 [model] Posterior to be computed for parameters {'Omega_m': 0.17772578165008182}
2023-07-02 10:24:52,747 [prior] Evaluating prior at array([0.17772578])
2023-07-02 10:24:52,748 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:52,748 [model] Got input parameters: {'Omega_m': 0.17772578165008182, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:52,748 [classy] Got parameters {'Omega_m': 0.17772578165008182, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:52,748 [classy] Computing new state
2023-07-02 10:24:52,748 [classy] Setting parameters: {'Omega_m': 0.17772578165008182, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:52,795 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 167.52110724393486}
2023-07-02 10:24:52,795 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:52,797 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.64374
2023-07-02 10:24:52,797 [model] Computed derived parameters: {}
2023-07-02 10:24:52,797 [mcmc] New sample, #432:
Omega_m:0.3304818
2023-07-02 10:24:52,797 [model] Posterior to be computed for parameters {'Omega_m': 0.10891982388073515}
2023-07-02 10:24:52,797 [prior] Evaluating prior at array([0.10891982])
2023-07-02 10:24:52,797 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:52,797 [model] Got input parameters: {'Omega_m': 0.10891982388073515, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:52,797 [classy] Got parameters {'Omega_m': 0.10891982388073515, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:52,798 [classy] Computing new state
2023-07-02 10:24:52,798 [classy] Setting parameters: {'Omega_m': 0.10891982388073515, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:52,845 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 182.79333169423265}
2023-07-02 10:24:52,845 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:52,847 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.85927
2023-07-02 10:24:52,847 [model] Computed derived parameters: {}
2023-07-02 10:24:52,847 [model] Posterior to be computed for parameters {'Omega_m': -0.12960109758764807}
2023-07-02 10:24:52,847 [prior] Evaluating prior at array([-0.1296011])
2023-07-02 10:24:52,848 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:52,848 [model] Posterior to be computed for parameters {'Omega_m': 0.16957209924293803}
2023-07-02 10:24:52,848 [prior] Evaluating prior at array([0.1695721])
2023-07-02 10:24:52,848 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:52,848 [model] Got input parameters: {'Omega_m': 0.16957209924293803, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:52,848 [classy] Got parameters {'Omega_m': 0.16957209924293803, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:52,848 [classy] Computing new state
2023-07-02 10:24:52,848 [classy] Setting parameters: {'Omega_m': 0.16957209924293803, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:52,896 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 169.09481584803484}
2023-07-02 10:24:52,896 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:52,900 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.90104
2023-07-02 10:24:52,900 [model] Computed derived parameters: {}
2023-07-02 10:24:52,900 [mcmc] New sample, #433:
Omega_m:0.1777258
2023-07-02 10:24:52,900 [model] Posterior to be computed for parameters {'Omega_m': 0.35119760407553424}
2023-07-02 10:24:52,900 [prior] Evaluating prior at array([0.3511976])
2023-07-02 10:24:52,900 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:52,900 [model] Got input parameters: {'Omega_m': 0.35119760407553424, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:52,900 [classy] Got parameters {'Omega_m': 0.35119760407553424, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:52,900 [classy] Computing new state
2023-07-02 10:24:52,900 [classy] Setting parameters: {'Omega_m': 0.35119760407553424, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:52,949 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.84235238186002}
2023-07-02 10:24:52,950 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:52,951 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0839509
2023-07-02 10:24:52,951 [model] Computed derived parameters: {}
2023-07-02 10:24:52,951 [mcmc] New sample, #434:
Omega_m:0.1695721
2023-07-02 10:24:52,951 [model] Posterior to be computed for parameters {'Omega_m': -0.09756868853909945}
2023-07-02 10:24:52,952 [prior] Evaluating prior at array([-0.09756869])
2023-07-02 10:24:52,952 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:52,952 [model] Posterior to be computed for parameters {'Omega_m': -0.34353085489925617}
2023-07-02 10:24:52,952 [prior] Evaluating prior at array([-0.34353085])
2023-07-02 10:24:52,952 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:52,952 [model] Posterior to be computed for parameters {'Omega_m': 0.22860511962845703}
2023-07-02 10:24:52,952 [prior] Evaluating prior at array([0.22860512])
2023-07-02 10:24:52,952 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:52,952 [model] Got input parameters: {'Omega_m': 0.22860511962845703, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:52,952 [classy] Got parameters {'Omega_m': 0.22860511962845703, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:52,952 [classy] Computing new state
2023-07-02 10:24:52,952 [classy] Setting parameters: {'Omega_m': 0.22860511962845703, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:53,001 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 158.7565575633803}
2023-07-02 10:24:53,001 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:53,003 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.542026
2023-07-02 10:24:53,003 [model] Computed derived parameters: {}
2023-07-02 10:24:53,004 [model] Posterior to be computed for parameters {'Omega_m': 0.6533852298182787}
2023-07-02 10:24:53,004 [prior] Evaluating prior at array([0.65338523])
2023-07-02 10:24:53,004 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:53,004 [model] Got input parameters: {'Omega_m': 0.6533852298182787, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:53,004 [classy] Got parameters {'Omega_m': 0.6533852298182787, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:53,004 [classy] Computing new state
2023-07-02 10:24:53,004 [classy] Setting parameters: {'Omega_m': 0.6533852298182787, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:53,053 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 119.0163331278112}
2023-07-02 10:24:53,053 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:53,055 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.70075
2023-07-02 10:24:53,055 [model] Computed derived parameters: {}
2023-07-02 10:24:53,055 [model] Posterior to be computed for parameters {'Omega_m': 0.5747935099801675}
2023-07-02 10:24:53,055 [prior] Evaluating prior at array([0.57479351])
2023-07-02 10:24:53,055 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:53,055 [model] Got input parameters: {'Omega_m': 0.5747935099801675, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:53,055 [classy] Got parameters {'Omega_m': 0.5747935099801675, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:53,055 [classy] Computing new state
2023-07-02 10:24:53,056 [classy] Setting parameters: {'Omega_m': 0.5747935099801675, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:53,105 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 123.92280915182621}
2023-07-02 10:24:53,105 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:53,107 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.48367
2023-07-02 10:24:53,107 [model] Computed derived parameters: {}
2023-07-02 10:24:53,107 [model] Posterior to be computed for parameters {'Omega_m': 0.2955783918740894}
2023-07-02 10:24:53,107 [prior] Evaluating prior at array([0.29557839])
2023-07-02 10:24:53,107 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:53,107 [model] Got input parameters: {'Omega_m': 0.2955783918740894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:53,107 [classy] Got parameters {'Omega_m': 0.2955783918740894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:53,107 [classy] Computing new state
2023-07-02 10:24:53,108 [classy] Setting parameters: {'Omega_m': 0.2955783918740894, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:53,158 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.34458724194678}
2023-07-02 10:24:53,158 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:53,160 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0184937
2023-07-02 10:24:53,160 [model] Computed derived parameters: {}
2023-07-02 10:24:53,160 [mcmc] New sample, #435:
Omega_m:0.3511976
2023-07-02 10:24:53,160 [model] Posterior to be computed for parameters {'Omega_m': 0.18709117175057555}
2023-07-02 10:24:53,160 [prior] Evaluating prior at array([0.18709117])
2023-07-02 10:24:53,160 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:53,160 [model] Got input parameters: {'Omega_m': 0.18709117175057555, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:53,160 [classy] Got parameters {'Omega_m': 0.18709117175057555, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:53,160 [classy] Computing new state
2023-07-02 10:24:53,160 [classy] Setting parameters: {'Omega_m': 0.18709117175057555, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:53,211 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 165.77685888245034}
2023-07-02 10:24:53,211 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:53,213 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.37932
2023-07-02 10:24:53,213 [model] Computed derived parameters: {}
2023-07-02 10:24:53,213 [mcmc] New sample, #436:
Omega_m:0.2955784
2023-07-02 10:24:53,213 [model] Posterior to be computed for parameters {'Omega_m': -0.10217597968914022}
2023-07-02 10:24:53,213 [prior] Evaluating prior at array([-0.10217598])
2023-07-02 10:24:53,213 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:53,214 [model] Posterior to be computed for parameters {'Omega_m': 0.2443235813161443}
2023-07-02 10:24:53,214 [prior] Evaluating prior at array([0.24432358])
2023-07-02 10:24:53,214 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:53,214 [model] Got input parameters: {'Omega_m': 0.2443235813161443, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:53,214 [classy] Got parameters {'Omega_m': 0.2443235813161443, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:53,214 [classy] Computing new state
2023-07-02 10:24:53,214 [classy] Setting parameters: {'Omega_m': 0.2443235813161443, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:53,264 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 156.35984802825078}
2023-07-02 10:24:53,264 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:53,266 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.34192
2023-07-02 10:24:53,266 [model] Computed derived parameters: {}
2023-07-02 10:24:53,266 [mcmc] New sample, #437:
Omega_m:0.1870912
2023-07-02 10:24:53,266 [model] Posterior to be computed for parameters {'Omega_m': 0.4390780027300739}
2023-07-02 10:24:53,266 [prior] Evaluating prior at array([0.439078])
2023-07-02 10:24:53,266 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:53,266 [model] Got input parameters: {'Omega_m': 0.4390780027300739, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:53,266 [classy] Got parameters {'Omega_m': 0.4390780027300739, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:53,266 [classy] Computing new state
2023-07-02 10:24:53,266 [classy] Setting parameters: {'Omega_m': 0.4390780027300739, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:53,316 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 134.29052797349036}
2023-07-02 10:24:53,316 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:53,318 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.741372
2023-07-02 10:24:53,318 [model] Computed derived parameters: {}
2023-07-02 10:24:53,318 [mcmc] New sample, #438:
Omega_m:0.2443236
2023-07-02 10:24:53,318 [model] Posterior to be computed for parameters {'Omega_m': 0.9962645781022594}
2023-07-02 10:24:53,318 [prior] Evaluating prior at array([0.99626458])
2023-07-02 10:24:53,318 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:53,318 [model] Got input parameters: {'Omega_m': 0.9962645781022594, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:53,318 [classy] Got parameters {'Omega_m': 0.9962645781022594, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:53,318 [classy] Computing new state
2023-07-02 10:24:53,318 [classy] Setting parameters: {'Omega_m': 0.9962645781022594, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:53,366 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 103.23978926683354}
2023-07-02 10:24:53,367 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:53,368 [bao_likelihood.baolikelihood] Computed log-likelihood = -9.54631
2023-07-02 10:24:53,368 [model] Computed derived parameters: {}
2023-07-02 10:24:53,368 [model] Posterior to be computed for parameters {'Omega_m': 0.6529173404474666}
2023-07-02 10:24:53,368 [prior] Evaluating prior at array([0.65291734])
2023-07-02 10:24:53,369 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:53,369 [model] Got input parameters: {'Omega_m': 0.6529173404474666, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:53,369 [classy] Got parameters {'Omega_m': 0.6529173404474666, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:53,369 [classy] Computing new state
2023-07-02 10:24:53,369 [classy] Setting parameters: {'Omega_m': 0.6529173404474666, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:53,416 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 119.04366058374174}
2023-07-02 10:24:53,416 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:53,418 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.69324
2023-07-02 10:24:53,418 [model] Computed derived parameters: {}
2023-07-02 10:24:53,418 [model] Posterior to be computed for parameters {'Omega_m': 0.07498858836129024}
2023-07-02 10:24:53,418 [prior] Evaluating prior at array([0.07498859])
2023-07-02 10:24:53,419 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:53,419 [model] Posterior to be computed for parameters {'Omega_m': 0.6787494557828322}
2023-07-02 10:24:53,419 [prior] Evaluating prior at array([0.67874946])
2023-07-02 10:24:53,419 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:53,419 [model] Got input parameters: {'Omega_m': 0.6787494557828322, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:53,419 [classy] Got parameters {'Omega_m': 0.6787494557828322, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:53,419 [classy] Computing new state
2023-07-02 10:24:53,419 [classy] Setting parameters: {'Omega_m': 0.6787494557828322, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:53,465 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 117.5654292590559}
2023-07-02 10:24:53,465 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:53,467 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.11209
2023-07-02 10:24:53,467 [model] Computed derived parameters: {}
2023-07-02 10:24:53,467 [model] Posterior to be computed for parameters {'Omega_m': 0.8964698385562446}
2023-07-02 10:24:53,467 [prior] Evaluating prior at array([0.89646984])
2023-07-02 10:24:53,467 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:53,467 [model] Got input parameters: {'Omega_m': 0.8964698385562446, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:53,468 [classy] Got parameters {'Omega_m': 0.8964698385562446, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:53,468 [classy] Computing new state
2023-07-02 10:24:53,468 [classy] Setting parameters: {'Omega_m': 0.8964698385562446, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:53,514 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 107.11590141661479}
2023-07-02 10:24:53,514 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:53,516 [bao_likelihood.baolikelihood] Computed log-likelihood = -7.81708
2023-07-02 10:24:53,516 [model] Computed derived parameters: {}
2023-07-02 10:24:53,516 [model] Posterior to be computed for parameters {'Omega_m': 0.07842868325733798}
2023-07-02 10:24:53,516 [prior] Evaluating prior at array([0.07842868])
2023-07-02 10:24:53,516 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:53,516 [model] Posterior to be computed for parameters {'Omega_m': -0.04992282667118003}
2023-07-02 10:24:53,516 [prior] Evaluating prior at array([-0.04992283])
2023-07-02 10:24:53,516 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:53,517 [model] Posterior to be computed for parameters {'Omega_m': 0.4391277894817036}
2023-07-02 10:24:53,517 [prior] Evaluating prior at array([0.43912779])
2023-07-02 10:24:53,517 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:53,517 [model] Got input parameters: {'Omega_m': 0.4391277894817036, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:53,517 [classy] Got parameters {'Omega_m': 0.4391277894817036, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:53,517 [classy] Computing new state
2023-07-02 10:24:53,517 [classy] Setting parameters: {'Omega_m': 0.4391277894817036, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:53,565 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 134.28616344845622}
2023-07-02 10:24:53,565 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:53,567 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.741882
2023-07-02 10:24:53,567 [model] Computed derived parameters: {}
2023-07-02 10:24:53,567 [mcmc] New sample, #439:
Omega_m:0.439078
2023-07-02 10:24:53,567 [model] Posterior to be computed for parameters {'Omega_m': 0.10599605075573809}
2023-07-02 10:24:53,567 [prior] Evaluating prior at array([0.10599605])
2023-07-02 10:24:53,567 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:53,567 [model] Got input parameters: {'Omega_m': 0.10599605075573809, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:53,567 [classy] Got parameters {'Omega_m': 0.10599605075573809, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:53,567 [classy] Computing new state
2023-07-02 10:24:53,567 [classy] Setting parameters: {'Omega_m': 0.10599605075573809, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:53,615 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 183.56238438227797}
2023-07-02 10:24:53,615 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:53,617 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.062
2023-07-02 10:24:53,617 [model] Computed derived parameters: {}
2023-07-02 10:24:53,617 [model] Posterior to be computed for parameters {'Omega_m': 0.48039377902710834}
2023-07-02 10:24:53,617 [prior] Evaluating prior at array([0.48039378])
2023-07-02 10:24:53,617 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:53,617 [model] Got input parameters: {'Omega_m': 0.48039377902710834, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:53,617 [classy] Got parameters {'Omega_m': 0.48039377902710834, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:53,617 [classy] Computing new state
2023-07-02 10:24:53,617 [classy] Setting parameters: {'Omega_m': 0.48039377902710834, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:53,666 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.82758881330835}
2023-07-02 10:24:53,666 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:53,668 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.20336
2023-07-02 10:24:53,668 [model] Computed derived parameters: {}
2023-07-02 10:24:53,668 [mcmc] New sample, #440:
Omega_m:0.4391278
2023-07-02 10:24:53,668 [mcmc] Learn + convergence test @ 440 samples accepted.
2023-07-02 10:24:53,668 [mcmc] Ready to check convergence and learn a new proposal covmat
2023-07-02 10:24:53,673 [mcmc] - Acceptance rate: 0.420
2023-07-02 10:24:53,673 [mcmc] - Condition number = 1
2023-07-02 10:24:53,673 [mcmc] - Eigenvalues = array([0.02193125])
2023-07-02 10:24:53,673 [mcmc] - Convergence of means: R-1 = 0.021931 after 352 accepted steps
2023-07-02 10:24:53,673 [mcmc] - Updated covariance matrix of proposal pdf.
2023-07-02 10:24:53,673 [mcmc] array([[0.01224873]])
2023-07-02 10:24:53,684 [mcmc] Dumped checkpoint and progress info, and current covmat.
2023-07-02 10:24:53,684 [model] Posterior to be computed for parameters {'Omega_m': 0.7840185275272447}
2023-07-02 10:24:53,684 [prior] Evaluating prior at array([0.78401853])
2023-07-02 10:24:53,684 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:53,684 [model] Got input parameters: {'Omega_m': 0.7840185275272447, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:53,684 [classy] Got parameters {'Omega_m': 0.7840185275272447, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:53,684 [classy] Computing new state
2023-07-02 10:24:53,684 [classy] Setting parameters: {'Omega_m': 0.7840185275272447, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:53,730 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 112.11307230323}
2023-07-02 10:24:53,730 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:53,732 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.87784
2023-07-02 10:24:53,732 [model] Computed derived parameters: {}
2023-07-02 10:24:53,732 [model] Posterior to be computed for parameters {'Omega_m': 1.0345929950379507}
2023-07-02 10:24:53,732 [prior] Evaluating prior at array([1.034593])
2023-07-02 10:24:53,732 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:53,732 [model] Posterior to be computed for parameters {'Omega_m': 0.5859445836287613}
2023-07-02 10:24:53,732 [prior] Evaluating prior at array([0.58594458])
2023-07-02 10:24:53,732 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:53,732 [model] Got input parameters: {'Omega_m': 0.5859445836287613, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:53,733 [classy] Got parameters {'Omega_m': 0.5859445836287613, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:53,733 [classy] Computing new state
2023-07-02 10:24:53,733 [classy] Setting parameters: {'Omega_m': 0.5859445836287613, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:53,780 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 123.18519974739237}
2023-07-02 10:24:53,780 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:53,781 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.64987
2023-07-02 10:24:53,782 [model] Computed derived parameters: {}
2023-07-02 10:24:53,782 [model] Posterior to be computed for parameters {'Omega_m': 0.9266418805082961}
2023-07-02 10:24:53,782 [prior] Evaluating prior at array([0.92664188])
2023-07-02 10:24:53,782 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:53,782 [model] Got input parameters: {'Omega_m': 0.9266418805082961, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:53,782 [classy] Got parameters {'Omega_m': 0.9266418805082961, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:53,782 [classy] Computing new state
2023-07-02 10:24:53,782 [classy] Setting parameters: {'Omega_m': 0.9266418805082961, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:53,828 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 105.89423552218476}
2023-07-02 10:24:53,828 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:53,830 [bao_likelihood.baolikelihood] Computed log-likelihood = -8.34028
2023-07-02 10:24:53,830 [model] Computed derived parameters: {}
2023-07-02 10:24:53,830 [model] Posterior to be computed for parameters {'Omega_m': -0.06098955566050912}
2023-07-02 10:24:53,830 [prior] Evaluating prior at array([-0.06098956])
2023-07-02 10:24:53,830 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:53,830 [model] Posterior to be computed for parameters {'Omega_m': 0.3758760651720021}
2023-07-02 10:24:53,830 [prior] Evaluating prior at array([0.37587607])
2023-07-02 10:24:53,831 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:53,831 [model] Got input parameters: {'Omega_m': 0.3758760651720021, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:53,831 [classy] Got parameters {'Omega_m': 0.3758760651720021, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:53,831 [classy] Computing new state
2023-07-02 10:24:53,831 [classy] Setting parameters: {'Omega_m': 0.3758760651720021, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:53,878 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.25322182260336}
2023-07-02 10:24:53,878 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:53,880 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.212546
2023-07-02 10:24:53,880 [model] Computed derived parameters: {}
2023-07-02 10:24:53,880 [mcmc] New sample, #441:
Omega_m:0.4803938
2023-07-02 10:24:53,880 [model] Posterior to be computed for parameters {'Omega_m': 0.19723526986329767}
2023-07-02 10:24:53,880 [prior] Evaluating prior at array([0.19723527])
2023-07-02 10:24:53,880 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:53,880 [model] Got input parameters: {'Omega_m': 0.19723526986329767, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:53,880 [classy] Got parameters {'Omega_m': 0.19723526986329767, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:53,880 [classy] Computing new state
2023-07-02 10:24:53,881 [classy] Setting parameters: {'Omega_m': 0.19723526986329767, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:53,928 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 163.95904617514472}
2023-07-02 10:24:53,928 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:53,930 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.1273
2023-07-02 10:24:53,930 [model] Computed derived parameters: {}
2023-07-02 10:24:53,930 [mcmc] New sample, #442:
Omega_m:0.3758761
2023-07-02 10:24:53,930 [model] Posterior to be computed for parameters {'Omega_m': 0.38158935821267803}
2023-07-02 10:24:53,931 [prior] Evaluating prior at array([0.38158936])
2023-07-02 10:24:53,931 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:53,931 [model] Got input parameters: {'Omega_m': 0.38158935821267803, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:53,931 [classy] Got parameters {'Omega_m': 0.38158935821267803, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:53,931 [classy] Computing new state
2023-07-02 10:24:53,931 [classy] Setting parameters: {'Omega_m': 0.38158935821267803, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:53,978 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 139.67647702415152}
2023-07-02 10:24:53,979 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:53,980 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.249378
2023-07-02 10:24:53,980 [model] Computed derived parameters: {}
2023-07-02 10:24:53,980 [mcmc] New sample, #443:
Omega_m:0.1972353
2023-07-02 10:24:53,981 [model] Posterior to be computed for parameters {'Omega_m': 0.20808801155648604}
2023-07-02 10:24:53,981 [prior] Evaluating prior at array([0.20808801])
2023-07-02 10:24:53,981 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:53,981 [model] Got input parameters: {'Omega_m': 0.20808801155648604, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:53,981 [classy] Got parameters {'Omega_m': 0.20808801155648604, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:53,981 [classy] Computing new state
2023-07-02 10:24:53,981 [classy] Setting parameters: {'Omega_m': 0.20808801155648604, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:54,029 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 162.09090271294613}
2023-07-02 10:24:54,029 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:54,031 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.893721
2023-07-02 10:24:54,031 [model] Computed derived parameters: {}
2023-07-02 10:24:54,031 [mcmc] New sample, #444:
Omega_m:0.3815894
2023-07-02 10:24:54,031 [model] Posterior to be computed for parameters {'Omega_m': -0.0751473947532677}
2023-07-02 10:24:54,032 [prior] Evaluating prior at array([-0.07514739])
2023-07-02 10:24:54,032 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:54,032 [model] Posterior to be computed for parameters {'Omega_m': 0.3932800369841343}
2023-07-02 10:24:54,032 [prior] Evaluating prior at array([0.39328004])
2023-07-02 10:24:54,032 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:54,032 [model] Got input parameters: {'Omega_m': 0.3932800369841343, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:54,032 [classy] Got parameters {'Omega_m': 0.3932800369841343, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:54,032 [classy] Computing new state
2023-07-02 10:24:54,032 [classy] Setting parameters: {'Omega_m': 0.3932800369841343, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:54,079 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 138.52116867122453}
2023-07-02 10:24:54,079 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:54,081 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.332263
2023-07-02 10:24:54,081 [model] Computed derived parameters: {}
2023-07-02 10:24:54,081 [mcmc] New sample, #445:
Omega_m:0.208088
2023-07-02 10:24:54,081 [model] Posterior to be computed for parameters {'Omega_m': 0.6306143938372174}
2023-07-02 10:24:54,081 [prior] Evaluating prior at array([0.63061439])
2023-07-02 10:24:54,082 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:54,082 [model] Got input parameters: {'Omega_m': 0.6306143938372174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:54,082 [classy] Got parameters {'Omega_m': 0.6306143938372174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:54,082 [classy] Computing new state
2023-07-02 10:24:54,082 [classy] Setting parameters: {'Omega_m': 0.6306143938372174, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:54,128 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 120.37098193971023}
2023-07-02 10:24:54,128 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:54,130 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.33819
2023-07-02 10:24:54,130 [model] Computed derived parameters: {}
2023-07-02 10:24:54,130 [model] Posterior to be computed for parameters {'Omega_m': 0.4049576307928636}
2023-07-02 10:24:54,130 [prior] Evaluating prior at array([0.40495763])
2023-07-02 10:24:54,130 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:54,130 [model] Got input parameters: {'Omega_m': 0.4049576307928636, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:54,130 [classy] Got parameters {'Omega_m': 0.4049576307928636, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:54,130 [classy] Computing new state
2023-07-02 10:24:54,130 [classy] Setting parameters: {'Omega_m': 0.4049576307928636, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:54,178 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 137.39922414455987}
2023-07-02 10:24:54,178 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:54,180 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.424474
2023-07-02 10:24:54,180 [model] Computed derived parameters: {}
2023-07-02 10:24:54,180 [mcmc] New sample, #446:
Omega_m:0.39328
2023-07-02 10:24:54,180 [model] Posterior to be computed for parameters {'Omega_m': -0.107305091829758}
2023-07-02 10:24:54,180 [prior] Evaluating prior at array([-0.10730509])
2023-07-02 10:24:54,180 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:54,180 [model] Posterior to be computed for parameters {'Omega_m': 0.556324701194813}
2023-07-02 10:24:54,180 [prior] Evaluating prior at array([0.5563247])
2023-07-02 10:24:54,180 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:54,180 [model] Got input parameters: {'Omega_m': 0.556324701194813, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:54,180 [classy] Got parameters {'Omega_m': 0.556324701194813, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:54,180 [classy] Computing new state
2023-07-02 10:24:54,180 [classy] Setting parameters: {'Omega_m': 0.556324701194813, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:54,228 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 125.17770068983356}
2023-07-02 10:24:54,228 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:54,230 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.21424
2023-07-02 10:24:54,230 [model] Computed derived parameters: {}
2023-07-02 10:24:54,230 [model] Posterior to be computed for parameters {'Omega_m': 0.06717386186167223}
2023-07-02 10:24:54,230 [prior] Evaluating prior at array([0.06717386])
2023-07-02 10:24:54,230 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:54,230 [model] Posterior to be computed for parameters {'Omega_m': 0.48227738671100506}
2023-07-02 10:24:54,230 [prior] Evaluating prior at array([0.48227739])
2023-07-02 10:24:54,230 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:54,230 [model] Got input parameters: {'Omega_m': 0.48227738671100506, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:54,230 [classy] Got parameters {'Omega_m': 0.48227738671100506, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:54,230 [classy] Computing new state
2023-07-02 10:24:54,230 [classy] Setting parameters: {'Omega_m': 0.48227738671100506, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:54,278 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.67683037164943}
2023-07-02 10:24:54,278 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:54,280 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.22614
2023-07-02 10:24:54,280 [model] Computed derived parameters: {}
2023-07-02 10:24:54,280 [model] Posterior to be computed for parameters {'Omega_m': 0.39716705814934616}
2023-07-02 10:24:54,280 [prior] Evaluating prior at array([0.39716706])
2023-07-02 10:24:54,280 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:54,280 [model] Got input parameters: {'Omega_m': 0.39716705814934616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:54,280 [classy] Got parameters {'Omega_m': 0.39716705814934616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:54,280 [classy] Computing new state
2023-07-02 10:24:54,280 [classy] Setting parameters: {'Omega_m': 0.39716705814934616, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:54,328 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 138.14425133847956}
2023-07-02 10:24:54,328 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:54,330 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.361945
2023-07-02 10:24:54,330 [model] Computed derived parameters: {}
2023-07-02 10:24:54,330 [mcmc] New sample, #447:
Omega_m:0.4049576
2023-07-02 10:24:54,330 [model] Posterior to be computed for parameters {'Omega_m': 0.40030809508707715}
2023-07-02 10:24:54,330 [prior] Evaluating prior at array([0.4003081])
2023-07-02 10:24:54,330 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:54,330 [model] Got input parameters: {'Omega_m': 0.40030809508707715, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:54,330 [classy] Got parameters {'Omega_m': 0.40030809508707715, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:54,330 [classy] Computing new state
2023-07-02 10:24:54,331 [classy] Setting parameters: {'Omega_m': 0.40030809508707715, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:54,379 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 137.84221319324757}
2023-07-02 10:24:54,379 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:54,381 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.386676
2023-07-02 10:24:54,381 [model] Computed derived parameters: {}
2023-07-02 10:24:54,381 [mcmc] New sample, #448:
Omega_m:0.3971671
2023-07-02 10:24:54,381 [model] Posterior to be computed for parameters {'Omega_m': 0.2947378661116574}
2023-07-02 10:24:54,381 [prior] Evaluating prior at array([0.29473787])
2023-07-02 10:24:54,381 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:54,381 [model] Got input parameters: {'Omega_m': 0.2947378661116574, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:54,381 [classy] Got parameters {'Omega_m': 0.2947378661116574, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:54,381 [classy] Computing new state
2023-07-02 10:24:54,381 [classy] Setting parameters: {'Omega_m': 0.2947378661116574, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:54,429 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.45092573921787}
2023-07-02 10:24:54,429 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:54,431 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0204013
2023-07-02 10:24:54,431 [model] Computed derived parameters: {}
2023-07-02 10:24:54,431 [mcmc] New sample, #449:
Omega_m:0.4003081
2023-07-02 10:24:54,431 [model] Posterior to be computed for parameters {'Omega_m': -0.004448947850334728}
2023-07-02 10:24:54,431 [prior] Evaluating prior at array([-0.00444895])
2023-07-02 10:24:54,431 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:54,431 [model] Posterior to be computed for parameters {'Omega_m': 0.3168329439016637}
2023-07-02 10:24:54,431 [prior] Evaluating prior at array([0.31683294])
2023-07-02 10:24:54,431 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:54,431 [model] Got input parameters: {'Omega_m': 0.3168329439016637, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:54,431 [classy] Got parameters {'Omega_m': 0.3168329439016637, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:54,431 [classy] Computing new state
2023-07-02 10:24:54,432 [classy] Setting parameters: {'Omega_m': 0.3168329439016637, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:54,479 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.7400401937837}
2023-07-02 10:24:54,479 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:54,481 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00134972
2023-07-02 10:24:54,481 [model] Computed derived parameters: {}
2023-07-02 10:24:54,481 [mcmc] New sample, #450:
Omega_m:0.2947379
2023-07-02 10:24:54,481 [model] Posterior to be computed for parameters {'Omega_m': 0.5641356858061696}
2023-07-02 10:24:54,481 [prior] Evaluating prior at array([0.56413569])
2023-07-02 10:24:54,481 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:54,481 [model] Got input parameters: {'Omega_m': 0.5641356858061696, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:54,481 [classy] Got parameters {'Omega_m': 0.5641356858061696, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:54,481 [classy] Computing new state
2023-07-02 10:24:54,481 [classy] Setting parameters: {'Omega_m': 0.5641356858061696, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:54,529 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 124.64177746891563}
2023-07-02 10:24:54,529 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:54,531 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.32727
2023-07-02 10:24:54,531 [model] Computed derived parameters: {}
2023-07-02 10:24:54,531 [model] Posterior to be computed for parameters {'Omega_m': 0.2165658239373025}
2023-07-02 10:24:54,531 [prior] Evaluating prior at array([0.21656582])
2023-07-02 10:24:54,531 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:54,531 [model] Got input parameters: {'Omega_m': 0.2165658239373025, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:54,531 [classy] Got parameters {'Omega_m': 0.2165658239373025, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:54,531 [classy] Computing new state
2023-07-02 10:24:54,531 [classy] Setting parameters: {'Omega_m': 0.2165658239373025, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:54,578 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 160.68317089454933}
2023-07-02 10:24:54,579 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:54,580 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.734956
2023-07-02 10:24:54,580 [model] Computed derived parameters: {}
2023-07-02 10:24:54,580 [model] Posterior to be computed for parameters {'Omega_m': 0.5191713834429545}
2023-07-02 10:24:54,581 [prior] Evaluating prior at array([0.51917138])
2023-07-02 10:24:54,581 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:54,581 [model] Got input parameters: {'Omega_m': 0.5191713834429545, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:54,581 [classy] Got parameters {'Omega_m': 0.5191713834429545, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:54,581 [classy] Computing new state
2023-07-02 10:24:54,581 [classy] Setting parameters: {'Omega_m': 0.5191713834429545, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:54,628 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 127.83733235059971}
2023-07-02 10:24:54,628 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:54,630 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.69775
2023-07-02 10:24:54,630 [model] Computed derived parameters: {}
2023-07-02 10:24:54,630 [mcmc] New sample, #451:
Omega_m:0.3168329
2023-07-02 10:24:54,630 [model] Posterior to be computed for parameters {'Omega_m': 0.48376521713630505}
2023-07-02 10:24:54,630 [prior] Evaluating prior at array([0.48376522])
2023-07-02 10:24:54,630 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:54,630 [model] Got input parameters: {'Omega_m': 0.48376521713630505, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:54,631 [classy] Got parameters {'Omega_m': 0.48376521713630505, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:54,631 [classy] Computing new state
2023-07-02 10:24:54,631 [classy] Setting parameters: {'Omega_m': 0.48376521713630505, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:54,679 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.55816270696}
2023-07-02 10:24:54,679 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:54,681 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.24423
2023-07-02 10:24:54,681 [model] Computed derived parameters: {}
2023-07-02 10:24:54,681 [mcmc] New sample, #452:
Omega_m:0.5191714
2023-07-02 10:24:54,681 [model] Posterior to be computed for parameters {'Omega_m': 0.8233428947211128}
2023-07-02 10:24:54,681 [prior] Evaluating prior at array([0.82334289])
2023-07-02 10:24:54,681 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:54,681 [model] Got input parameters: {'Omega_m': 0.8233428947211128, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:54,681 [classy] Got parameters {'Omega_m': 0.8233428947211128, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:54,681 [classy] Computing new state
2023-07-02 10:24:54,681 [classy] Setting parameters: {'Omega_m': 0.8233428947211128, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:54,727 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 110.27952478175851}
2023-07-02 10:24:54,727 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:54,729 [bao_likelihood.baolikelihood] Computed log-likelihood = -6.55261
2023-07-02 10:24:54,729 [model] Computed derived parameters: {}
2023-07-02 10:24:54,729 [model] Posterior to be computed for parameters {'Omega_m': 0.7153165323043591}
2023-07-02 10:24:54,729 [prior] Evaluating prior at array([0.71531653])
2023-07-02 10:24:54,729 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:54,729 [model] Got input parameters: {'Omega_m': 0.7153165323043591, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:54,729 [classy] Got parameters {'Omega_m': 0.7153165323043591, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:54,729 [classy] Computing new state
2023-07-02 10:24:54,729 [classy] Setting parameters: {'Omega_m': 0.7153165323043591, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:54,777 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 115.57316027019607}
2023-07-02 10:24:54,777 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:54,778 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.71643
2023-07-02 10:24:54,778 [model] Computed derived parameters: {}
2023-07-02 10:24:54,779 [model] Posterior to be computed for parameters {'Omega_m': 0.7668818066220325}
2023-07-02 10:24:54,779 [prior] Evaluating prior at array([0.76688181])
2023-07-02 10:24:54,779 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:54,779 [model] Got input parameters: {'Omega_m': 0.7668818066220325, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:54,779 [classy] Got parameters {'Omega_m': 0.7668818066220325, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:54,779 [classy] Computing new state
2023-07-02 10:24:54,779 [classy] Setting parameters: {'Omega_m': 0.7668818066220325, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:54,824 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 112.94412389301489}
2023-07-02 10:24:54,824 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:54,827 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.58569
2023-07-02 10:24:54,827 [model] Computed derived parameters: {}
2023-07-02 10:24:54,827 [model] Posterior to be computed for parameters {'Omega_m': 0.6351085290230681}
2023-07-02 10:24:54,827 [prior] Evaluating prior at array([0.63510853])
2023-07-02 10:24:54,827 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:54,827 [model] Got input parameters: {'Omega_m': 0.6351085290230681, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:54,827 [classy] Got parameters {'Omega_m': 0.6351085290230681, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:54,827 [classy] Computing new state
2023-07-02 10:24:54,827 [classy] Setting parameters: {'Omega_m': 0.6351085290230681, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:54,875 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 120.09955677665717}
2023-07-02 10:24:54,875 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:54,877 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.40919
2023-07-02 10:24:54,877 [model] Computed derived parameters: {}
2023-07-02 10:24:54,877 [model] Posterior to be computed for parameters {'Omega_m': 0.6580998273455653}
2023-07-02 10:24:54,877 [prior] Evaluating prior at array([0.65809983])
2023-07-02 10:24:54,877 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:54,877 [model] Got input parameters: {'Omega_m': 0.6580998273455653, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:54,878 [classy] Got parameters {'Omega_m': 0.6580998273455653, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:54,878 [classy] Computing new state
2023-07-02 10:24:54,878 [classy] Setting parameters: {'Omega_m': 0.6580998273455653, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:54,924 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 118.74213798958785}
2023-07-02 10:24:54,924 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:54,926 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.77665
2023-07-02 10:24:54,926 [model] Computed derived parameters: {}
2023-07-02 10:24:54,926 [model] Posterior to be computed for parameters {'Omega_m': 0.3848386847953992}
2023-07-02 10:24:54,927 [prior] Evaluating prior at array([0.38483868])
2023-07-02 10:24:54,927 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:54,927 [model] Got input parameters: {'Omega_m': 0.3848386847953992, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:54,927 [classy] Got parameters {'Omega_m': 0.3848386847953992, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:54,927 [classy] Computing new state
2023-07-02 10:24:54,927 [classy] Setting parameters: {'Omega_m': 0.3848386847953992, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:54,973 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 139.35205745348682}
2023-07-02 10:24:54,973 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:54,975 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.271424
2023-07-02 10:24:54,975 [model] Computed derived parameters: {}
2023-07-02 10:24:54,975 [mcmc] New sample, #453:
Omega_m:0.4837652
2023-07-02 10:24:54,975 [model] Posterior to be computed for parameters {'Omega_m': 0.2596717759058505}
2023-07-02 10:24:54,975 [prior] Evaluating prior at array([0.25967178])
2023-07-02 10:24:54,975 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:54,975 [model] Got input parameters: {'Omega_m': 0.2596717759058505, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:54,975 [classy] Got parameters {'Omega_m': 0.2596717759058505, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:54,975 [classy] Computing new state
2023-07-02 10:24:54,975 [classy] Setting parameters: {'Omega_m': 0.2596717759058505, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:55,023 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 154.1383923018722}
2023-07-02 10:24:55,023 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:55,025 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.19666
2023-07-02 10:24:55,025 [model] Computed derived parameters: {}
2023-07-02 10:24:55,025 [mcmc] New sample, #454:
Omega_m:0.3848387
2023-07-02 10:24:55,025 [model] Posterior to be computed for parameters {'Omega_m': 0.1198914501626149}
2023-07-02 10:24:55,025 [prior] Evaluating prior at array([0.11989145])
2023-07-02 10:24:55,025 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:55,026 [model] Got input parameters: {'Omega_m': 0.1198914501626149, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:55,026 [classy] Got parameters {'Omega_m': 0.1198914501626149, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:55,026 [classy] Computing new state
2023-07-02 10:24:55,026 [classy] Setting parameters: {'Omega_m': 0.1198914501626149, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:55,074 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 180.01014318615356}
2023-07-02 10:24:55,074 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:55,076 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.15726
2023-07-02 10:24:55,076 [model] Computed derived parameters: {}
2023-07-02 10:24:55,076 [mcmc] New sample, #455:
Omega_m:0.2596718
2023-07-02 10:24:55,076 [model] Posterior to be computed for parameters {'Omega_m': 0.31047758779691703}
2023-07-02 10:24:55,076 [prior] Evaluating prior at array([0.31047759])
2023-07-02 10:24:55,077 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:55,077 [model] Got input parameters: {'Omega_m': 0.31047758779691703, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:55,077 [classy] Got parameters {'Omega_m': 0.31047758779691703, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:55,077 [classy] Computing new state
2023-07-02 10:24:55,077 [classy] Setting parameters: {'Omega_m': 0.31047758779691703, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:55,125 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.5022462286668}
2023-07-02 10:24:55,126 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:55,128 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000450484
2023-07-02 10:24:55,128 [model] Computed derived parameters: {}
2023-07-02 10:24:55,128 [mcmc] New sample, #456:
Omega_m:0.1198915
2023-07-02 10:24:55,128 [model] Posterior to be computed for parameters {'Omega_m': 0.2918354009381155}
2023-07-02 10:24:55,128 [prior] Evaluating prior at array([0.2918354])
2023-07-02 10:24:55,129 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:55,129 [model] Got input parameters: {'Omega_m': 0.2918354009381155, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:55,129 [classy] Got parameters {'Omega_m': 0.2918354009381155, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:55,129 [classy] Computing new state
2023-07-02 10:24:55,129 [classy] Setting parameters: {'Omega_m': 0.2918354009381155, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:55,175 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.8201830093982}
2023-07-02 10:24:55,176 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:55,178 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0277547
2023-07-02 10:24:55,178 [model] Computed derived parameters: {}
2023-07-02 10:24:55,178 [mcmc] New sample, #457:
Omega_m:0.3104776
2023-07-02 10:24:55,178 [model] Posterior to be computed for parameters {'Omega_m': 0.6171402613140168}
2023-07-02 10:24:55,178 [prior] Evaluating prior at array([0.61714026])
2023-07-02 10:24:55,178 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:55,178 [model] Got input parameters: {'Omega_m': 0.6171402613140168, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:55,179 [classy] Got parameters {'Omega_m': 0.6171402613140168, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:55,179 [classy] Computing new state
2023-07-02 10:24:55,179 [classy] Setting parameters: {'Omega_m': 0.6171402613140168, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:55,227 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 121.19719842012466}
2023-07-02 10:24:55,227 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:55,229 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.1271
2023-07-02 10:24:55,229 [model] Computed derived parameters: {}
2023-07-02 10:24:55,230 [model] Posterior to be computed for parameters {'Omega_m': -0.05874593285529228}
2023-07-02 10:24:55,230 [prior] Evaluating prior at array([-0.05874593])
2023-07-02 10:24:55,230 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:55,230 [model] Posterior to be computed for parameters {'Omega_m': 0.13561171842788733}
2023-07-02 10:24:55,230 [prior] Evaluating prior at array([0.13561172])
2023-07-02 10:24:55,230 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:55,230 [model] Got input parameters: {'Omega_m': 0.13561171842788733, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:55,230 [classy] Got parameters {'Omega_m': 0.13561171842788733, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:55,230 [classy] Computing new state
2023-07-02 10:24:55,231 [classy] Setting parameters: {'Omega_m': 0.13561171842788733, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:55,278 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 176.28039883086342}
2023-07-02 10:24:55,278 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:55,280 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.29571
2023-07-02 10:24:55,281 [model] Computed derived parameters: {}
2023-07-02 10:24:55,281 [model] Posterior to be computed for parameters {'Omega_m': -0.050639235292443574}
2023-07-02 10:24:55,281 [prior] Evaluating prior at array([-0.05063924])
2023-07-02 10:24:55,281 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:55,281 [model] Posterior to be computed for parameters {'Omega_m': 1.2232412840423736}
2023-07-02 10:24:55,281 [prior] Evaluating prior at array([1.22324128])
2023-07-02 10:24:55,281 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:55,281 [model] Posterior to be computed for parameters {'Omega_m': 0.6018682596413101}
2023-07-02 10:24:55,281 [prior] Evaluating prior at array([0.60186826])
2023-07-02 10:24:55,281 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:55,281 [model] Got input parameters: {'Omega_m': 0.6018682596413101, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:55,281 [classy] Got parameters {'Omega_m': 0.6018682596413101, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:55,282 [classy] Computing new state
2023-07-02 10:24:55,282 [classy] Setting parameters: {'Omega_m': 0.6018682596413101, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:55,331 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 122.15693789085411}
2023-07-02 10:24:55,331 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:55,333 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.89134
2023-07-02 10:24:55,333 [model] Computed derived parameters: {}
2023-07-02 10:24:55,333 [model] Posterior to be computed for parameters {'Omega_m': 0.030149267931499135}
2023-07-02 10:24:55,333 [prior] Evaluating prior at array([0.03014927])
2023-07-02 10:24:55,333 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:55,333 [model] Posterior to be computed for parameters {'Omega_m': -0.040187964325526626}
2023-07-02 10:24:55,333 [prior] Evaluating prior at array([-0.04018796])
2023-07-02 10:24:55,333 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:55,333 [model] Posterior to be computed for parameters {'Omega_m': 0.5284874582816548}
2023-07-02 10:24:55,333 [prior] Evaluating prior at array([0.52848746])
2023-07-02 10:24:55,333 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:55,333 [model] Got input parameters: {'Omega_m': 0.5284874582816548, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:55,333 [classy] Got parameters {'Omega_m': 0.5284874582816548, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:55,334 [classy] Computing new state
2023-07-02 10:24:55,334 [classy] Setting parameters: {'Omega_m': 0.5284874582816548, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:55,388 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 127.15256699508025}
2023-07-02 10:24:55,388 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:55,390 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.82374
2023-07-02 10:24:55,390 [model] Computed derived parameters: {}
2023-07-02 10:24:55,390 [model] Posterior to be computed for parameters {'Omega_m': 0.40402916126575134}
2023-07-02 10:24:55,390 [prior] Evaluating prior at array([0.40402916])
2023-07-02 10:24:55,390 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:55,390 [model] Got input parameters: {'Omega_m': 0.40402916126575134, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:55,390 [classy] Got parameters {'Omega_m': 0.40402916126575134, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:55,390 [classy] Computing new state
2023-07-02 10:24:55,390 [classy] Setting parameters: {'Omega_m': 0.40402916126575134, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:55,440 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 137.48729700717303}
2023-07-02 10:24:55,440 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:55,442 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.416814
2023-07-02 10:24:55,442 [model] Computed derived parameters: {}
2023-07-02 10:24:55,442 [mcmc] New sample, #458:
Omega_m:0.2918354
2023-07-02 10:24:55,442 [model] Posterior to be computed for parameters {'Omega_m': -0.7836151030940739}
2023-07-02 10:24:55,442 [prior] Evaluating prior at array([-0.7836151])
2023-07-02 10:24:55,442 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:55,442 [model] Posterior to be computed for parameters {'Omega_m': 0.5372363393726617}
2023-07-02 10:24:55,442 [prior] Evaluating prior at array([0.53723634])
2023-07-02 10:24:55,442 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:55,442 [model] Got input parameters: {'Omega_m': 0.5372363393726617, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:55,442 [classy] Got parameters {'Omega_m': 0.5372363393726617, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:55,443 [classy] Computing new state
2023-07-02 10:24:55,443 [classy] Setting parameters: {'Omega_m': 0.5372363393726617, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:55,493 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 126.52064485926047}
2023-07-02 10:24:55,493 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:55,495 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.94427
2023-07-02 10:24:55,495 [model] Computed derived parameters: {}
2023-07-02 10:24:55,495 [model] Posterior to be computed for parameters {'Omega_m': 1.1821444200179239}
2023-07-02 10:24:55,495 [prior] Evaluating prior at array([1.18214442])
2023-07-02 10:24:55,495 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:55,495 [model] Posterior to be computed for parameters {'Omega_m': 0.5011826557401233}
2023-07-02 10:24:55,495 [prior] Evaluating prior at array([0.50118266])
2023-07-02 10:24:55,495 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:55,495 [model] Got input parameters: {'Omega_m': 0.5011826557401233, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:55,496 [classy] Got parameters {'Omega_m': 0.5011826557401233, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:55,496 [classy] Computing new state
2023-07-02 10:24:55,496 [classy] Setting parameters: {'Omega_m': 0.5011826557401233, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:55,546 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 129.19550834761623}
2023-07-02 10:24:55,546 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:55,547 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.46204
2023-07-02 10:24:55,548 [model] Computed derived parameters: {}
2023-07-02 10:24:55,548 [mcmc] New sample, #459:
Omega_m:0.4040292
2023-07-02 10:24:55,548 [model] Posterior to be computed for parameters {'Omega_m': 0.4658319347356983}
2023-07-02 10:24:55,548 [prior] Evaluating prior at array([0.46583193])
2023-07-02 10:24:55,548 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:55,548 [model] Got input parameters: {'Omega_m': 0.4658319347356983, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:55,548 [classy] Got parameters {'Omega_m': 0.4658319347356983, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:55,548 [classy] Computing new state
2023-07-02 10:24:55,548 [classy] Setting parameters: {'Omega_m': 0.4658319347356983, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:55,597 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 132.0133456158857}
2023-07-02 10:24:55,597 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:55,599 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.032
2023-07-02 10:24:55,599 [model] Computed derived parameters: {}
2023-07-02 10:24:55,599 [mcmc] New sample, #460:
Omega_m:0.5011827
2023-07-02 10:24:55,599 [model] Posterior to be computed for parameters {'Omega_m': 0.9738955805389513}
2023-07-02 10:24:55,599 [prior] Evaluating prior at array([0.97389558])
2023-07-02 10:24:55,600 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:55,600 [model] Got input parameters: {'Omega_m': 0.9738955805389513, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:55,600 [classy] Got parameters {'Omega_m': 0.9738955805389513, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:55,600 [classy] Computing new state
2023-07-02 10:24:55,600 [classy] Setting parameters: {'Omega_m': 0.9738955805389513, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:55,649 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 104.06892453909201}
2023-07-02 10:24:55,649 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:55,650 [bao_likelihood.baolikelihood] Computed log-likelihood = -9.15927
2023-07-02 10:24:55,651 [model] Computed derived parameters: {}
2023-07-02 10:24:55,651 [model] Posterior to be computed for parameters {'Omega_m': 0.48956667763627115}
2023-07-02 10:24:55,651 [prior] Evaluating prior at array([0.48956668])
2023-07-02 10:24:55,651 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:55,651 [model] Got input parameters: {'Omega_m': 0.48956667763627115, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:55,651 [classy] Got parameters {'Omega_m': 0.48956667763627115, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:55,651 [classy] Computing new state
2023-07-02 10:24:55,651 [classy] Setting parameters: {'Omega_m': 0.48956667763627115, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:55,700 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.0988874024501}
2023-07-02 10:24:55,700 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:55,702 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.31557
2023-07-02 10:24:55,702 [model] Computed derived parameters: {}
2023-07-02 10:24:55,702 [mcmc] New sample, #461:
Omega_m:0.4658319
2023-07-02 10:24:55,702 [model] Posterior to be computed for parameters {'Omega_m': 0.24240954412105067}
2023-07-02 10:24:55,702 [prior] Evaluating prior at array([0.24240954])
2023-07-02 10:24:55,703 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:55,703 [model] Got input parameters: {'Omega_m': 0.24240954412105067, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:55,703 [classy] Got parameters {'Omega_m': 0.24240954412105067, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:55,703 [classy] Computing new state
2023-07-02 10:24:55,703 [classy] Setting parameters: {'Omega_m': 0.24240954412105067, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:55,752 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 156.64489359796235}
2023-07-02 10:24:55,752 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:55,754 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.363376
2023-07-02 10:24:55,754 [model] Computed derived parameters: {}
2023-07-02 10:24:55,754 [mcmc] New sample, #462:
Omega_m:0.4895667
2023-07-02 10:24:55,754 [model] Posterior to be computed for parameters {'Omega_m': 0.00033519678364549166}
2023-07-02 10:24:55,754 [prior] Evaluating prior at array([0.0003352])
2023-07-02 10:24:55,754 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:55,754 [model] Posterior to be computed for parameters {'Omega_m': 0.8924294166640759}
2023-07-02 10:24:55,754 [prior] Evaluating prior at array([0.89242942])
2023-07-02 10:24:55,754 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:55,754 [model] Got input parameters: {'Omega_m': 0.8924294166640759, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:55,754 [classy] Got parameters {'Omega_m': 0.8924294166640759, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:55,754 [classy] Computing new state
2023-07-02 10:24:55,754 [classy] Setting parameters: {'Omega_m': 0.8924294166640759, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:55,803 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 107.28301668755911}
2023-07-02 10:24:55,803 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:55,805 [bao_likelihood.baolikelihood] Computed log-likelihood = -7.74704
2023-07-02 10:24:55,805 [model] Computed derived parameters: {}
2023-07-02 10:24:55,805 [model] Posterior to be computed for parameters {'Omega_m': 0.6100593221132335}
2023-07-02 10:24:55,805 [prior] Evaluating prior at array([0.61005932])
2023-07-02 10:24:55,805 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:55,805 [model] Got input parameters: {'Omega_m': 0.6100593221132335, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:55,805 [classy] Got parameters {'Omega_m': 0.6100593221132335, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:55,805 [classy] Computing new state
2023-07-02 10:24:55,805 [classy] Setting parameters: {'Omega_m': 0.6100593221132335, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:55,854 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 121.63904294709232}
2023-07-02 10:24:55,855 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:55,857 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.01731
2023-07-02 10:24:55,857 [model] Computed derived parameters: {}
2023-07-02 10:24:55,857 [mcmc] New sample, #463:
Omega_m:0.2424095
2023-07-02 10:24:55,857 [model] Posterior to be computed for parameters {'Omega_m': 0.39830429038834736}
2023-07-02 10:24:55,857 [prior] Evaluating prior at array([0.39830429])
2023-07-02 10:24:55,857 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:55,857 [model] Got input parameters: {'Omega_m': 0.39830429038834736, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:55,857 [classy] Got parameters {'Omega_m': 0.39830429038834736, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:55,857 [classy] Computing new state
2023-07-02 10:24:55,857 [classy] Setting parameters: {'Omega_m': 0.39830429038834736, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:55,906 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 138.0346365040614}
2023-07-02 10:24:55,906 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:55,908 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.370823
2023-07-02 10:24:55,908 [model] Computed derived parameters: {}
2023-07-02 10:24:55,908 [mcmc] New sample, #464:
Omega_m:0.6100593
2023-07-02 10:24:55,908 [model] Posterior to be computed for parameters {'Omega_m': 0.11964120511788973}
2023-07-02 10:24:55,908 [prior] Evaluating prior at array([0.11964121])
2023-07-02 10:24:55,908 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:55,908 [model] Got input parameters: {'Omega_m': 0.11964120511788973, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:55,908 [classy] Got parameters {'Omega_m': 0.11964120511788973, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:55,908 [classy] Computing new state
2023-07-02 10:24:55,908 [classy] Setting parameters: {'Omega_m': 0.11964120511788973, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:55,956 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 180.0718942490337}
2023-07-02 10:24:55,956 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:55,958 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.17229
2023-07-02 10:24:55,958 [model] Computed derived parameters: {}
2023-07-02 10:24:55,958 [model] Posterior to be computed for parameters {'Omega_m': 0.1764226137087952}
2023-07-02 10:24:55,958 [prior] Evaluating prior at array([0.17642261])
2023-07-02 10:24:55,958 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:55,958 [model] Got input parameters: {'Omega_m': 0.1764226137087952, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:55,958 [classy] Got parameters {'Omega_m': 0.1764226137087952, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:55,958 [classy] Computing new state
2023-07-02 10:24:55,958 [classy] Setting parameters: {'Omega_m': 0.1764226137087952, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:56,006 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 167.76908658113405}
2023-07-02 10:24:56,007 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:56,008 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.68311
2023-07-02 10:24:56,008 [model] Computed derived parameters: {}
2023-07-02 10:24:56,009 [mcmc] New sample, #465:
Omega_m:0.3983043
2023-07-02 10:24:56,009 [model] Posterior to be computed for parameters {'Omega_m': 0.149367286287286}
2023-07-02 10:24:56,009 [prior] Evaluating prior at array([0.14936729])
2023-07-02 10:24:56,009 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:56,009 [model] Got input parameters: {'Omega_m': 0.149367286287286, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:56,009 [classy] Got parameters {'Omega_m': 0.149367286287286, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:56,009 [classy] Computing new state
2023-07-02 10:24:56,009 [classy] Setting parameters: {'Omega_m': 0.149367286287286, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:56,058 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 173.23786911371818}
2023-07-02 10:24:56,059 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:56,060 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.6618
2023-07-02 10:24:56,060 [model] Computed derived parameters: {}
2023-07-02 10:24:56,060 [mcmc] New sample, #466:
Omega_m:0.1764226
2023-07-02 10:24:56,061 [model] Posterior to be computed for parameters {'Omega_m': -0.16895233755754288}
2023-07-02 10:24:56,061 [prior] Evaluating prior at array([-0.16895234])
2023-07-02 10:24:56,061 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:56,061 [model] Posterior to be computed for parameters {'Omega_m': 0.1934104067147679}
2023-07-02 10:24:56,061 [prior] Evaluating prior at array([0.19341041])
2023-07-02 10:24:56,061 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:56,061 [model] Got input parameters: {'Omega_m': 0.1934104067147679, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:56,061 [classy] Got parameters {'Omega_m': 0.1934104067147679, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:56,061 [classy] Computing new state
2023-07-02 10:24:56,061 [classy] Setting parameters: {'Omega_m': 0.1934104067147679, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:56,109 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 164.63606040667446}
2023-07-02 10:24:56,109 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:56,111 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.21833
2023-07-02 10:24:56,111 [model] Computed derived parameters: {}
2023-07-02 10:24:56,111 [mcmc] New sample, #467:
Omega_m:0.1493673
2023-07-02 10:24:56,111 [model] Posterior to be computed for parameters {'Omega_m': 0.08160074926509314}
2023-07-02 10:24:56,111 [prior] Evaluating prior at array([0.08160075])
2023-07-02 10:24:56,112 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:56,112 [model] Posterior to be computed for parameters {'Omega_m': -0.16623112981685167}
2023-07-02 10:24:56,112 [prior] Evaluating prior at array([-0.16623113])
2023-07-02 10:24:56,112 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:56,112 [model] Posterior to be computed for parameters {'Omega_m': -0.08822334226108064}
2023-07-02 10:24:56,112 [prior] Evaluating prior at array([-0.08822334])
2023-07-02 10:24:56,112 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:56,112 [model] Posterior to be computed for parameters {'Omega_m': 0.27196797214811486}
2023-07-02 10:24:56,112 [prior] Evaluating prior at array([0.27196797])
2023-07-02 10:24:56,112 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:56,112 [model] Got input parameters: {'Omega_m': 0.27196797214811486, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:56,112 [classy] Got parameters {'Omega_m': 0.27196797214811486, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:56,112 [classy] Computing new state
2023-07-02 10:24:56,112 [classy] Setting parameters: {'Omega_m': 0.27196797214811486, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:56,160 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.43643262126605}
2023-07-02 10:24:56,161 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:56,162 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.112002
2023-07-02 10:24:56,162 [model] Computed derived parameters: {}
2023-07-02 10:24:56,162 [mcmc] New sample, #468:
Omega_m:0.1934104
2023-07-02 10:24:56,163 [model] Posterior to be computed for parameters {'Omega_m': 0.23969080033112217}
2023-07-02 10:24:56,163 [prior] Evaluating prior at array([0.2396908])
2023-07-02 10:24:56,163 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:56,163 [model] Got input parameters: {'Omega_m': 0.23969080033112217, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:56,163 [classy] Got parameters {'Omega_m': 0.23969080033112217, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:56,163 [classy] Computing new state
2023-07-02 10:24:56,163 [classy] Setting parameters: {'Omega_m': 0.23969080033112217, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:56,213 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 157.05294502371925}
2023-07-02 10:24:56,213 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:56,215 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.395197
2023-07-02 10:24:56,215 [model] Computed derived parameters: {}
2023-07-02 10:24:56,215 [mcmc] New sample, #469:
Omega_m:0.271968
2023-07-02 10:24:56,215 [model] Posterior to be computed for parameters {'Omega_m': 0.20171543743059936}
2023-07-02 10:24:56,215 [prior] Evaluating prior at array([0.20171544])
2023-07-02 10:24:56,215 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:56,215 [model] Got input parameters: {'Omega_m': 0.20171543743059936, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:56,215 [classy] Got parameters {'Omega_m': 0.20171543743059936, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:56,215 [classy] Computing new state
2023-07-02 10:24:56,215 [classy] Setting parameters: {'Omega_m': 0.20171543743059936, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:56,266 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 163.17859970336679}
2023-07-02 10:24:56,266 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:56,268 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.02657
2023-07-02 10:24:56,268 [model] Computed derived parameters: {}
2023-07-02 10:24:56,268 [mcmc] New sample, #470:
Omega_m:0.2396908
2023-07-02 10:24:56,268 [model] Posterior to be computed for parameters {'Omega_m': 0.0033737735880343123}
2023-07-02 10:24:56,268 [prior] Evaluating prior at array([0.00337377])
2023-07-02 10:24:56,268 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:56,268 [model] Posterior to be computed for parameters {'Omega_m': 0.3658812234313563}
2023-07-02 10:24:56,268 [prior] Evaluating prior at array([0.36588122])
2023-07-02 10:24:56,269 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:56,269 [model] Got input parameters: {'Omega_m': 0.3658812234313563, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:56,269 [classy] Got parameters {'Omega_m': 0.3658812234313563, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:56,269 [classy] Computing new state
2023-07-02 10:24:56,269 [classy] Setting parameters: {'Omega_m': 0.3658812234313563, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:56,318 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.2822633703795}
2023-07-02 10:24:56,318 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:56,320 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.15427
2023-07-02 10:24:56,320 [model] Computed derived parameters: {}
2023-07-02 10:24:56,320 [mcmc] New sample, #471:
Omega_m:0.2017154
2023-07-02 10:24:56,320 [model] Posterior to be computed for parameters {'Omega_m': 0.4975570278610173}
2023-07-02 10:24:56,320 [prior] Evaluating prior at array([0.49755703])
2023-07-02 10:24:56,320 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:56,321 [model] Got input parameters: {'Omega_m': 0.4975570278610173, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:56,321 [classy] Got parameters {'Omega_m': 0.4975570278610173, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:56,321 [classy] Computing new state
2023-07-02 10:24:56,321 [classy] Setting parameters: {'Omega_m': 0.4975570278610173, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:56,371 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 129.47519381403762}
2023-07-02 10:24:56,371 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:56,373 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.41581
2023-07-02 10:24:56,373 [model] Computed derived parameters: {}
2023-07-02 10:24:56,373 [model] Posterior to be computed for parameters {'Omega_m': 0.36689318576364804}
2023-07-02 10:24:56,373 [prior] Evaluating prior at array([0.36689319])
2023-07-02 10:24:56,373 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:56,373 [model] Got input parameters: {'Omega_m': 0.36689318576364804, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:56,373 [classy] Got parameters {'Omega_m': 0.36689318576364804, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:56,373 [classy] Computing new state
2023-07-02 10:24:56,374 [classy] Setting parameters: {'Omega_m': 0.36689318576364804, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:56,420 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.1768942031325}
2023-07-02 10:24:56,420 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:56,422 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.1598
2023-07-02 10:24:56,422 [model] Computed derived parameters: {}
2023-07-02 10:24:56,423 [mcmc] New sample, #472:
Omega_m:0.3658812
2023-07-02 10:24:56,423 [model] Posterior to be computed for parameters {'Omega_m': 0.5532205457305936}
2023-07-02 10:24:56,423 [prior] Evaluating prior at array([0.55322055])
2023-07-02 10:24:56,423 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:56,423 [model] Got input parameters: {'Omega_m': 0.5532205457305936, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:56,423 [classy] Got parameters {'Omega_m': 0.5532205457305936, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:56,423 [classy] Computing new state
2023-07-02 10:24:56,423 [classy] Setting parameters: {'Omega_m': 0.5532205457305936, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:56,472 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 125.39283261886278}
2023-07-02 10:24:56,472 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:56,474 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.16973
2023-07-02 10:24:56,474 [model] Computed derived parameters: {}
2023-07-02 10:24:56,474 [model] Posterior to be computed for parameters {'Omega_m': 0.6258599191147033}
2023-07-02 10:24:56,474 [prior] Evaluating prior at array([0.62585992])
2023-07-02 10:24:56,474 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:56,474 [model] Got input parameters: {'Omega_m': 0.6258599191147033, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:56,474 [classy] Got parameters {'Omega_m': 0.6258599191147033, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:56,474 [classy] Computing new state
2023-07-02 10:24:56,474 [classy] Setting parameters: {'Omega_m': 0.6258599191147033, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:56,520 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 120.66035597168865}
2023-07-02 10:24:56,520 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:56,521 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.26341
2023-07-02 10:24:56,521 [model] Computed derived parameters: {}
2023-07-02 10:24:56,522 [model] Posterior to be computed for parameters {'Omega_m': 0.5883179222338727}
2023-07-02 10:24:56,522 [prior] Evaluating prior at array([0.58831792])
2023-07-02 10:24:56,522 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:56,522 [model] Got input parameters: {'Omega_m': 0.5883179222338727, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:56,522 [classy] Got parameters {'Omega_m': 0.5883179222338727, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:56,522 [classy] Computing new state
2023-07-02 10:24:56,522 [classy] Setting parameters: {'Omega_m': 0.5883179222338727, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:56,572 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 123.03011159903112}
2023-07-02 10:24:56,572 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:56,573 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.68555
2023-07-02 10:24:56,573 [model] Computed derived parameters: {}
2023-07-02 10:24:56,574 [model] Posterior to be computed for parameters {'Omega_m': 0.007121882756645437}
2023-07-02 10:24:56,574 [prior] Evaluating prior at array([0.00712188])
2023-07-02 10:24:56,574 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:56,574 [model] Posterior to be computed for parameters {'Omega_m': 0.3224310114139725}
2023-07-02 10:24:56,574 [prior] Evaluating prior at array([0.32243101])
2023-07-02 10:24:56,574 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:56,574 [model] Got input parameters: {'Omega_m': 0.3224310114139725, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:56,574 [classy] Got parameters {'Omega_m': 0.3224310114139725, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:56,574 [classy] Computing new state
2023-07-02 10:24:56,574 [classy] Setting parameters: {'Omega_m': 0.3224310114139725, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:56,620 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.079882795819}
2023-07-02 10:24:56,621 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:56,622 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00612228
2023-07-02 10:24:56,622 [model] Computed derived parameters: {}
2023-07-02 10:24:56,622 [mcmc] New sample, #473:
Omega_m:0.3668932
2023-07-02 10:24:56,622 [model] Posterior to be computed for parameters {'Omega_m': 0.33198566070181174}
2023-07-02 10:24:56,622 [prior] Evaluating prior at array([0.33198566])
2023-07-02 10:24:56,623 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:56,623 [model] Got input parameters: {'Omega_m': 0.33198566070181174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:56,623 [classy] Got parameters {'Omega_m': 0.33198566070181174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:56,623 [classy] Computing new state
2023-07-02 10:24:56,623 [classy] Setting parameters: {'Omega_m': 0.33198566070181174, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:56,673 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.97648727122817}
2023-07-02 10:24:56,673 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:56,674 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0224385
2023-07-02 10:24:56,675 [model] Computed derived parameters: {}
2023-07-02 10:24:56,675 [mcmc] New sample, #474:
Omega_m:0.322431
2023-07-02 10:24:56,675 [model] Posterior to be computed for parameters {'Omega_m': 0.60359376854119}
2023-07-02 10:24:56,675 [prior] Evaluating prior at array([0.60359377])
2023-07-02 10:24:56,675 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:56,675 [model] Got input parameters: {'Omega_m': 0.60359376854119, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:56,675 [classy] Got parameters {'Omega_m': 0.60359376854119, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:56,675 [classy] Computing new state
2023-07-02 10:24:56,675 [classy] Setting parameters: {'Omega_m': 0.60359376854119, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:56,726 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 122.04721871501327}
2023-07-02 10:24:56,726 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:56,729 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.91778
2023-07-02 10:24:56,729 [model] Computed derived parameters: {}
2023-07-02 10:24:56,729 [model] Posterior to be computed for parameters {'Omega_m': 0.15200950509395011}
2023-07-02 10:24:56,729 [prior] Evaluating prior at array([0.15200951])
2023-07-02 10:24:56,729 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:56,729 [model] Got input parameters: {'Omega_m': 0.15200950509395011, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:56,729 [classy] Got parameters {'Omega_m': 0.15200950509395011, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:56,729 [classy] Computing new state
2023-07-02 10:24:56,730 [classy] Setting parameters: {'Omega_m': 0.15200950509395011, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:56,777 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 172.67499855735954}
2023-07-02 10:24:56,778 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:56,780 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.55145
2023-07-02 10:24:56,780 [model] Computed derived parameters: {}
2023-07-02 10:24:56,780 [model] Posterior to be computed for parameters {'Omega_m': 0.26870541247070573}
2023-07-02 10:24:56,780 [prior] Evaluating prior at array([0.26870541])
2023-07-02 10:24:56,781 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:56,781 [model] Got input parameters: {'Omega_m': 0.26870541247070573, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:56,781 [classy] Got parameters {'Omega_m': 0.26870541247070573, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:56,781 [classy] Computing new state
2023-07-02 10:24:56,781 [classy] Setting parameters: {'Omega_m': 0.26870541247070573, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:56,829 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.88160714070378}
2023-07-02 10:24:56,829 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:56,831 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.131894
2023-07-02 10:24:56,831 [model] Computed derived parameters: {}
2023-07-02 10:24:56,832 [mcmc] New sample, #475:
Omega_m:0.3319857
2023-07-02 10:24:56,832 [model] Posterior to be computed for parameters {'Omega_m': 0.06187105319800107}
2023-07-02 10:24:56,832 [prior] Evaluating prior at array([0.06187105])
2023-07-02 10:24:56,832 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:56,832 [model] Posterior to be computed for parameters {'Omega_m': 0.7421253746372425}
2023-07-02 10:24:56,832 [prior] Evaluating prior at array([0.74212537])
2023-07-02 10:24:56,832 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:56,832 [model] Got input parameters: {'Omega_m': 0.7421253746372425, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:56,832 [classy] Got parameters {'Omega_m': 0.7421253746372425, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:56,832 [classy] Computing new state
2023-07-02 10:24:56,832 [classy] Setting parameters: {'Omega_m': 0.7421253746372425, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:56,879 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 114.18141965632469}
2023-07-02 10:24:56,879 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:56,882 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.16628
2023-07-02 10:24:56,882 [model] Computed derived parameters: {}
2023-07-02 10:24:56,882 [model] Posterior to be computed for parameters {'Omega_m': 0.3610544096983999}
2023-07-02 10:24:56,882 [prior] Evaluating prior at array([0.36105441])
2023-07-02 10:24:56,882 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:56,882 [model] Got input parameters: {'Omega_m': 0.3610544096983999, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:56,883 [classy] Got parameters {'Omega_m': 0.3610544096983999, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:56,883 [classy] Computing new state
2023-07-02 10:24:56,883 [classy] Setting parameters: {'Omega_m': 0.3610544096983999, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:56,931 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.78858586836583}
2023-07-02 10:24:56,931 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:56,934 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.12908
2023-07-02 10:24:56,934 [model] Computed derived parameters: {}
2023-07-02 10:24:56,934 [mcmc] New sample, #476:
Omega_m:0.2687054
2023-07-02 10:24:56,934 [model] Posterior to be computed for parameters {'Omega_m': 0.7661509377562101}
2023-07-02 10:24:56,934 [prior] Evaluating prior at array([0.76615094])
2023-07-02 10:24:56,934 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:56,935 [model] Got input parameters: {'Omega_m': 0.7661509377562101, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:56,935 [classy] Got parameters {'Omega_m': 0.7661509377562101, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:56,935 [classy] Computing new state
2023-07-02 10:24:56,935 [classy] Setting parameters: {'Omega_m': 0.7661509377562101, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:56,981 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 112.98002200321469}
2023-07-02 10:24:56,981 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:56,984 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.57326
2023-07-02 10:24:56,984 [model] Computed derived parameters: {}
2023-07-02 10:24:56,984 [model] Posterior to be computed for parameters {'Omega_m': 0.44701356579548246}
2023-07-02 10:24:56,984 [prior] Evaluating prior at array([0.44701357])
2023-07-02 10:24:56,984 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:56,984 [model] Got input parameters: {'Omega_m': 0.44701356579548246, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:56,984 [classy] Got parameters {'Omega_m': 0.44701356579548246, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:56,984 [classy] Computing new state
2023-07-02 10:24:56,985 [classy] Setting parameters: {'Omega_m': 0.44701356579548246, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:57,035 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 133.60119362147717}
2023-07-02 10:24:57,036 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:57,038 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.824061
2023-07-02 10:24:57,038 [model] Computed derived parameters: {}
2023-07-02 10:24:57,038 [mcmc] New sample, #477:
Omega_m:0.3610544
2023-07-02 10:24:57,038 [model] Posterior to be computed for parameters {'Omega_m': 0.19308934838203123}
2023-07-02 10:24:57,039 [prior] Evaluating prior at array([0.19308935])
2023-07-02 10:24:57,039 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:57,039 [model] Got input parameters: {'Omega_m': 0.19308934838203123, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:57,039 [classy] Got parameters {'Omega_m': 0.19308934838203123, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:57,039 [classy] Computing new state
2023-07-02 10:24:57,039 [classy] Setting parameters: {'Omega_m': 0.19308934838203123, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:57,087 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 164.69334557494722}
2023-07-02 10:24:57,087 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:57,089 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.22619
2023-07-02 10:24:57,089 [model] Computed derived parameters: {}
2023-07-02 10:24:57,089 [model] Posterior to be computed for parameters {'Omega_m': 0.3511332622061472}
2023-07-02 10:24:57,089 [prior] Evaluating prior at array([0.35113326])
2023-07-02 10:24:57,089 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:57,089 [model] Got input parameters: {'Omega_m': 0.3511332622061472, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:57,089 [classy] Got parameters {'Omega_m': 0.3511332622061472, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:57,089 [classy] Computing new state
2023-07-02 10:24:57,089 [classy] Setting parameters: {'Omega_m': 0.3511332622061472, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:57,138 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.84932109338956}
2023-07-02 10:24:57,138 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:57,140 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0836851
2023-07-02 10:24:57,140 [model] Computed derived parameters: {}
2023-07-02 10:24:57,140 [mcmc] New sample, #478:
Omega_m:0.4470136
2023-07-02 10:24:57,140 [model] Posterior to be computed for parameters {'Omega_m': 0.24449886285267897}
2023-07-02 10:24:57,140 [prior] Evaluating prior at array([0.24449886])
2023-07-02 10:24:57,140 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:57,140 [model] Got input parameters: {'Omega_m': 0.24449886285267897, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:57,140 [classy] Got parameters {'Omega_m': 0.24449886285267897, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:57,140 [classy] Computing new state
2023-07-02 10:24:57,140 [classy] Setting parameters: {'Omega_m': 0.24449886285267897, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:57,190 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 156.33383493088584}
2023-07-02 10:24:57,190 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:57,192 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.339993
2023-07-02 10:24:57,192 [model] Computed derived parameters: {}
2023-07-02 10:24:57,192 [mcmc] New sample, #479:
Omega_m:0.3511333
2023-07-02 10:24:57,192 [model] Posterior to be computed for parameters {'Omega_m': 0.4793283838172733}
2023-07-02 10:24:57,193 [prior] Evaluating prior at array([0.47932838])
2023-07-02 10:24:57,193 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:57,193 [model] Got input parameters: {'Omega_m': 0.4793283838172733, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:57,193 [classy] Got parameters {'Omega_m': 0.4793283838172733, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:57,193 [classy] Computing new state
2023-07-02 10:24:57,193 [classy] Setting parameters: {'Omega_m': 0.4793283838172733, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:57,242 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.9131198440028}
2023-07-02 10:24:57,242 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:57,244 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.19053
2023-07-02 10:24:57,244 [model] Computed derived parameters: {}
2023-07-02 10:24:57,244 [model] Posterior to be computed for parameters {'Omega_m': -0.22025253538277467}
2023-07-02 10:24:57,245 [prior] Evaluating prior at array([-0.22025254])
2023-07-02 10:24:57,245 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:57,245 [model] Posterior to be computed for parameters {'Omega_m': 0.002748045088537654}
2023-07-02 10:24:57,245 [prior] Evaluating prior at array([0.00274805])
2023-07-02 10:24:57,245 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:57,245 [model] Posterior to be computed for parameters {'Omega_m': 0.44862691641739383}
2023-07-02 10:24:57,245 [prior] Evaluating prior at array([0.44862692])
2023-07-02 10:24:57,245 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:57,245 [model] Got input parameters: {'Omega_m': 0.44862691641739383, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:57,245 [classy] Got parameters {'Omega_m': 0.44862691641739383, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:57,245 [classy] Computing new state
2023-07-02 10:24:57,245 [classy] Setting parameters: {'Omega_m': 0.44862691641739383, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:57,293 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 133.46251301094304}
2023-07-02 10:24:57,293 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:57,296 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.841248
2023-07-02 10:24:57,296 [model] Computed derived parameters: {}
2023-07-02 10:24:57,296 [model] Posterior to be computed for parameters {'Omega_m': 0.33966348090923326}
2023-07-02 10:24:57,296 [prior] Evaluating prior at array([0.33966348])
2023-07-02 10:24:57,296 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:57,297 [model] Got input parameters: {'Omega_m': 0.33966348090923326, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:57,297 [classy] Got parameters {'Omega_m': 0.33966348090923326, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:57,297 [classy] Computing new state
2023-07-02 10:24:57,297 [classy] Setting parameters: {'Omega_m': 0.33966348090923326, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:57,344 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.1104494268838}
2023-07-02 10:24:57,344 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:57,347 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0426108
2023-07-02 10:24:57,347 [model] Computed derived parameters: {}
2023-07-02 10:24:57,347 [mcmc] New sample, #480:
Omega_m:0.2444989
2023-07-02 10:24:57,347 [mcmc] Learn + convergence test @ 480 samples accepted.
2023-07-02 10:24:57,347 [mcmc] Ready to check convergence and learn a new proposal covmat
2023-07-02 10:24:57,353 [mcmc] - Acceptance rate: 0.416
2023-07-02 10:24:57,354 [mcmc] - Condition number = 1
2023-07-02 10:24:57,354 [mcmc] - Eigenvalues = array([0.0089159])
2023-07-02 10:24:57,354 [mcmc] - Convergence of means: R-1 = 0.008916 after 384 accepted steps
2023-07-02 10:24:57,354 [mcmc] - Updated covariance matrix of proposal pdf.
2023-07-02 10:24:57,354 [mcmc] array([[0.01221298]])
2023-07-02 10:24:57,364 [mcmc] Dumped checkpoint and progress info, and current covmat.
2023-07-02 10:24:57,364 [model] Posterior to be computed for parameters {'Omega_m': 0.6867707876486637}
2023-07-02 10:24:57,364 [prior] Evaluating prior at array([0.68677079])
2023-07-02 10:24:57,365 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:57,365 [model] Got input parameters: {'Omega_m': 0.6867707876486637, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:57,365 [classy] Got parameters {'Omega_m': 0.6867707876486637, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:57,365 [classy] Computing new state
2023-07-02 10:24:57,365 [classy] Setting parameters: {'Omega_m': 0.6867707876486637, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:57,415 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 117.11863918175084}
2023-07-02 10:24:57,415 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:57,417 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.24362
2023-07-02 10:24:57,417 [model] Computed derived parameters: {}
2023-07-02 10:24:57,417 [model] Posterior to be computed for parameters {'Omega_m': 0.27133818609766547}
2023-07-02 10:24:57,417 [prior] Evaluating prior at array([0.27133819])
2023-07-02 10:24:57,417 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:57,417 [model] Got input parameters: {'Omega_m': 0.27133818609766547, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:57,417 [classy] Got parameters {'Omega_m': 0.27133818609766547, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:57,417 [classy] Computing new state
2023-07-02 10:24:57,417 [classy] Setting parameters: {'Omega_m': 0.27133818609766547, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:57,468 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.5220130664281}
2023-07-02 10:24:57,468 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:57,470 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.115702
2023-07-02 10:24:57,470 [model] Computed derived parameters: {}
2023-07-02 10:24:57,470 [mcmc] New sample, #481:
Omega_m:0.3396635
2023-07-02 10:24:57,470 [model] Posterior to be computed for parameters {'Omega_m': -0.159431386035431}
2023-07-02 10:24:57,470 [prior] Evaluating prior at array([-0.15943139])
2023-07-02 10:24:57,470 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:57,471 [model] Posterior to be computed for parameters {'Omega_m': 0.22743338916384875}
2023-07-02 10:24:57,471 [prior] Evaluating prior at array([0.22743339])
2023-07-02 10:24:57,471 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:57,471 [model] Got input parameters: {'Omega_m': 0.22743338916384875, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:57,471 [classy] Got parameters {'Omega_m': 0.22743338916384875, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:57,471 [classy] Computing new state
2023-07-02 10:24:57,471 [classy] Setting parameters: {'Omega_m': 0.22743338916384875, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:57,523 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 158.9404831028675}
2023-07-02 10:24:57,523 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:57,525 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.559219
2023-07-02 10:24:57,525 [model] Computed derived parameters: {}
2023-07-02 10:24:57,525 [mcmc] New sample, #482:
Omega_m:0.2713382
2023-07-02 10:24:57,526 [model] Posterior to be computed for parameters {'Omega_m': 0.22064955407671344}
2023-07-02 10:24:57,526 [prior] Evaluating prior at array([0.22064955])
2023-07-02 10:24:57,526 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:57,526 [model] Got input parameters: {'Omega_m': 0.22064955407671344, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:57,526 [classy] Got parameters {'Omega_m': 0.22064955407671344, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:57,526 [classy] Computing new state
2023-07-02 10:24:57,526 [classy] Setting parameters: {'Omega_m': 0.22064955407671344, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:57,579 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 160.02034720876546}
2023-07-02 10:24:57,579 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:57,580 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.665384
2023-07-02 10:24:57,581 [model] Computed derived parameters: {}
2023-07-02 10:24:57,581 [mcmc] New sample, #483:
Omega_m:0.2274334
2023-07-02 10:24:57,581 [model] Posterior to be computed for parameters {'Omega_m': -0.26316354009123577}
2023-07-02 10:24:57,581 [prior] Evaluating prior at array([-0.26316354])
2023-07-02 10:24:57,581 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:57,581 [model] Posterior to be computed for parameters {'Omega_m': 0.8440387668413107}
2023-07-02 10:24:57,581 [prior] Evaluating prior at array([0.84403877])
2023-07-02 10:24:57,581 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:57,581 [model] Got input parameters: {'Omega_m': 0.8440387668413107, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:57,581 [classy] Got parameters {'Omega_m': 0.8440387668413107, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:57,581 [classy] Computing new state
2023-07-02 10:24:57,581 [classy] Setting parameters: {'Omega_m': 0.8440387668413107, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:57,632 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 109.3532128671015}
2023-07-02 10:24:57,632 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:57,634 [bao_likelihood.baolikelihood] Computed log-likelihood = -6.90956
2023-07-02 10:24:57,634 [model] Computed derived parameters: {}
2023-07-02 10:24:57,634 [model] Posterior to be computed for parameters {'Omega_m': 0.4023210000821952}
2023-07-02 10:24:57,634 [prior] Evaluating prior at array([0.402321])
2023-07-02 10:24:57,634 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:57,634 [model] Got input parameters: {'Omega_m': 0.4023210000821952, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:57,634 [classy] Got parameters {'Omega_m': 0.4023210000821952, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:57,634 [classy] Computing new state
2023-07-02 10:24:57,634 [classy] Setting parameters: {'Omega_m': 0.4023210000821952, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:57,685 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 137.6498341368594}
2023-07-02 10:24:57,685 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:57,687 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.402867
2023-07-02 10:24:57,687 [model] Computed derived parameters: {}
2023-07-02 10:24:57,687 [mcmc] New sample, #484:
Omega_m:0.2206496
2023-07-02 10:24:57,687 [model] Posterior to be computed for parameters {'Omega_m': 0.20792652340549492}
2023-07-02 10:24:57,687 [prior] Evaluating prior at array([0.20792652])
2023-07-02 10:24:57,687 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:57,687 [model] Got input parameters: {'Omega_m': 0.20792652340549492, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:57,687 [classy] Got parameters {'Omega_m': 0.20792652340549492, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:57,687 [classy] Computing new state
2023-07-02 10:24:57,687 [classy] Setting parameters: {'Omega_m': 0.20792652340549492, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:57,739 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 162.11814671477725}
2023-07-02 10:24:57,740 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:57,742 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.89694
2023-07-02 10:24:57,742 [model] Computed derived parameters: {}
2023-07-02 10:24:57,742 [model] Posterior to be computed for parameters {'Omega_m': 0.040691792035609575}
2023-07-02 10:24:57,742 [prior] Evaluating prior at array([0.04069179])
2023-07-02 10:24:57,743 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:57,743 [model] Posterior to be computed for parameters {'Omega_m': 0.7369371268068596}
2023-07-02 10:24:57,743 [prior] Evaluating prior at array([0.73693713])
2023-07-02 10:24:57,743 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:57,743 [model] Got input parameters: {'Omega_m': 0.7369371268068596, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:57,743 [classy] Got parameters {'Omega_m': 0.7369371268068596, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:57,743 [classy] Computing new state
2023-07-02 10:24:57,743 [classy] Setting parameters: {'Omega_m': 0.7369371268068596, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:57,792 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 114.44644197599506}
2023-07-02 10:24:57,792 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:57,795 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.07883
2023-07-02 10:24:57,795 [model] Computed derived parameters: {}
2023-07-02 10:24:57,795 [model] Posterior to be computed for parameters {'Omega_m': 0.21746467085280555}
2023-07-02 10:24:57,795 [prior] Evaluating prior at array([0.21746467])
2023-07-02 10:24:57,795 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:57,795 [model] Got input parameters: {'Omega_m': 0.21746467085280555, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:57,795 [classy] Got parameters {'Omega_m': 0.21746467085280555, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:57,795 [classy] Computing new state
2023-07-02 10:24:57,795 [classy] Setting parameters: {'Omega_m': 0.21746467085280555, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:57,845 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 160.5364444131339}
2023-07-02 10:24:57,845 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:57,848 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.719268
2023-07-02 10:24:57,848 [model] Computed derived parameters: {}
2023-07-02 10:24:57,848 [model] Posterior to be computed for parameters {'Omega_m': 0.49272648164610805}
2023-07-02 10:24:57,848 [prior] Evaluating prior at array([0.49272648])
2023-07-02 10:24:57,848 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:57,848 [model] Got input parameters: {'Omega_m': 0.49272648164610805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:57,848 [classy] Got parameters {'Omega_m': 0.49272648164610805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:57,848 [classy] Computing new state
2023-07-02 10:24:57,848 [classy] Setting parameters: {'Omega_m': 0.49272648164610805, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:57,897 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 129.85101765769232}
2023-07-02 10:24:57,897 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:57,900 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.35495
2023-07-02 10:24:57,900 [model] Computed derived parameters: {}
2023-07-02 10:24:57,900 [model] Posterior to be computed for parameters {'Omega_m': 0.2666145038243846}
2023-07-02 10:24:57,900 [prior] Evaluating prior at array([0.2666145])
2023-07-02 10:24:57,900 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:57,900 [model] Got input parameters: {'Omega_m': 0.2666145038243846, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:57,900 [classy] Got parameters {'Omega_m': 0.2666145038243846, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:57,900 [classy] Computing new state
2023-07-02 10:24:57,900 [classy] Setting parameters: {'Omega_m': 0.2666145038243846, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:57,948 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.16931507937986}
2023-07-02 10:24:57,948 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:57,951 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.1456
2023-07-02 10:24:57,951 [model] Computed derived parameters: {}
2023-07-02 10:24:57,951 [mcmc] New sample, #485:
Omega_m:0.402321
2023-07-02 10:24:57,951 [model] Posterior to be computed for parameters {'Omega_m': 0.20703986222239235}
2023-07-02 10:24:57,951 [prior] Evaluating prior at array([0.20703986])
2023-07-02 10:24:57,951 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:57,951 [model] Got input parameters: {'Omega_m': 0.20703986222239235, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:57,951 [classy] Got parameters {'Omega_m': 0.20703986222239235, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:57,951 [classy] Computing new state
2023-07-02 10:24:57,952 [classy] Setting parameters: {'Omega_m': 0.20703986222239235, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:57,998 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 162.26803287057638}
2023-07-02 10:24:57,998 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:58,000 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.914754
2023-07-02 10:24:58,001 [model] Computed derived parameters: {}
2023-07-02 10:24:58,001 [model] Posterior to be computed for parameters {'Omega_m': 0.05911522687824197}
2023-07-02 10:24:58,001 [prior] Evaluating prior at array([0.05911523])
2023-07-02 10:24:58,001 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:58,001 [model] Posterior to be computed for parameters {'Omega_m': 0.3295998026546274}
2023-07-02 10:24:58,001 [prior] Evaluating prior at array([0.3295998])
2023-07-02 10:24:58,001 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:58,001 [model] Got input parameters: {'Omega_m': 0.3295998026546274, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:58,001 [classy] Got parameters {'Omega_m': 0.3295998026546274, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:58,001 [classy] Computing new state
2023-07-02 10:24:58,001 [classy] Setting parameters: {'Omega_m': 0.3295998026546274, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:58,048 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.2492868779145}
2023-07-02 10:24:58,048 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:58,050 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0174297
2023-07-02 10:24:58,050 [model] Computed derived parameters: {}
2023-07-02 10:24:58,050 [mcmc] New sample, #486:
Omega_m:0.2666145
2023-07-02 10:24:58,050 [model] Posterior to be computed for parameters {'Omega_m': 0.303580996064218}
2023-07-02 10:24:58,050 [prior] Evaluating prior at array([0.303581])
2023-07-02 10:24:58,050 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:58,050 [model] Got input parameters: {'Omega_m': 0.303580996064218, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:58,050 [classy] Got parameters {'Omega_m': 0.303580996064218, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:58,050 [classy] Computing new state
2023-07-02 10:24:58,050 [classy] Setting parameters: {'Omega_m': 0.303580996064218, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:58,096 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.34513852837438}
2023-07-02 10:24:58,096 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:58,098 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00517269
2023-07-02 10:24:58,098 [model] Computed derived parameters: {}
2023-07-02 10:24:58,098 [mcmc] New sample, #487:
Omega_m:0.3295998
2023-07-02 10:24:58,099 [model] Posterior to be computed for parameters {'Omega_m': 0.15086905549703236}
2023-07-02 10:24:58,099 [prior] Evaluating prior at array([0.15086906])
2023-07-02 10:24:58,099 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:58,099 [model] Got input parameters: {'Omega_m': 0.15086905549703236, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:58,099 [classy] Got parameters {'Omega_m': 0.15086905549703236, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:58,099 [classy] Computing new state
2023-07-02 10:24:58,099 [classy] Setting parameters: {'Omega_m': 0.15086905549703236, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:58,145 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 172.91711586445405}
2023-07-02 10:24:58,145 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:58,147 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.59865
2023-07-02 10:24:58,147 [model] Computed derived parameters: {}
2023-07-02 10:24:58,147 [model] Posterior to be computed for parameters {'Omega_m': 0.13199600682645402}
2023-07-02 10:24:58,148 [prior] Evaluating prior at array([0.13199601])
2023-07-02 10:24:58,148 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:58,148 [model] Got input parameters: {'Omega_m': 0.13199600682645402, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:58,148 [classy] Got parameters {'Omega_m': 0.13199600682645402, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:58,148 [classy] Computing new state
2023-07-02 10:24:58,148 [classy] Setting parameters: {'Omega_m': 0.13199600682645402, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:58,194 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 177.11315902598756}
2023-07-02 10:24:58,194 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:58,196 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.48009
2023-07-02 10:24:58,196 [model] Computed derived parameters: {}
2023-07-02 10:24:58,197 [model] Posterior to be computed for parameters {'Omega_m': 1.2427119618064963}
2023-07-02 10:24:58,197 [prior] Evaluating prior at array([1.24271196])
2023-07-02 10:24:58,197 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:58,197 [model] Posterior to be computed for parameters {'Omega_m': 0.4472987085514163}
2023-07-02 10:24:58,197 [prior] Evaluating prior at array([0.44729871])
2023-07-02 10:24:58,197 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:58,197 [model] Got input parameters: {'Omega_m': 0.4472987085514163, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:58,197 [classy] Got parameters {'Omega_m': 0.4472987085514163, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:58,197 [classy] Computing new state
2023-07-02 10:24:58,197 [classy] Setting parameters: {'Omega_m': 0.4472987085514163, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:58,245 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 133.57664917591535}
2023-07-02 10:24:58,245 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:58,246 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.827089
2023-07-02 10:24:58,247 [model] Computed derived parameters: {}
2023-07-02 10:24:58,247 [model] Posterior to be computed for parameters {'Omega_m': 0.44303977630074587}
2023-07-02 10:24:58,247 [prior] Evaluating prior at array([0.44303978])
2023-07-02 10:24:58,247 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:58,247 [model] Got input parameters: {'Omega_m': 0.44303977630074587, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:58,247 [classy] Got parameters {'Omega_m': 0.44303977630074587, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:58,247 [classy] Computing new state
2023-07-02 10:24:58,247 [classy] Setting parameters: {'Omega_m': 0.44303977630074587, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:58,294 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 133.9448687905368}
2023-07-02 10:24:58,294 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:58,296 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.782266
2023-07-02 10:24:58,296 [model] Computed derived parameters: {}
2023-07-02 10:24:58,296 [model] Posterior to be computed for parameters {'Omega_m': 0.6098798011584754}
2023-07-02 10:24:58,296 [prior] Evaluating prior at array([0.6098798])
2023-07-02 10:24:58,296 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:58,296 [model] Got input parameters: {'Omega_m': 0.6098798011584754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:58,296 [classy] Got parameters {'Omega_m': 0.6098798011584754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:58,296 [classy] Computing new state
2023-07-02 10:24:58,296 [classy] Setting parameters: {'Omega_m': 0.6098798011584754, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:58,344 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 121.65031555086593}
2023-07-02 10:24:58,344 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:58,345 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.01453
2023-07-02 10:24:58,345 [model] Computed derived parameters: {}
2023-07-02 10:24:58,346 [model] Posterior to be computed for parameters {'Omega_m': 0.39509618281919673}
2023-07-02 10:24:58,346 [prior] Evaluating prior at array([0.39509618])
2023-07-02 10:24:58,346 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:58,346 [model] Got input parameters: {'Omega_m': 0.39509618281919673, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:58,346 [classy] Got parameters {'Omega_m': 0.39509618281919673, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:58,346 [classy] Computing new state
2023-07-02 10:24:58,346 [classy] Setting parameters: {'Omega_m': 0.39509618281919673, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:58,402 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 138.34462348825278}
2023-07-02 10:24:58,402 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:58,404 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.346003
2023-07-02 10:24:58,404 [model] Computed derived parameters: {}
2023-07-02 10:24:58,404 [mcmc] New sample, #488:
Omega_m:0.303581
2023-07-02 10:24:58,404 [model] Posterior to be computed for parameters {'Omega_m': 0.3420387079439696}
2023-07-02 10:24:58,404 [prior] Evaluating prior at array([0.34203871])
2023-07-02 10:24:58,404 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:58,404 [model] Got input parameters: {'Omega_m': 0.3420387079439696, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:58,404 [classy] Got parameters {'Omega_m': 0.3420387079439696, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:58,405 [classy] Computing new state
2023-07-02 10:24:58,405 [classy] Setting parameters: {'Omega_m': 0.3420387079439696, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:58,453 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.84611518584913}
2023-07-02 10:24:58,453 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:58,455 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0500675
2023-07-02 10:24:58,456 [model] Computed derived parameters: {}
2023-07-02 10:24:58,456 [mcmc] New sample, #489:
Omega_m:0.3950962
2023-07-02 10:24:58,456 [model] Posterior to be computed for parameters {'Omega_m': 0.006289722193287661}
2023-07-02 10:24:58,456 [prior] Evaluating prior at array([0.00628972])
2023-07-02 10:24:58,456 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:58,456 [model] Posterior to be computed for parameters {'Omega_m': 0.3204165760127692}
2023-07-02 10:24:58,456 [prior] Evaluating prior at array([0.32041658])
2023-07-02 10:24:58,456 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:58,456 [model] Got input parameters: {'Omega_m': 0.3204165760127692, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:58,456 [classy] Got parameters {'Omega_m': 0.3204165760127692, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:58,456 [classy] Computing new state
2023-07-02 10:24:58,457 [classy] Setting parameters: {'Omega_m': 0.3204165760127692, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:58,506 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.3162532928452}
2023-07-02 10:24:58,507 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:58,509 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00398586
2023-07-02 10:24:58,509 [model] Computed derived parameters: {}
2023-07-02 10:24:58,509 [mcmc] New sample, #490:
Omega_m:0.3420387
2023-07-02 10:24:58,509 [model] Posterior to be computed for parameters {'Omega_m': 0.2316909815566665}
2023-07-02 10:24:58,509 [prior] Evaluating prior at array([0.23169098])
2023-07-02 10:24:58,510 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:58,510 [model] Got input parameters: {'Omega_m': 0.2316909815566665, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:58,510 [classy] Got parameters {'Omega_m': 0.2316909815566665, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:58,510 [classy] Computing new state
2023-07-02 10:24:58,510 [classy] Setting parameters: {'Omega_m': 0.2316909815566665, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:58,561 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 158.2757439229257}
2023-07-02 10:24:58,561 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:58,563 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.49831
2023-07-02 10:24:58,563 [model] Computed derived parameters: {}
2023-07-02 10:24:58,563 [model] Posterior to be computed for parameters {'Omega_m': 0.4527346598486598}
2023-07-02 10:24:58,564 [prior] Evaluating prior at array([0.45273466])
2023-07-02 10:24:58,564 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:58,564 [model] Got input parameters: {'Omega_m': 0.4527346598486598, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:58,564 [classy] Got parameters {'Omega_m': 0.4527346598486598, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:58,564 [classy] Computing new state
2023-07-02 10:24:58,564 [classy] Setting parameters: {'Omega_m': 0.4527346598486598, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:58,613 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 133.11160756671094}
2023-07-02 10:24:58,614 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:58,616 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.885568
2023-07-02 10:24:58,616 [model] Computed derived parameters: {}
2023-07-02 10:24:58,616 [mcmc] New sample, #491:
Omega_m:0.3204166
2023-07-02 10:24:58,616 [model] Posterior to be computed for parameters {'Omega_m': 0.3149699203730418}
2023-07-02 10:24:58,616 [prior] Evaluating prior at array([0.31496992])
2023-07-02 10:24:58,617 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:58,617 [model] Got input parameters: {'Omega_m': 0.3149699203730418, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:58,617 [classy] Got parameters {'Omega_m': 0.3149699203730418, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:58,617 [classy] Computing new state
2023-07-02 10:24:58,617 [classy] Setting parameters: {'Omega_m': 0.3149699203730418, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:58,667 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.9620381223081}
2023-07-02 10:24:58,668 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:58,669 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000579119
2023-07-02 10:24:58,669 [model] Computed derived parameters: {}
2023-07-02 10:24:58,669 [mcmc] New sample, #492:
Omega_m:0.4527347
2023-07-02 10:24:58,670 [model] Posterior to be computed for parameters {'Omega_m': 0.000218796065928617}
2023-07-02 10:24:58,670 [prior] Evaluating prior at array([0.0002188])
2023-07-02 10:24:58,670 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:58,670 [model] Posterior to be computed for parameters {'Omega_m': 0.44650368618027025}
2023-07-02 10:24:58,670 [prior] Evaluating prior at array([0.44650369])
2023-07-02 10:24:58,670 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:58,670 [model] Got input parameters: {'Omega_m': 0.44650368618027025, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:58,670 [classy] Got parameters {'Omega_m': 0.44650368618027025, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:58,670 [classy] Computing new state
2023-07-02 10:24:58,670 [classy] Setting parameters: {'Omega_m': 0.44650368618027025, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:58,720 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 133.64512504730916}
2023-07-02 10:24:58,720 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:58,722 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.818655
2023-07-02 10:24:58,722 [model] Computed derived parameters: {}
2023-07-02 10:24:58,722 [mcmc] New sample, #493:
Omega_m:0.3149699
2023-07-02 10:24:58,723 [model] Posterior to be computed for parameters {'Omega_m': 0.19100925321391593}
2023-07-02 10:24:58,723 [prior] Evaluating prior at array([0.19100925])
2023-07-02 10:24:58,723 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:58,723 [model] Got input parameters: {'Omega_m': 0.19100925321391593, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:58,723 [classy] Got parameters {'Omega_m': 0.19100925321391593, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:58,723 [classy] Computing new state
2023-07-02 10:24:58,723 [classy] Setting parameters: {'Omega_m': 0.19100925321391593, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:58,775 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 165.06622766378237}
2023-07-02 10:24:58,775 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:58,778 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.27792
2023-07-02 10:24:58,778 [model] Computed derived parameters: {}
2023-07-02 10:24:58,778 [model] Posterior to be computed for parameters {'Omega_m': 0.4504220668826536}
2023-07-02 10:24:58,778 [prior] Evaluating prior at array([0.45042207])
2023-07-02 10:24:58,779 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:58,779 [model] Got input parameters: {'Omega_m': 0.4504220668826536, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:58,779 [classy] Got parameters {'Omega_m': 0.4504220668826536, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:58,779 [classy] Computing new state
2023-07-02 10:24:58,779 [classy] Setting parameters: {'Omega_m': 0.4504220668826536, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:58,833 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 133.30877578204175}
2023-07-02 10:24:58,833 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:58,835 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.860519
2023-07-02 10:24:58,835 [model] Computed derived parameters: {}
2023-07-02 10:24:58,835 [mcmc] New sample, #494:
Omega_m:0.4465037
2023-07-02 10:24:58,835 [model] Posterior to be computed for parameters {'Omega_m': 0.38098561200603404}
2023-07-02 10:24:58,835 [prior] Evaluating prior at array([0.38098561])
2023-07-02 10:24:58,836 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:58,836 [model] Got input parameters: {'Omega_m': 0.38098561200603404, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:58,836 [classy] Got parameters {'Omega_m': 0.38098561200603404, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:58,836 [classy] Computing new state
2023-07-02 10:24:58,836 [classy] Setting parameters: {'Omega_m': 0.38098561200603404, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:58,888 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 139.73704023110884}
2023-07-02 10:24:58,888 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:58,890 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.245369
2023-07-02 10:24:58,890 [model] Computed derived parameters: {}
2023-07-02 10:24:58,890 [mcmc] New sample, #495:
Omega_m:0.4504221
2023-07-02 10:24:58,890 [model] Posterior to be computed for parameters {'Omega_m': 0.027363947613091133}
2023-07-02 10:24:58,890 [prior] Evaluating prior at array([0.02736395])
2023-07-02 10:24:58,890 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:58,890 [model] Posterior to be computed for parameters {'Omega_m': 0.2684475781084633}
2023-07-02 10:24:58,890 [prior] Evaluating prior at array([0.26844758])
2023-07-02 10:24:58,890 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:58,890 [model] Got input parameters: {'Omega_m': 0.2684475781084633, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:58,890 [classy] Got parameters {'Omega_m': 0.2684475781084633, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:58,890 [classy] Computing new state
2023-07-02 10:24:58,890 [classy] Setting parameters: {'Omega_m': 0.2684475781084633, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:58,941 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.91698180883932}
2023-07-02 10:24:58,941 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:58,942 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.133543
2023-07-02 10:24:58,943 [model] Computed derived parameters: {}
2023-07-02 10:24:58,943 [mcmc] New sample, #496:
Omega_m:0.3809856
2023-07-02 10:24:58,943 [model] Posterior to be computed for parameters {'Omega_m': 0.6460008213503673}
2023-07-02 10:24:58,943 [prior] Evaluating prior at array([0.64600082])
2023-07-02 10:24:58,943 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:58,943 [model] Got input parameters: {'Omega_m': 0.6460008213503673, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:58,943 [classy] Got parameters {'Omega_m': 0.6460008213503673, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:58,943 [classy] Computing new state
2023-07-02 10:24:58,943 [classy] Setting parameters: {'Omega_m': 0.6460008213503673, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:58,993 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 119.45004915319981}
2023-07-02 10:24:58,993 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:58,995 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.58244
2023-07-02 10:24:58,995 [model] Computed derived parameters: {}
2023-07-02 10:24:58,995 [model] Posterior to be computed for parameters {'Omega_m': 0.18194352835918481}
2023-07-02 10:24:58,995 [prior] Evaluating prior at array([0.18194353])
2023-07-02 10:24:58,995 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:58,995 [model] Got input parameters: {'Omega_m': 0.18194352835918481, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:58,995 [classy] Got parameters {'Omega_m': 0.18194352835918481, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:58,995 [classy] Computing new state
2023-07-02 10:24:58,995 [classy] Setting parameters: {'Omega_m': 0.18194352835918481, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:59,046 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 166.72743963252006}
2023-07-02 10:24:59,046 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:59,048 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.5207
2023-07-02 10:24:59,048 [model] Computed derived parameters: {}
2023-07-02 10:24:59,048 [model] Posterior to be computed for parameters {'Omega_m': 0.1429904125067427}
2023-07-02 10:24:59,048 [prior] Evaluating prior at array([0.14299041])
2023-07-02 10:24:59,048 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:59,048 [model] Got input parameters: {'Omega_m': 0.1429904125067427, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:59,048 [classy] Got parameters {'Omega_m': 0.1429904125067427, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:59,048 [classy] Computing new state
2023-07-02 10:24:59,048 [classy] Setting parameters: {'Omega_m': 0.1429904125067427, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:59,096 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 174.62434230295347}
2023-07-02 10:24:59,096 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:59,098 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.94289
2023-07-02 10:24:59,098 [model] Computed derived parameters: {}
2023-07-02 10:24:59,098 [model] Posterior to be computed for parameters {'Omega_m': 0.28883176986597187}
2023-07-02 10:24:59,098 [prior] Evaluating prior at array([0.28883177])
2023-07-02 10:24:59,098 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:59,098 [model] Got input parameters: {'Omega_m': 0.28883176986597187, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:59,098 [classy] Got parameters {'Omega_m': 0.28883176986597187, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:59,098 [classy] Computing new state
2023-07-02 10:24:59,098 [classy] Setting parameters: {'Omega_m': 0.28883176986597187, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:59,146 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.20567030704817}
2023-07-02 10:24:59,146 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:59,148 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0366362
2023-07-02 10:24:59,148 [model] Computed derived parameters: {}
2023-07-02 10:24:59,148 [mcmc] New sample, #497:
Omega_m:0.2684476
2023-07-02 10:24:59,148 [model] Posterior to be computed for parameters {'Omega_m': -0.18935579704719563}
2023-07-02 10:24:59,148 [prior] Evaluating prior at array([-0.1893558])
2023-07-02 10:24:59,148 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:59,148 [model] Posterior to be computed for parameters {'Omega_m': 0.6375616439072355}
2023-07-02 10:24:59,149 [prior] Evaluating prior at array([0.63756164])
2023-07-02 10:24:59,149 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:59,149 [model] Got input parameters: {'Omega_m': 0.6375616439072355, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:59,149 [classy] Got parameters {'Omega_m': 0.6375616439072355, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:59,149 [classy] Computing new state
2023-07-02 10:24:59,149 [classy] Setting parameters: {'Omega_m': 0.6375616439072355, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:59,195 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 119.95225342070886}
2023-07-02 10:24:59,196 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:59,197 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.44807
2023-07-02 10:24:59,197 [model] Computed derived parameters: {}
2023-07-02 10:24:59,197 [model] Posterior to be computed for parameters {'Omega_m': -0.19592901185617134}
2023-07-02 10:24:59,198 [prior] Evaluating prior at array([-0.19592901])
2023-07-02 10:24:59,198 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:59,198 [model] Posterior to be computed for parameters {'Omega_m': -0.045400155786379404}
2023-07-02 10:24:59,198 [prior] Evaluating prior at array([-0.04540016])
2023-07-02 10:24:59,198 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:59,198 [model] Posterior to be computed for parameters {'Omega_m': 0.3644019137285386}
2023-07-02 10:24:59,198 [prior] Evaluating prior at array([0.36440191])
2023-07-02 10:24:59,198 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:59,198 [model] Got input parameters: {'Omega_m': 0.3644019137285386, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:59,198 [classy] Got parameters {'Omega_m': 0.3644019137285386, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:59,198 [classy] Computing new state
2023-07-02 10:24:59,198 [classy] Setting parameters: {'Omega_m': 0.3644019137285386, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:59,246 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.4367823130311}
2023-07-02 10:24:59,246 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:59,248 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.14634
2023-07-02 10:24:59,248 [model] Computed derived parameters: {}
2023-07-02 10:24:59,248 [mcmc] New sample, #498:
Omega_m:0.2888318
2023-07-02 10:24:59,248 [model] Posterior to be computed for parameters {'Omega_m': 0.0249409911446416}
2023-07-02 10:24:59,248 [prior] Evaluating prior at array([0.02494099])
2023-07-02 10:24:59,248 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:59,248 [model] Posterior to be computed for parameters {'Omega_m': 0.5829197022100089}
2023-07-02 10:24:59,248 [prior] Evaluating prior at array([0.5829197])
2023-07-02 10:24:59,249 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:59,249 [model] Got input parameters: {'Omega_m': 0.5829197022100089, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:59,249 [classy] Got parameters {'Omega_m': 0.5829197022100089, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:59,249 [classy] Computing new state
2023-07-02 10:24:59,249 [classy] Setting parameters: {'Omega_m': 0.5829197022100089, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:59,296 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 123.383836907}
2023-07-02 10:24:59,296 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:59,297 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.60454
2023-07-02 10:24:59,298 [model] Computed derived parameters: {}
2023-07-02 10:24:59,298 [model] Posterior to be computed for parameters {'Omega_m': 0.31695111855817837}
2023-07-02 10:24:59,298 [prior] Evaluating prior at array([0.31695112])
2023-07-02 10:24:59,298 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:59,298 [model] Got input parameters: {'Omega_m': 0.31695111855817837, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:59,298 [classy] Got parameters {'Omega_m': 0.31695111855817837, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:59,298 [classy] Computing new state
2023-07-02 10:24:59,298 [classy] Setting parameters: {'Omega_m': 0.31695111855817837, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:59,345 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.72599527735125}
2023-07-02 10:24:59,346 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:59,347 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00141258
2023-07-02 10:24:59,347 [model] Computed derived parameters: {}
2023-07-02 10:24:59,347 [mcmc] New sample, #499:
Omega_m:0.3644019
2023-07-02 10:24:59,348 [model] Posterior to be computed for parameters {'Omega_m': 0.15372104750792787}
2023-07-02 10:24:59,348 [prior] Evaluating prior at array([0.15372105])
2023-07-02 10:24:59,348 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:59,348 [model] Got input parameters: {'Omega_m': 0.15372104750792787, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:59,348 [classy] Got parameters {'Omega_m': 0.15372104750792787, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:59,348 [classy] Computing new state
2023-07-02 10:24:59,348 [classy] Setting parameters: {'Omega_m': 0.15372104750792787, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:59,395 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 172.31394142664675}
2023-07-02 10:24:59,395 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:59,396 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.48181
2023-07-02 10:24:59,396 [model] Computed derived parameters: {}
2023-07-02 10:24:59,397 [model] Posterior to be computed for parameters {'Omega_m': -0.3289677563516449}
2023-07-02 10:24:59,397 [prior] Evaluating prior at array([-0.32896776])
2023-07-02 10:24:59,397 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:59,397 [model] Posterior to be computed for parameters {'Omega_m': 1.0192840218664285}
2023-07-02 10:24:59,397 [prior] Evaluating prior at array([1.01928402])
2023-07-02 10:24:59,397 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:59,397 [model] Posterior to be computed for parameters {'Omega_m': 0.27843262830493365}
2023-07-02 10:24:59,397 [prior] Evaluating prior at array([0.27843263])
2023-07-02 10:24:59,397 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:59,397 [model] Got input parameters: {'Omega_m': 0.27843262830493365, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:59,397 [classy] Got parameters {'Omega_m': 0.27843262830493365, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:59,397 [classy] Computing new state
2023-07-02 10:24:59,397 [classy] Setting parameters: {'Omega_m': 0.27843262830493365, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:59,445 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.56765463453382}
2023-07-02 10:24:59,445 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:59,447 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0778159
2023-07-02 10:24:59,447 [model] Computed derived parameters: {}
2023-07-02 10:24:59,447 [mcmc] New sample, #500:
Omega_m:0.3169511
2023-07-02 10:24:59,447 [model] Posterior to be computed for parameters {'Omega_m': 0.40583131383172233}
2023-07-02 10:24:59,447 [prior] Evaluating prior at array([0.40583131])
2023-07-02 10:24:59,447 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:59,447 [model] Got input parameters: {'Omega_m': 0.40583131383172233, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:59,447 [classy] Got parameters {'Omega_m': 0.40583131383172233, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:59,447 [classy] Computing new state
2023-07-02 10:24:59,447 [classy] Setting parameters: {'Omega_m': 0.40583131383172233, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:59,495 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 137.31652425787706}
2023-07-02 10:24:59,495 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:59,496 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.431732
2023-07-02 10:24:59,496 [model] Computed derived parameters: {}
2023-07-02 10:24:59,496 [mcmc] New sample, #501:
Omega_m:0.2784326
2023-07-02 10:24:59,497 [model] Posterior to be computed for parameters {'Omega_m': 0.2152010804542365}
2023-07-02 10:24:59,497 [prior] Evaluating prior at array([0.21520108])
2023-07-02 10:24:59,497 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:59,497 [model] Got input parameters: {'Omega_m': 0.2152010804542365, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:59,497 [classy] Got parameters {'Omega_m': 0.2152010804542365, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:59,497 [classy] Computing new state
2023-07-02 10:24:59,497 [classy] Setting parameters: {'Omega_m': 0.2152010804542365, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:59,545 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 160.90686101606065}
2023-07-02 10:24:59,545 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:59,547 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.759186
2023-07-02 10:24:59,547 [model] Computed derived parameters: {}
2023-07-02 10:24:59,547 [mcmc] New sample, #502:
Omega_m:0.4058313
2023-07-02 10:24:59,547 [model] Posterior to be computed for parameters {'Omega_m': 0.24083491369506746}
2023-07-02 10:24:59,547 [prior] Evaluating prior at array([0.24083491])
2023-07-02 10:24:59,547 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:59,547 [model] Got input parameters: {'Omega_m': 0.24083491369506746, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:59,547 [classy] Got parameters {'Omega_m': 0.24083491369506746, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:59,547 [classy] Computing new state
2023-07-02 10:24:59,547 [classy] Setting parameters: {'Omega_m': 0.24083491369506746, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:59,595 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 156.88077284093114}
2023-07-02 10:24:59,595 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:59,597 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.381612
2023-07-02 10:24:59,597 [model] Computed derived parameters: {}
2023-07-02 10:24:59,597 [mcmc] New sample, #503:
Omega_m:0.2152011
2023-07-02 10:24:59,597 [model] Posterior to be computed for parameters {'Omega_m': 0.21818592324265312}
2023-07-02 10:24:59,597 [prior] Evaluating prior at array([0.21818592])
2023-07-02 10:24:59,598 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:59,598 [model] Got input parameters: {'Omega_m': 0.21818592324265312, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:59,598 [classy] Got parameters {'Omega_m': 0.21818592324265312, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:59,598 [classy] Computing new state
2023-07-02 10:24:59,598 [classy] Setting parameters: {'Omega_m': 0.21818592324265312, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:59,646 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 160.41905100810837}
2023-07-02 10:24:59,646 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:59,647 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.706833
2023-07-02 10:24:59,647 [model] Computed derived parameters: {}
2023-07-02 10:24:59,648 [model] Posterior to be computed for parameters {'Omega_m': 0.19965710470644535}
2023-07-02 10:24:59,648 [prior] Evaluating prior at array([0.1996571])
2023-07-02 10:24:59,648 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:59,648 [model] Got input parameters: {'Omega_m': 0.19965710470644535, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:59,648 [classy] Got parameters {'Omega_m': 0.19965710470644535, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:59,648 [classy] Computing new state
2023-07-02 10:24:59,648 [classy] Setting parameters: {'Omega_m': 0.19965710470644535, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:59,695 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 163.53551354914342}
2023-07-02 10:24:59,696 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:59,697 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.07208
2023-07-02 10:24:59,697 [model] Computed derived parameters: {}
2023-07-02 10:24:59,698 [model] Posterior to be computed for parameters {'Omega_m': 0.3272900214423215}
2023-07-02 10:24:59,698 [prior] Evaluating prior at array([0.32729002])
2023-07-02 10:24:59,698 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:59,698 [model] Got input parameters: {'Omega_m': 0.3272900214423215, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:59,698 [classy] Got parameters {'Omega_m': 0.3272900214423215, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:59,698 [classy] Computing new state
2023-07-02 10:24:59,698 [classy] Setting parameters: {'Omega_m': 0.3272900214423215, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:59,746 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.5151228873236}
2023-07-02 10:24:59,746 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:59,747 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0131653
2023-07-02 10:24:59,747 [model] Computed derived parameters: {}
2023-07-02 10:24:59,748 [mcmc] New sample, #504:
Omega_m:0.2408349
2023-07-02 10:24:59,748 [model] Posterior to be computed for parameters {'Omega_m': -0.3890205184394315}
2023-07-02 10:24:59,748 [prior] Evaluating prior at array([-0.38902052])
2023-07-02 10:24:59,748 [prior] Got logpriors (internal) = -inf
2023-07-02 10:24:59,748 [model] Posterior to be computed for parameters {'Omega_m': 0.4287357291747858}
2023-07-02 10:24:59,748 [prior] Evaluating prior at array([0.42873573])
2023-07-02 10:24:59,748 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:59,748 [model] Got input parameters: {'Omega_m': 0.4287357291747858, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:59,748 [classy] Got parameters {'Omega_m': 0.4287357291747858, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:59,748 [classy] Computing new state
2023-07-02 10:24:59,748 [classy] Setting parameters: {'Omega_m': 0.4287357291747858, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:59,796 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 135.20741358414028}
2023-07-02 10:24:59,796 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:59,798 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.63842
2023-07-02 10:24:59,798 [model] Computed derived parameters: {}
2023-07-02 10:24:59,798 [mcmc] New sample, #505:
Omega_m:0.32729
2023-07-02 10:24:59,798 [model] Posterior to be computed for parameters {'Omega_m': 0.6069887891387977}
2023-07-02 10:24:59,798 [prior] Evaluating prior at array([0.60698879])
2023-07-02 10:24:59,798 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:59,798 [model] Got input parameters: {'Omega_m': 0.6069887891387977, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:59,798 [classy] Got parameters {'Omega_m': 0.6069887891387977, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:59,798 [classy] Computing new state
2023-07-02 10:24:59,798 [classy] Setting parameters: {'Omega_m': 0.6069887891387977, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:59,848 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 121.83231517459835}
2023-07-02 10:24:59,848 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:59,850 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.96996
2023-07-02 10:24:59,850 [model] Computed derived parameters: {}
2023-07-02 10:24:59,850 [mcmc] New sample, #506:
Omega_m:0.4287357
2023-07-02 10:24:59,850 [model] Posterior to be computed for parameters {'Omega_m': 0.6812572224799933}
2023-07-02 10:24:59,850 [prior] Evaluating prior at array([0.68125722])
2023-07-02 10:24:59,850 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:59,850 [model] Got input parameters: {'Omega_m': 0.6812572224799933, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:59,850 [classy] Got parameters {'Omega_m': 0.6812572224799933, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:59,850 [classy] Computing new state
2023-07-02 10:24:59,850 [classy] Setting parameters: {'Omega_m': 0.6812572224799933, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:59,899 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 117.42514018091656}
2023-07-02 10:24:59,899 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:59,901 [bao_likelihood.baolikelihood] Computed log-likelihood = -4.15314
2023-07-02 10:24:59,901 [model] Computed derived parameters: {}
2023-07-02 10:24:59,901 [mcmc] New sample, #507:
Omega_m:0.6069888
2023-07-02 10:24:59,901 [model] Posterior to be computed for parameters {'Omega_m': 0.9532714533403336}
2023-07-02 10:24:59,901 [prior] Evaluating prior at array([0.95327145])
2023-07-02 10:24:59,901 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:59,901 [model] Got input parameters: {'Omega_m': 0.9532714533403336, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:59,901 [classy] Got parameters {'Omega_m': 0.9532714533403336, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:59,901 [classy] Computing new state
2023-07-02 10:24:59,901 [classy] Setting parameters: {'Omega_m': 0.9532714533403336, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:59,949 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 104.85289745108174}
2023-07-02 10:24:59,949 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:24:59,951 [bao_likelihood.baolikelihood] Computed log-likelihood = -8.80199
2023-07-02 10:24:59,951 [model] Computed derived parameters: {}
2023-07-02 10:24:59,951 [model] Posterior to be computed for parameters {'Omega_m': 0.8146510914440364}
2023-07-02 10:24:59,951 [prior] Evaluating prior at array([0.81465109])
2023-07-02 10:24:59,951 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:24:59,951 [model] Got input parameters: {'Omega_m': 0.8146510914440364, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:59,951 [classy] Got parameters {'Omega_m': 0.8146510914440364, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:24:59,951 [classy] Computing new state
2023-07-02 10:24:59,951 [classy] Setting parameters: {'Omega_m': 0.8146510914440364, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:24:59,999 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 110.67629036113388}
2023-07-02 10:24:59,999 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:25:00,001 [bao_likelihood.baolikelihood] Computed log-likelihood = -6.40305
2023-07-02 10:25:00,001 [model] Computed derived parameters: {}
2023-07-02 10:25:00,001 [model] Posterior to be computed for parameters {'Omega_m': 0.4368508942887319}
2023-07-02 10:25:00,001 [prior] Evaluating prior at array([0.43685089])
2023-07-02 10:25:00,001 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:25:00,001 [model] Got input parameters: {'Omega_m': 0.4368508942887319, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:00,001 [classy] Got parameters {'Omega_m': 0.4368508942887319, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:00,001 [classy] Computing new state
2023-07-02 10:25:00,001 [classy] Setting parameters: {'Omega_m': 0.4368508942887319, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:25:00,050 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 134.4861873550882}
2023-07-02 10:25:00,050 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:25:00,052 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.718729
2023-07-02 10:25:00,052 [model] Computed derived parameters: {}
2023-07-02 10:25:00,052 [mcmc] New sample, #508:
Omega_m:0.6812572
2023-07-02 10:25:00,052 [model] Posterior to be computed for parameters {'Omega_m': 0.03043767468106101}
2023-07-02 10:25:00,052 [prior] Evaluating prior at array([0.03043767])
2023-07-02 10:25:00,052 [prior] Got logpriors (internal) = -inf
2023-07-02 10:25:00,052 [model] Posterior to be computed for parameters {'Omega_m': 0.6520482490851541}
2023-07-02 10:25:00,053 [prior] Evaluating prior at array([0.65204825])
2023-07-02 10:25:00,053 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:25:00,053 [model] Got input parameters: {'Omega_m': 0.6520482490851541, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:00,053 [classy] Got parameters {'Omega_m': 0.6520482490851541, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:00,053 [classy] Computing new state
2023-07-02 10:25:00,053 [classy] Setting parameters: {'Omega_m': 0.6520482490851541, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:25:00,099 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 119.09447310723998}
2023-07-02 10:25:00,099 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:25:00,101 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.67928
2023-07-02 10:25:00,101 [model] Computed derived parameters: {}
2023-07-02 10:25:00,102 [model] Posterior to be computed for parameters {'Omega_m': 0.5298418992954042}
2023-07-02 10:25:00,102 [prior] Evaluating prior at array([0.5298419])
2023-07-02 10:25:00,102 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:25:00,102 [model] Got input parameters: {'Omega_m': 0.5298418992954042, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:00,102 [classy] Got parameters {'Omega_m': 0.5298418992954042, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:00,102 [classy] Computing new state
2023-07-02 10:25:00,102 [classy] Setting parameters: {'Omega_m': 0.5298418992954042, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:25:00,150 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 127.05403777363148}
2023-07-02 10:25:00,151 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:25:00,152 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.84226
2023-07-02 10:25:00,152 [model] Computed derived parameters: {}
2023-07-02 10:25:00,153 [model] Posterior to be computed for parameters {'Omega_m': 0.5271170380259129}
2023-07-02 10:25:00,153 [prior] Evaluating prior at array([0.52711704])
2023-07-02 10:25:00,153 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:25:00,153 [model] Got input parameters: {'Omega_m': 0.5271170380259129, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:00,153 [classy] Got parameters {'Omega_m': 0.5271170380259129, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:00,153 [classy] Computing new state
2023-07-02 10:25:00,153 [classy] Setting parameters: {'Omega_m': 0.5271170380259129, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:25:00,201 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 127.25252759793983}
2023-07-02 10:25:00,201 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:25:00,203 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.80504
2023-07-02 10:25:00,203 [model] Computed derived parameters: {}
2023-07-02 10:25:00,203 [model] Posterior to be computed for parameters {'Omega_m': 0.20360865673521666}
2023-07-02 10:25:00,203 [prior] Evaluating prior at array([0.20360866])
2023-07-02 10:25:00,203 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:25:00,203 [model] Got input parameters: {'Omega_m': 0.20360865673521666, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:00,203 [classy] Got parameters {'Omega_m': 0.20360865673521666, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:00,203 [classy] Computing new state
2023-07-02 10:25:00,203 [classy] Setting parameters: {'Omega_m': 0.20360865673521666, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:25:00,252 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 162.85274910686618}
2023-07-02 10:25:00,252 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:25:00,254 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.985848
2023-07-02 10:25:00,254 [model] Computed derived parameters: {}
2023-07-02 10:25:00,254 [mcmc] New sample, #509:
Omega_m:0.4368509
2023-07-02 10:25:00,254 [model] Posterior to be computed for parameters {'Omega_m': 0.41891353769913114}
2023-07-02 10:25:00,254 [prior] Evaluating prior at array([0.41891354])
2023-07-02 10:25:00,255 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:25:00,255 [model] Got input parameters: {'Omega_m': 0.41891353769913114, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:00,255 [classy] Got parameters {'Omega_m': 0.41891353769913114, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:00,255 [classy] Computing new state
2023-07-02 10:25:00,255 [classy] Setting parameters: {'Omega_m': 0.41891353769913114, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:25:00,303 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 136.09825634316107}
2023-07-02 10:25:00,303 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:25:00,305 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.546026
2023-07-02 10:25:00,306 [model] Computed derived parameters: {}
2023-07-02 10:25:00,306 [mcmc] New sample, #510:
Omega_m:0.2036087
2023-07-02 10:25:00,306 [model] Posterior to be computed for parameters {'Omega_m': 0.426431484356208}
2023-07-02 10:25:00,306 [prior] Evaluating prior at array([0.42643148])
2023-07-02 10:25:00,306 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:25:00,306 [model] Got input parameters: {'Omega_m': 0.426431484356208, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:00,306 [classy] Got parameters {'Omega_m': 0.426431484356208, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:00,306 [classy] Computing new state
2023-07-02 10:25:00,306 [classy] Setting parameters: {'Omega_m': 0.426431484356208, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:25:00,353 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 135.41460601900008}
2023-07-02 10:25:00,354 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:25:00,356 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.616264
2023-07-02 10:25:00,356 [model] Computed derived parameters: {}
2023-07-02 10:25:00,356 [mcmc] New sample, #511:
Omega_m:0.4189135
2023-07-02 10:25:00,356 [model] Posterior to be computed for parameters {'Omega_m': 0.4331236397817187}
2023-07-02 10:25:00,356 [prior] Evaluating prior at array([0.43312364])
2023-07-02 10:25:00,356 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:25:00,356 [model] Got input parameters: {'Omega_m': 0.4331236397817187, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:00,356 [classy] Got parameters {'Omega_m': 0.4331236397817187, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:00,356 [classy] Computing new state
2023-07-02 10:25:00,356 [classy] Setting parameters: {'Omega_m': 0.4331236397817187, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:25:00,404 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 134.8158189429784}
2023-07-02 10:25:00,404 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:25:00,406 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.68141
2023-07-02 10:25:00,406 [model] Computed derived parameters: {}
2023-07-02 10:25:00,406 [model] Posterior to be computed for parameters {'Omega_m': 0.3590992070220916}
2023-07-02 10:25:00,406 [prior] Evaluating prior at array([0.35909921])
2023-07-02 10:25:00,406 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:25:00,406 [model] Got input parameters: {'Omega_m': 0.3590992070220916, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:00,406 [classy] Got parameters {'Omega_m': 0.3590992070220916, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:00,406 [classy] Computing new state
2023-07-02 10:25:00,406 [classy] Setting parameters: {'Omega_m': 0.3590992070220916, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:25:00,454 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.99547961113245}
2023-07-02 10:25:00,454 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:25:00,456 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.119443
2023-07-02 10:25:00,456 [model] Computed derived parameters: {}
2023-07-02 10:25:00,456 [mcmc] New sample, #512:
Omega_m:0.4264315
2023-07-02 10:25:00,456 [model] Posterior to be computed for parameters {'Omega_m': 0.4292568163630922}
2023-07-02 10:25:00,456 [prior] Evaluating prior at array([0.42925682])
2023-07-02 10:25:00,457 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:25:00,457 [model] Got input parameters: {'Omega_m': 0.4292568163630922, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:00,457 [classy] Got parameters {'Omega_m': 0.4292568163630922, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:00,457 [classy] Computing new state
2023-07-02 10:25:00,457 [classy] Setting parameters: {'Omega_m': 0.4292568163630922, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:25:00,504 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 135.16070681432302}
2023-07-02 10:25:00,504 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:25:00,506 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.643471
2023-07-02 10:25:00,506 [model] Computed derived parameters: {}
2023-07-02 10:25:00,506 [model] Posterior to be computed for parameters {'Omega_m': 0.14034099639645511}
2023-07-02 10:25:00,506 [prior] Evaluating prior at array([0.140341])
2023-07-02 10:25:00,506 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:25:00,506 [model] Got input parameters: {'Omega_m': 0.14034099639645511, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:00,506 [classy] Got parameters {'Omega_m': 0.14034099639645511, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:00,506 [classy] Computing new state
2023-07-02 10:25:00,506 [classy] Setting parameters: {'Omega_m': 0.14034099639645511, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:25:00,554 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 175.21238318984066}
2023-07-02 10:25:00,554 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:25:00,556 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.06605
2023-07-02 10:25:00,556 [model] Computed derived parameters: {}
2023-07-02 10:25:00,556 [model] Posterior to be computed for parameters {'Omega_m': 0.1352732136373893}
2023-07-02 10:25:00,556 [prior] Evaluating prior at array([0.13527321])
2023-07-02 10:25:00,556 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:25:00,556 [model] Got input parameters: {'Omega_m': 0.1352732136373893, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:00,556 [classy] Got parameters {'Omega_m': 0.1352732136373893, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:00,556 [classy] Computing new state
2023-07-02 10:25:00,556 [classy] Setting parameters: {'Omega_m': 0.1352732136373893, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:25:00,603 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 176.35775461212725}
2023-07-02 10:25:00,603 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:25:00,605 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.31265
2023-07-02 10:25:00,605 [model] Computed derived parameters: {}
2023-07-02 10:25:00,606 [model] Posterior to be computed for parameters {'Omega_m': 0.5222116666774199}
2023-07-02 10:25:00,606 [prior] Evaluating prior at array([0.52221167])
2023-07-02 10:25:00,606 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:25:00,606 [model] Got input parameters: {'Omega_m': 0.5222116666774199, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:00,606 [classy] Got parameters {'Omega_m': 0.5222116666774199, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:00,606 [classy] Computing new state
2023-07-02 10:25:00,606 [classy] Setting parameters: {'Omega_m': 0.5222116666774199, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:25:00,654 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 127.61250208223163}
2023-07-02 10:25:00,655 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:25:00,656 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.73858
2023-07-02 10:25:00,656 [model] Computed derived parameters: {}
2023-07-02 10:25:00,657 [model] Posterior to be computed for parameters {'Omega_m': 0.020585103948990657}
2023-07-02 10:25:00,657 [prior] Evaluating prior at array([0.0205851])
2023-07-02 10:25:00,657 [prior] Got logpriors (internal) = -inf
2023-07-02 10:25:00,657 [model] Posterior to be computed for parameters {'Omega_m': 1.0512445780095014}
2023-07-02 10:25:00,657 [prior] Evaluating prior at array([1.05124458])
2023-07-02 10:25:00,657 [prior] Got logpriors (internal) = -inf
2023-07-02 10:25:00,657 [model] Posterior to be computed for parameters {'Omega_m': 0.5746449049384776}
2023-07-02 10:25:00,657 [prior] Evaluating prior at array([0.5746449])
2023-07-02 10:25:00,657 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:25:00,657 [model] Got input parameters: {'Omega_m': 0.5746449049384776, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:00,657 [classy] Got parameters {'Omega_m': 0.5746449049384776, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:00,657 [classy] Computing new state
2023-07-02 10:25:00,657 [classy] Setting parameters: {'Omega_m': 0.5746449049384776, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:25:00,705 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 123.93273897843247}
2023-07-02 10:25:00,705 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:25:00,707 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.48147
2023-07-02 10:25:00,707 [model] Computed derived parameters: {}
2023-07-02 10:25:00,707 [model] Posterior to be computed for parameters {'Omega_m': -0.018261187069966267}
2023-07-02 10:25:00,707 [prior] Evaluating prior at array([-0.01826119])
2023-07-02 10:25:00,707 [prior] Got logpriors (internal) = -inf
2023-07-02 10:25:00,708 [model] Posterior to be computed for parameters {'Omega_m': 0.6524456064256794}
2023-07-02 10:25:00,708 [prior] Evaluating prior at array([0.65244561])
2023-07-02 10:25:00,708 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:25:00,708 [model] Got input parameters: {'Omega_m': 0.6524456064256794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:00,708 [classy] Got parameters {'Omega_m': 0.6524456064256794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:00,708 [classy] Computing new state
2023-07-02 10:25:00,708 [classy] Setting parameters: {'Omega_m': 0.6524456064256794, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:25:00,756 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 119.07123097320716}
2023-07-02 10:25:00,756 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:25:00,758 [bao_likelihood.baolikelihood] Computed log-likelihood = -3.68566
2023-07-02 10:25:00,758 [model] Computed derived parameters: {}
2023-07-02 10:25:00,758 [model] Posterior to be computed for parameters {'Omega_m': 0.4878308793130527}
2023-07-02 10:25:00,758 [prior] Evaluating prior at array([0.48783088])
2023-07-02 10:25:00,758 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:25:00,758 [model] Got input parameters: {'Omega_m': 0.4878308793130527, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:00,759 [classy] Got parameters {'Omega_m': 0.4878308793130527, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:00,759 [classy] Computing new state
2023-07-02 10:25:00,759 [classy] Setting parameters: {'Omega_m': 0.4878308793130527, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:25:00,807 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 130.23573327039216}
2023-07-02 10:25:00,807 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:25:00,810 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.29409
2023-07-02 10:25:00,810 [model] Computed derived parameters: {}
2023-07-02 10:25:00,810 [model] Posterior to be computed for parameters {'Omega_m': 0.26293436911561363}
2023-07-02 10:25:00,810 [prior] Evaluating prior at array([0.26293437])
2023-07-02 10:25:00,810 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:25:00,810 [model] Got input parameters: {'Omega_m': 0.26293436911561363, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:00,811 [classy] Got parameters {'Omega_m': 0.26293436911561363, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:00,811 [classy] Computing new state
2023-07-02 10:25:00,811 [classy] Setting parameters: {'Omega_m': 0.26293436911561363, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:25:00,858 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.68032840352754}
2023-07-02 10:25:00,859 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:25:00,861 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.171587
2023-07-02 10:25:00,861 [model] Computed derived parameters: {}
2023-07-02 10:25:00,861 [mcmc] New sample, #513:
Omega_m:0.3590992
2023-07-02 10:25:00,861 [model] Posterior to be computed for parameters {'Omega_m': -0.0668037159471826}
2023-07-02 10:25:00,861 [prior] Evaluating prior at array([-0.06680372])
2023-07-02 10:25:00,861 [prior] Got logpriors (internal) = -inf
2023-07-02 10:25:00,862 [model] Posterior to be computed for parameters {'Omega_m': 0.4270595017916761}
2023-07-02 10:25:00,862 [prior] Evaluating prior at array([0.4270595])
2023-07-02 10:25:00,862 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:25:00,862 [model] Got input parameters: {'Omega_m': 0.4270595017916761, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:00,862 [classy] Got parameters {'Omega_m': 0.4270595017916761, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:00,862 [classy] Computing new state
2023-07-02 10:25:00,862 [classy] Setting parameters: {'Omega_m': 0.4270595017916761, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:25:00,911 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 135.3580295449772}
2023-07-02 10:25:00,911 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:25:00,912 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.622274
2023-07-02 10:25:00,913 [model] Computed derived parameters: {}
2023-07-02 10:25:00,913 [model] Posterior to be computed for parameters {'Omega_m': -0.06052913516716146}
2023-07-02 10:25:00,913 [prior] Evaluating prior at array([-0.06052914])
2023-07-02 10:25:00,913 [prior] Got logpriors (internal) = -inf
2023-07-02 10:25:00,913 [model] Posterior to be computed for parameters {'Omega_m': -0.09805194209068252}
2023-07-02 10:25:00,913 [prior] Evaluating prior at array([-0.09805194])
2023-07-02 10:25:00,913 [prior] Got logpriors (internal) = -inf
2023-07-02 10:25:00,913 [model] Posterior to be computed for parameters {'Omega_m': 0.4166198707325491}
2023-07-02 10:25:00,913 [prior] Evaluating prior at array([0.41661987])
2023-07-02 10:25:00,913 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:25:00,913 [model] Got input parameters: {'Omega_m': 0.4166198707325491, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:00,913 [classy] Got parameters {'Omega_m': 0.4166198707325491, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:00,913 [classy] Computing new state
2023-07-02 10:25:00,913 [classy] Setting parameters: {'Omega_m': 0.4166198707325491, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:25:00,961 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 136.30919160317976}
2023-07-02 10:25:00,962 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:25:00,963 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.525243
2023-07-02 10:25:00,963 [model] Computed derived parameters: {}
2023-07-02 10:25:00,963 [model] Posterior to be computed for parameters {'Omega_m': 0.3302900486851549}
2023-07-02 10:25:00,964 [prior] Evaluating prior at array([0.33029005])
2023-07-02 10:25:00,964 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:25:00,964 [model] Got input parameters: {'Omega_m': 0.3302900486851549, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:00,964 [classy] Got parameters {'Omega_m': 0.3302900486851549, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:00,964 [classy] Computing new state
2023-07-02 10:25:00,964 [classy] Setting parameters: {'Omega_m': 0.3302900486851549, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:25:01,011 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.1701818798397}
2023-07-02 10:25:01,011 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:25:01,013 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.018816
2023-07-02 10:25:01,013 [model] Computed derived parameters: {}
2023-07-02 10:25:01,013 [mcmc] New sample, #514:
Omega_m:0.2629344
2023-07-02 10:25:01,013 [model] Posterior to be computed for parameters {'Omega_m': 0.35597247926532155}
2023-07-02 10:25:01,013 [prior] Evaluating prior at array([0.35597248])
2023-07-02 10:25:01,014 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:25:01,014 [model] Got input parameters: {'Omega_m': 0.35597247926532155, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:01,014 [classy] Got parameters {'Omega_m': 0.35597247926532155, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:01,014 [classy] Computing new state
2023-07-02 10:25:01,014 [classy] Setting parameters: {'Omega_m': 0.35597247926532155, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:25:01,061 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.3285272358097}
2023-07-02 10:25:01,061 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:25:01,063 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.104727
2023-07-02 10:25:01,063 [model] Computed derived parameters: {}
2023-07-02 10:25:01,063 [mcmc] New sample, #515:
Omega_m:0.33029
2023-07-02 10:25:01,063 [model] Posterior to be computed for parameters {'Omega_m': 0.27422339025415715}
2023-07-02 10:25:01,063 [prior] Evaluating prior at array([0.27422339])
2023-07-02 10:25:01,063 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:25:01,063 [model] Got input parameters: {'Omega_m': 0.27422339025415715, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:01,063 [classy] Got parameters {'Omega_m': 0.27422339025415715, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:01,064 [classy] Computing new state
2023-07-02 10:25:01,064 [classy] Setting parameters: {'Omega_m': 0.27422339025415715, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:25:01,111 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.13134627187068}
2023-07-02 10:25:01,111 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:25:01,113 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0992979
2023-07-02 10:25:01,113 [model] Computed derived parameters: {}
2023-07-02 10:25:01,113 [mcmc] New sample, #516:
Omega_m:0.3559725
2023-07-02 10:25:01,113 [model] Posterior to be computed for parameters {'Omega_m': 0.14450886018958956}
2023-07-02 10:25:01,113 [prior] Evaluating prior at array([0.14450886])
2023-07-02 10:25:01,113 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:25:01,113 [model] Got input parameters: {'Omega_m': 0.14450886018958956, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:01,113 [classy] Got parameters {'Omega_m': 0.14450886018958956, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:01,113 [classy] Computing new state
2023-07-02 10:25:01,114 [classy] Setting parameters: {'Omega_m': 0.14450886018958956, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:25:01,161 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 174.2905413393162}
2023-07-02 10:25:01,161 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:25:01,163 [bao_likelihood.baolikelihood] Computed log-likelihood = -2.87402
2023-07-02 10:25:01,163 [model] Computed derived parameters: {}
2023-07-02 10:25:01,163 [model] Posterior to be computed for parameters {'Omega_m': 0.41123568781668945}
2023-07-02 10:25:01,163 [prior] Evaluating prior at array([0.41123569])
2023-07-02 10:25:01,163 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:25:01,163 [model] Got input parameters: {'Omega_m': 0.41123568781668945, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:01,163 [classy] Got parameters {'Omega_m': 0.41123568781668945, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:01,163 [classy] Computing new state
2023-07-02 10:25:01,163 [classy] Setting parameters: {'Omega_m': 0.41123568781668945, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:25:01,211 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 136.80874644997817}
2023-07-02 10:25:01,211 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:25:01,213 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.477686
2023-07-02 10:25:01,213 [model] Computed derived parameters: {}
2023-07-02 10:25:01,213 [mcmc] New sample, #517:
Omega_m:0.2742234
2023-07-02 10:25:01,213 [model] Posterior to be computed for parameters {'Omega_m': 0.7818493503867618}
2023-07-02 10:25:01,213 [prior] Evaluating prior at array([0.78184935])
2023-07-02 10:25:01,213 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:25:01,213 [model] Got input parameters: {'Omega_m': 0.7818493503867618, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:01,213 [classy] Got parameters {'Omega_m': 0.7818493503867618, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:01,213 [classy] Computing new state
2023-07-02 10:25:01,213 [classy] Setting parameters: {'Omega_m': 0.7818493503867618, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:25:01,260 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 112.21715650092754}
2023-07-02 10:25:01,261 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:25:01,262 [bao_likelihood.baolikelihood] Computed log-likelihood = -5.84079
2023-07-02 10:25:01,262 [model] Computed derived parameters: {}
2023-07-02 10:25:01,262 [model] Posterior to be computed for parameters {'Omega_m': 0.8116795499514405}
2023-07-02 10:25:01,262 [prior] Evaluating prior at array([0.81167955])
2023-07-02 10:25:01,263 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:25:01,263 [model] Got input parameters: {'Omega_m': 0.8116795499514405, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:01,263 [classy] Got parameters {'Omega_m': 0.8116795499514405, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:01,263 [classy] Computing new state
2023-07-02 10:25:01,263 [classy] Setting parameters: {'Omega_m': 0.8116795499514405, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:25:01,310 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 110.81303428227075}
2023-07-02 10:25:01,310 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:25:01,312 [bao_likelihood.baolikelihood] Computed log-likelihood = -6.35195
2023-07-02 10:25:01,312 [model] Computed derived parameters: {}
2023-07-02 10:25:01,312 [model] Posterior to be computed for parameters {'Omega_m': 0.2884473855225448}
2023-07-02 10:25:01,312 [prior] Evaluating prior at array([0.28844739])
2023-07-02 10:25:01,312 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:25:01,312 [model] Got input parameters: {'Omega_m': 0.2884473855225448, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:01,312 [classy] Got parameters {'Omega_m': 0.2884473855225448, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:01,312 [classy] Computing new state
2023-07-02 10:25:01,312 [classy] Setting parameters: {'Omega_m': 0.2884473855225448, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:25:01,360 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.25525320207984}
2023-07-02 10:25:01,361 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:25:01,362 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0378677
2023-07-02 10:25:01,362 [model] Computed derived parameters: {}
2023-07-02 10:25:01,362 [mcmc] New sample, #518:
Omega_m:0.4112357
2023-07-02 10:25:01,363 [model] Posterior to be computed for parameters {'Omega_m': 0.26974919374554795}
2023-07-02 10:25:01,363 [prior] Evaluating prior at array([0.26974919])
2023-07-02 10:25:01,363 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:25:01,363 [model] Got input parameters: {'Omega_m': 0.26974919374554795, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:01,363 [classy] Got parameters {'Omega_m': 0.26974919374554795, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:01,363 [classy] Computing new state
2023-07-02 10:25:01,363 [classy] Setting parameters: {'Omega_m': 0.26974919374554795, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:25:01,411 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.7386889689358}
2023-07-02 10:25:01,411 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:25:01,413 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.125333
2023-07-02 10:25:01,413 [model] Computed derived parameters: {}
2023-07-02 10:25:01,413 [mcmc] New sample, #519:
Omega_m:0.2884474
2023-07-02 10:25:01,413 [model] Posterior to be computed for parameters {'Omega_m': 0.330175272371908}
2023-07-02 10:25:01,413 [prior] Evaluating prior at array([0.33017527])
2023-07-02 10:25:01,413 [prior] Got logpriors (internal) = 0.10536051565782628
2023-07-02 10:25:01,413 [model] Got input parameters: {'Omega_m': 0.330175272371908, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:01,413 [classy] Got parameters {'Omega_m': 0.330175272371908, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:25:01,413 [classy] Computing new state
2023-07-02 10:25:01,413 [classy] Setting parameters: {'Omega_m': 0.330175272371908, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:25:01,461 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.18332575071275}
2023-07-02 10:25:01,461 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:25:01,462 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0185819
2023-07-02 10:25:01,462 [model] Computed derived parameters: {}
2023-07-02 10:25:01,463 [mcmc] New sample, #520:
Omega_m:0.2697492
2023-07-02 10:25:01,463 [mcmc] Learn + convergence test @ 520 samples accepted.
2023-07-02 10:25:01,463 [mcmc] Ready to check convergence and learn a new proposal covmat
2023-07-02 10:25:01,467 [mcmc] - Acceptance rate: 0.411
2023-07-02 10:25:01,468 [mcmc] - Condition number = 1
2023-07-02 10:25:01,468 [mcmc] - Eigenvalues = array([0.01206916])
2023-07-02 10:25:01,468 [mcmc] - Convergence of means: R-1 = 0.012069 after 416 accepted steps
2023-07-02 10:25:01,473 [mcmc] - normalized std's of bounds = array([[0.13696813],
[0.18262798]])
2023-07-02 10:25:01,473 [mcmc] - Convergence of bounds: R-1 = 0.182628 after 520 accepted steps
2023-07-02 10:25:01,474 [mcmc] The run has converged!
2023-07-02 10:25:01,483 [mcmc] Dumped checkpoint and progress info, and current covmat.
2023-07-02 10:25:01,485 [mcmc] Sampling complete after 520 accepted steps.
In [22]:
# To load Cobaya samples from disk
from getdist.mcsamples import loadMCSamples
samples_bao_cobaya = loadMCSamples('_tests/chains_bao_cobaya/chain', settings={'ignore_rows': 0.5}).copy(label='cobaya')
g = plots.get_subplot_plotter()
g.triangle_plot([samples_bao_cobaya, samples_bao_desilike],
params=['Omega_m'], markers={'Omega_m': cosmo['Omega_m']})
[000150.02] [0/1] 07-02 10:25 root WARNING outlier fraction 0.11923076923076924
CosmoSIS¶
Let's apply the static bindings to CosmoSIS. The BAOLikelihood definition is exactly the same, we just need to generate new files with a simple CosmoSISLikelihoodGenerator call.
In [23]:
%%file _tests/bao_likelihood.py
dirname = '.'
# The same as for Cobaya!
def BAOLikelihood(cosmo='external'):
import numpy as np
from desilike.observables.galaxy_clustering import BAOCompressionObservable
from desilike.likelihoods import ObservablesGaussianLikelihood
# cosmo = 'external' to tell desilike that cosmo will be provided externally
observable1 = BAOCompressionObservable(data=[1., 1.], quantities=['qpar', 'qper'], z=0.5, cosmo=cosmo)
observable2 = BAOCompressionObservable(data=[1.], quantities=['qiso'], z=1., cosmo=cosmo)
likelihood = ObservablesGaussianLikelihood([observable1, observable2],
covariance=np.diag([0.002, 0.002, 0.005]))
return likelihood
if __name__ == '__main__':
from desilike.bindings import CobayaLikelihoodGenerator, CosmoSISLikelihoodGenerator, MontePythonLikelihoodGenerator
CobayaLikelihoodGenerator(dirname=dirname)([BAOLikelihood], kw_like={'cosmo': 'external'})
# The only change!
CosmoSISLikelihoodGenerator(dirname=dirname)([BAOLikelihood], kw_like={'cosmo': 'external'})
# Let's directly generate the bindings for MontePython
MontePythonLikelihoodGenerator(dirname=dirname)([BAOLikelihood], kw_like={'cosmo': 'external'})
Overwriting _tests/bao_likelihood.py
Let's generate the static bindings by calling the above Python script
In [24]:
%%bash
cd _tests
python bao_likelihood.py
bash: /home/adematti/anaconda3/envs/cosmodesi/lib/libtinfo.so.6: no version information available (required by bash) WARNING:absl:No GPU/TPU found, falling back to CPU. (Set TF_CPP_MIN_LOG_LEVEL=0 and rerun for more info.)
Let's take a look at the generated files:
- the likelihood module:
BAOLikelihood.py - the
*values.inifile containing the values / ranges of nuisance parameters (none in this case), to be copy-pasted in the input*values.ini(see below) - the
*priors.inifile containing the optional priors of nuisance parameters, to be copy-pasted in the input*priors.inifile
In [25]:
ls -la _tests/cosmosis
/bin/bash: /home/adematti/anaconda3/envs/cosmodesi/lib/libtinfo.so.6: no version information available (required by /bin/bash) total 20 drwxr-xr-x 2 adematti idphp 4096 juil. 2 10:25 ./ drwxr-xr-x 7 adematti idphp 4096 juil. 2 10:25 ../ -rw-r--r-- 1 adematti idphp 7 juil. 2 10:25 BAOLikelihood_priors.ini -rw-r--r-- 1 adematti idphp 543 juil. 2 10:25 BAOLikelihood.py -rw-r--r-- 1 adematti idphp 7 juil. 2 10:25 BAOLikelihood_values.ini
Now let's write the config file to run inference. This is pure CosmoSIS.
In [26]:
%%file _tests/config_bao.ini
[DEFAULT]
fatal_errors = T
[runtime]
sampler = emcee
[output]
filename = _tests/chains_bao_cosmosis/chain.txt
format = text
verbosity = 0
[pipeline]
modules = consistency camb bao
values = _tests/values_bao.ini
likelihoods = BAOLikelihood ; notice the name of the liklelihood: the same as the *.py file
quiet = T
debug = F
timing = F
[consistency]
file = ${COSMOSIS_STD_DIR}/utility/consistency/consistency_interface.py
[camb]
file = ${COSMOSIS_STD_DIR}/boltzmann/camb/camb_interface.py
mode = background
feedback = 0
nz = 901
[bao]
file = _tests/cosmosis/BAOLikelihood.py
[emcee]
walkers = 6
samples = 600
nsteps = 20
Writing _tests/config_bao.ini
The *values.ini file containing parameter values and ranges
In [27]:
%%file _tests/values_bao.ini
[cosmological_parameters]
; This is the only parameter being varied.
omega_m = 0.1 0.3 0.9
ombh2 = 0.02237
h0 = 0.6736
A_s = 2.083e-09
n_s = 0.9649
tau = 0.0544
mnu = 0.06
nnu = 3.046
num_massive_neutrinos = 1
omega_k = 0.0
w = -1.0
wa = 0.0
Writing _tests/values_bao.ini
Let's sample!
In [28]:
!cosmosis _tests/config_bao.ini
/bin/bash: /home/adematti/anaconda3/envs/cosmodesi/lib/libtinfo.so.6: no version information available (required by /bin/bash) WARNING:absl:No GPU/TPU found, falling back to CPU. (Set TF_CPP_MIN_LOG_LEVEL=0 and rerun for more info.) Parameter Priors ---------------- cosmological_parameters--omega_m ~ U(0.1, 0.9) cosmological_parameters--ombh2 ~ delta(0.02237) cosmological_parameters--h0 ~ delta(0.6736) cosmological_parameters--a_s ~ delta(2.083e-09) cosmological_parameters--n_s ~ delta(0.9649) cosmological_parameters--tau ~ delta(0.0544) cosmological_parameters--mnu ~ delta(0.06) cosmological_parameters--nnu ~ delta(3.046) cosmological_parameters--num_massive_neutrinos ~ delta(1) cosmological_parameters--omega_k ~ delta(0.0) cosmological_parameters--w ~ delta(-1.0) cosmological_parameters--wa ~ delta(0.0) **************************** * Running sampler 1/1: emcee * Saving output -> _tests/chains_bao_cosmosis/chain.txt **************************** Begun sampling Done 20 iterations of emcee. Acceptance fraction 0.958 Done 40 iterations of emcee. Acceptance fraction 0.904 Done 60 iterations of emcee. Acceptance fraction 0.856 Done 80 iterations of emcee. Acceptance fraction 0.844 Done 100 iterations of emcee. Acceptance fraction 0.835 Done 120 iterations of emcee. Acceptance fraction 0.835 Done 140 iterations of emcee. Acceptance fraction 0.820 Done 160 iterations of emcee. Acceptance fraction 0.806 Done 180 iterations of emcee. Acceptance fraction 0.804 Done 200 iterations of emcee. Acceptance fraction 0.817 Done 220 iterations of emcee. Acceptance fraction 0.809 Done 240 iterations of emcee. Acceptance fraction 0.806 Done 260 iterations of emcee. Acceptance fraction 0.805 Done 280 iterations of emcee. Acceptance fraction 0.807 Done 300 iterations of emcee. Acceptance fraction 0.806 Done 320 iterations of emcee. Acceptance fraction 0.801 Done 340 iterations of emcee. Acceptance fraction 0.801 Done 360 iterations of emcee. Acceptance fraction 0.807 Done 380 iterations of emcee. Acceptance fraction 0.804 Done 400 iterations of emcee. Acceptance fraction 0.806 Done 420 iterations of emcee. Acceptance fraction 0.806 Done 440 iterations of emcee. Acceptance fraction 0.805 Done 460 iterations of emcee. Acceptance fraction 0.808 Done 480 iterations of emcee. Acceptance fraction 0.808 Done 500 iterations of emcee. Acceptance fraction 0.810 Done 520 iterations of emcee. Acceptance fraction 0.808 Done 540 iterations of emcee. Acceptance fraction 0.807 Done 560 iterations of emcee. Acceptance fraction 0.808 Done 580 iterations of emcee. Acceptance fraction 0.808 Done 600 iterations of emcee. Acceptance fraction 0.806
In [29]:
# To load CosmoSIS samples from disk
from cosmosis import Inifile
from cosmosis.output import input_from_options
from getdist import MCSamples
ini = Inifile('_tests/config_bao.ini')
options = dict(ini.items('output'))
options['filename'] = '_tests/chains_bao_cosmosis/chain.txt'
column_names, data = input_from_options(options)[:2]
#print(column_names)
data = data[0].T
data = data[..., data.shape[-1] // 2:] # removing burnin
samples_bao_cosmosis = MCSamples(samples=[data[0]], weights=None, loglikes=-data[-1],
names=['Omega_m'], label='cosmosis')
g = plots.get_subplot_plotter()
g.triangle_plot([samples_bao_cobaya, samples_bao_desilike, samples_bao_cosmosis],
params=['Omega_m'], markers={'Omega_m': cosmo['Omega_m']})
LOADING CHAIN FROM FILE: _tests/chains_bao_cosmosis/chain.txt
MontePython¶
MontePython is not a Python package, so is not installed in the cosmodesi environment.
Let's install it locally! (it may take some time to download, because of the data sets).
In [30]:
%%bash
cd _tests/
git clone https://github.com/brinckmann/montepython_public.git
bash: /home/adematti/anaconda3/envs/cosmodesi/lib/libtinfo.so.6: no version information available (required by bash) Cloning into 'montepython_public'... Updating files: 100% (1492/1492), done.
We write the .conf file that specifies the path to the Boltzman code Class and Planck likelihoods.
In [31]:
%%file _tests/montepython_public/default.conf
import os
path['cosmo'] = os.getenv('CLASS_STD_DIR')
path['clik'] = os.path.join(os.getenv('PLANCK_SRC_DIR'), 'code', 'plc_3.0', 'plc-3.1')
Writing _tests/montepython_public/default.conf
Let's take a look at the files previously generated by the static bindings:
- the package:
BAOLikelihood - with a (mandatory)
*.datafile specifying the likelihood name and nuisance parameter priors - with
*.paramfile specifying parameter ranges, to be copy-pasted in the input.paramfile (see below) - with the
__init__.pyfile containing the likelihood definition
As required by MontePython, we copy all this to the montepython/likelihoods directory.
In [32]:
!ls -la _tests/montepython/BAOLikelihood
!cp -r _tests/montepython/BAOLikelihood _tests/montepython_public/montepython/likelihoods/
/bin/bash: /home/adematti/anaconda3/envs/cosmodesi/lib/libtinfo.so.6: no version information available (required by /bin/bash) total 20 drwxr-xr-x 2 adematti idphp 4096 juil. 2 10:25 . drwxr-xr-x 3 adematti idphp 4096 juil. 2 10:25 .. -rw-r--r-- 1 adematti idphp 35 juil. 2 10:25 BAOLikelihood.data -rw-r--r-- 1 adematti idphp 52 juil. 2 10:25 BAOLikelihood.param -rw-r--r-- 1 adematti idphp 502 juil. 2 10:25 __init__.py /bin/bash: /home/adematti/anaconda3/envs/cosmodesi/lib/libtinfo.so.6: no version information available (required by /bin/bash)
Now let's write the config file to run inference. This is pure MontePython.
In [33]:
%%file _tests/conf_bao.param
data.experiments = ['BAOLikelihood']
#------ Parameter list -------
# data.parameters[class name] = [mean, min, max, 1-sigma, scale, role]
# Cosmological parameters list
data.parameters['Omega_m'] = [0.3, 0.1, 0.9, 0.1, 1., 'cosmo']
# Fixed parameters
data.parameters['omega_b'] = [0.02237, 0.001, 0.1, 0., 1., 'cosmo']
data.parameters['H0'] = [67.36, 0.1, 0.9, 0., 1., 'cosmo']
data.parameters['A_s'] = [2.083e-09, 1e-09, 3e-09, 0., 1., 'cosmo']
data.parameters['n_s'] = [0.9649, 0.9, 1.0, 0., 1., 'cosmo']
data.parameters['tau_reio'] = [0.0544, 0.02, 0.1, 0., 1., 'cosmo']
# Cosmo arguments
data.cosmo_arguments['k_pivot'] = 0.05
data.cosmo_arguments['N_ur'] = 2.0328
data.cosmo_arguments['N_ncdm'] = 1
data.cosmo_arguments['m_ncdm'] = 0.06
data.cosmo_arguments['T_ncdm'] = 0.71611
#------ MCMC parameters ----
data.N = 3000
data.write_step = 5
Writing _tests/conf_bao.param
Let's sample!
In [34]:
!python _tests/montepython_public/montepython/MontePython.py run --conf _tests/montepython_public/default.conf -p _tests/conf_bao.param -o _tests/chains_bao_montepython
/bin/bash: /home/adematti/anaconda3/envs/cosmodesi/lib/libtinfo.so.6: no version information available (required by /bin/bash)
/!\ PyMultiNest detected but MultiNest likely not installed correctly. You can
safely ignore this if not running with option -m NS
Running Monte Python v3.6.0
with CLASS v3.2.0
Testing likelihoods for:
->BAOLikelihood
WARNING:absl:No GPU/TPU found, falling back to CPU. (Set TF_CPP_MIN_LOG_LEVEL=0 and rerun for more info.)
Creating _tests/chains_bao_montepython/2023-07-02_3000__1.txt
Deduced starting covariance matrix:
['Omega_m']
[[0.01]]
Update routine is enabled with value 50 (recommended: 50)
This number is rescaled by cycle length 1 (N_slow + f_fast * N_fast) to 50
# -LogLkl Omega_m
/!\ PyMultiNest detected but MultiNest likely not installed correctly. You can
safely ignore this if not running with option -m NS
1 0.474813 4.139400e-01
6 0.0393078 3.415106e-01
1 0.0795065 3.530712e-01
1 0.299953 3.918899e-01
1 0.28913 3.903726e-01
1 1.88732 5.363267e-01
3 1.75998 5.269886e-01
1 0.353307 2.459891e-01
1 0.00723461 3.045927e-01
2 0.156011 3.691783e-01
1 0.207845 2.610078e-01
1 0.743891 4.424003e-01
9 0.099125 2.769897e-01
1 1.45946e-05 3.148490e-01
5 0.390573 2.427618e-01
2 0.322765 3.950166e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 8 steps
/!\ Convergence computed for a single file
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.023861 for Omega_m
--> Not computing covariance matrix
3 0.00225593 3.092987e-01
/!\ PyMultiNest detected but MultiNest likely not installed correctly. You can
safely ignore this if not running with option -m NS
2 0.178771 3.732351e-01
2 1.05338 2.030995e-01
2 0.0636985 2.842953e-01
4 0.00297849 3.223716e-01
2 0.325495 2.485320e-01
1 0.692487 4.373065e-01
2 0.346225 3.981394e-01
1 1.82164 5.315325e-01
4 2.01188 5.452945e-01
1 3.12612 6.203877e-01
1 0.0593596 2.853300e-01
1 0.183125 3.739850e-01
2 0.0197739 2.977335e-01
9 0.133208 2.712282e-01
1 0.72976 4.410130e-01
1 0.458166 4.119994e-01
1 2.89561 1.464973e-01
1 0.025582 3.363208e-01
7 0.343765 2.468476e-01
1 0.34691 3.982291e-01
1 0.494095 4.161551e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 18 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.588647 for Omega_m
--> Computing covariance matrix
3 0.100762 2.766899e-01
1 0.188175 2.634665e-01
1 0.0875733 2.791871e-01
3 0.000951407 3.114031e-01
After 42 accepted steps: update proposal with max(R-1) = 0.588647 and jumping factor = 2.400000
3 1.25691 4.879438e-01
1 0.0289588 3.377001e-01
5 0.117842 2.737100e-01
3 0.468053 4.131552e-01
2 0.170546 2.657972e-01
4 0.181677 3.737364e-01
1 0.500153 4.168440e-01
1 0.586944 2.282463e-01
7 0.00574804 3.251461e-01
1 0.24628 3.841182e-01
4 1.13643 4.779182e-01
2 1.08646 2.016194e-01
1 0.364993 2.449561e-01
1 1.3481 4.953290e-01
1 0.129411 2.718260e-01
2 1.47855 5.056334e-01
1 2.73758 1.500770e-01
4 2.57229 5.840266e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 31 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.022824 for Omega_m
--> Not computing covariance matrix
3 3.5438 6.469228e-01
1 4.1455 6.841766e-01
3 3.76552 6.607680e-01
1 4.56484 7.096253e-01
5 0.00827158 3.271341e-01
2 0.501024 2.341626e-01
1 0.576046 4.252202e-01
1 0.317311 3.942774e-01
1 0.857011 2.125812e-01
1 0.256071 2.554962e-01
1 0.0980799 3.574608e-01
7 0.349695 3.985939e-01
3 0.0267513 3.368077e-01
4 1.1034 4.751108e-01
1 2.50396 5.794242e-01
1 5.05559 7.390040e-01
2 1.11115 4.757719e-01
3 0.369159 2.445927e-01
8 0.145495 2.693563e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 38 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.057315 for Omega_m
--> Not computing covariance matrix
3 0.312185 3.935780e-01
4 0.852413 4.527595e-01
1 0.358453 3.997328e-01
1 0.0515435 3.454487e-01
1 0.000254286 3.132960e-01
7 0.221287 3.802581e-01
1 0.786015 4.464814e-01
1 0.00922449 3.032265e-01
20 0.013582 3.305179e-01
10 0.571653 4.247473e-01
1 0.477118 4.142066e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 46 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.014075 for Omega_m
--> Not computing covariance matrix
4 0.183305 2.640975e-01
1 0.209575 2.607980e-01
1 0.356327 3.994574e-01
2 0.00308832 3.082821e-01
5 0.0821669 2.802700e-01
7 1.25136 1.946550e-01
1 0.00122202 3.108823e-01
2 1.47679 5.054965e-01
1 0.124357 3.630752e-01
6 2.48395 5.780714e-01
3 2.29763 5.653394e-01
1 1.95267 5.410507e-01
2 0.521699 4.192688e-01
7 0.451156 2.378865e-01
6 0.337461 2.474226e-01
1 0.0491255 3.447082e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 53 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.008688 for Omega_m
--> Not computing covariance matrix
5 0.0133081 3.303611e-01
1 0.012032 3.015364e-01
3 0.0910879 3.558566e-01
10 0.0807114 3.533692e-01
3 0.0107104 3.023033e-01
1 1.18699 4.821654e-01
1 0.721041 4.401523e-01
4 0.626034 4.305109e-01
1 0.27161 3.878657e-01
1 0.375147 4.018733e-01
1 0.132493 2.713401e-01
3 0.0113417 3.019312e-01
4 0.0607866 2.849854e-01
1 0.161704 3.702159e-01
1 6.98359e-07 3.153832e-01
4 0.204936 3.776317e-01
5 0.05585 2.861970e-01
2 0.0227956 3.351161e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 61 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.012612 for Omega_m
--> Not computing covariance matrix
4 0.000320701 3.130461e-01
3 0.439463 4.097857e-01
1 0.92247 4.592000e-01
2 0.172153 3.720798e-01
6 0.0789282 3.529274e-01
1 1.05787 2.028968e-01
7 0.151481 2.684763e-01
3 0.280092 3.890875e-01
7 0.323614 3.951311e-01
1 0.467371 4.130758e-01
1 0.39934 2.420294e-01
1 2.41574 5.734377e-01
2 1.35641 4.959945e-01
2 0.0100308 3.283481e-01
6 0.0257057 2.953291e-01
2 1.36662 1.901459e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 71 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.013018 for Omega_m
--> Not computing covariance matrix
2 0.807091 4.484939e-01
1 0.694389 4.374973e-01
4 0.146348 2.692298e-01
6 0.297834 3.915947e-01
1 0.0001866 3.170777e-01
5 0.209697 3.784055e-01
1 0.019251 2.979625e-01
2 0.15927 3.697743e-01
1 0.341062 3.974596e-01
2 0.0407708 2.903046e-01
3 0.988732 4.651398e-01
1 0.873229 4.546918e-01
1 1.22114 4.850004e-01
2 0.200939 3.769762e-01
1 0.050699 2.875244e-01
3 0.134565 3.651112e-01
7 0.0340365 2.924023e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 78 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.010444 for Omega_m
--> Not computing covariance matrix
10 0.00204349 3.095876e-01
4 0.325655 3.954061e-01
1 0.0650389 2.839835e-01
4 0.000180561 3.136159e-01
3 0.0223833 3.349320e-01
1 0.262539 3.865413e-01
2 0.345941 3.981021e-01
4 0.0595406 3.477901e-01
1 0.382878 2.434126e-01
5 1.32151 1.918790e-01
1 0.0442547 2.892916e-01
1 1.2614 1.942512e-01
3 1.78489 5.288293e-01
1 0.0753482 3.520266e-01
2 0.649254 2.242833e-01
1 0.309715 3.932392e-01
2 1.03558 4.692578e-01
1 0.0923101 3.561410e-01
4 0.138947 3.659642e-01
1 0.16861 2.660613e-01
2 0.350048 2.462807e-01
1 0.209048 2.608618e-01
3 0.0570426 2.858992e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 91 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.014294 for Omega_m
--> Not computing covariance matrix
1 1.3972 4.992421e-01
1 0.00125824 3.198919e-01
4 0.4439 4.103141e-01
2 0.262001 3.864621e-01
6 0.0181291 3.329285e-01
1 0.504431 4.173286e-01
4 0.839287 4.515325e-01
1 0.542182 2.312567e-01
2 0.0980431 3.574525e-01
2 2.72639 5.943039e-01
3 0.26165 3.864104e-01
1 0.551642 2.306081e-01
1 0.245633 2.566347e-01
1 0.354891 3.992710e-01
1 0.00279075 3.221441e-01
2 0.0587136 3.475550e-01
2 0.0849594 3.544041e-01
1 0.0491583 3.447184e-01
1 0.0148282 3.000466e-01
6 0.491544 4.158640e-01
2 0.33222 3.962859e-01
2 0.0432573 3.428373e-01
1 0.197561 2.622759e-01
1 0.647921 2.243656e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 101 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.012042 for Omega_m
--> Not computing covariance matrix
2 0.513264 4.183243e-01
2 0.181015 2.643975e-01
1 0.625637 4.304696e-01
2 0.0369121 2.914818e-01
1 0.147983 3.676866e-01
2 0.0180662 3.328973e-01
1 0.0252194 3.361677e-01
3 0.253706 2.557518e-01
2 0.46576 2.367712e-01
4 0.00408146 3.072383e-01
1 2.35757 5.694613e-01
1 0.596201 4.273733e-01
1 2.47329 5.773491e-01
3 2.36459 5.699424e-01
6 0.00751828 3.265761e-01
3 0.351308 3.988044e-01
2 0.0146861 3.311350e-01
4 0.0159122 2.995088e-01
3 0.0733397 3.515126e-01
3 1.01977 4.678749e-01
1 2.06882 1.671894e-01
1 3.13412 1.413653e-01
1 0.206706 3.779203e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 113 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.003573 for Omega_m
--> Not computing covariance matrix
3 1.18644 4.821194e-01
4 0.188993 2.633614e-01
2 0.0800009 2.807147e-01
4 0.0501528 3.450249e-01
1 0.844495 2.132314e-01
4 1.43926 5.025606e-01
4 2.70493 5.928809e-01
1 3.24256 6.278513e-01
1 1.91245 5.381489e-01
1 1.25135 4.874881e-01
4 0.427701 4.083747e-01
1 0.424557 2.399752e-01
1 0.77294 2.170724e-01
1 0.226588 3.810916e-01
1 0.1057 3.591515e-01
1 0.243631 3.837174e-01
2 0.388765 4.035911e-01
1 0.499568 2.342681e-01
1 0.14421 3.669733e-01
1 0.0014393 3.105053e-01
1 1.59888 1.817924e-01
3 3.62302 6.518870e-01
3 6.90786 8.475028e-01
1 5.86501 7.867665e-01
1 4.11186 6.821189e-01
2 1.54258 5.105893e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 126 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.012110 for Omega_m
--> Not computing covariance matrix
2 2.26425 5.630319e-01
2 1.30822 4.921189e-01
8 0.00751576 3.265742e-01
1 0.277417 3.887039e-01
5 0.523544 4.194746e-01
1 0.034429 3.397820e-01
1 0.114689 2.742411e-01
4 0.419521 2.403796e-01
5 2.05249 5.481861e-01
1 0.383385 2.433696e-01
1 0.314184 3.938514e-01
5 0.200438 2.619174e-01
4 0.613286 4.291772e-01
1 0.0614054 3.483147e-01
1 0.49288 2.347549e-01
1 7.18536e-05 3.142497e-01
1 0.360819 4.000386e-01
2 0.163498 2.667670e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 136 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.002955 for Omega_m
--> Not computing covariance matrix
9 0.029568 2.939182e-01
4 0.254147 3.852988e-01
1 0.494946 2.346040e-01
2 1.1046 4.752128e-01
2 1.34156 4.948048e-01
1 2.82246 6.006443e-01
3 2.52693 5.809749e-01
3 3.92687 6.707538e-01
2 0.719968 4.400461e-01
3 2.28468 1.612714e-01
4 0.130856 3.643796e-01
2 0.446371 2.382566e-01
2 0.0270846 3.369446e-01
1 1.35048 4.955198e-01
1 0.7865 4.465279e-01
6 0.896316 4.568163e-01
1 0.811587 4.489208e-01
5 0.0976615 3.573663e-01
1 0.00350047 3.078308e-01
1 0.260144 2.550592e-01
1 0.999515 2.055769e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 146 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.006254 for Omega_m
--> Not computing covariance matrix
5 0.786336 4.465122e-01
2 0.595072 2.277150e-01
3 0.342118 3.975991e-01
1 0.937114 4.605250e-01
1 0.823419 4.500402e-01
3 0.0897097 3.555339e-01
1 0.403261 2.417051e-01
1 0.149011 2.688371e-01
4 0.0237775 3.355482e-01
1 0.0709773 2.826418e-01
8 0.00111676 3.196262e-01
4 0.105656 2.758093e-01
1 0.105236 2.758840e-01
1 0.128951 2.718991e-01
2 1.26844 4.888870e-01
1 0.47164 4.135722e-01
1 0.0975079 3.573316e-01
2 0.388047 4.035011e-01
3 0.458669 2.373100e-01
1 0.556858 2.302534e-01
2 0.517735 4.188256e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 156 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.002632 for Omega_m
--> Not computing covariance matrix
10 0.4411 4.099810e-01
1 1.26001 1.943070e-01
1 1.22405 4.852409e-01
4 0.398659 4.048241e-01
2 0.0404754 3.419090e-01
1 0.00808812 3.039856e-01
2 0.462908 2.369872e-01
2 1.11761 4.763210e-01
2 2.08752 5.506684e-01
2 3.66558 6.545463e-01
1 1.34202 4.948415e-01
2 0.517139 4.187588e-01
2 0.259771 2.550991e-01
2 1.12777 4.771846e-01
5 0.0163229 2.993100e-01
1 3.101 6.187709e-01
1 2.28368 5.643761e-01
2 0.680392 4.360882e-01
3 0.00751917 3.043864e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 166 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.001434 for Omega_m
--> Not computing covariance matrix
10 0.0075292 3.043792e-01
1 2.76192 5.966550e-01
1 0.914857 4.585086e-01
1 0.00806588 3.269843e-01
1 0.192076 2.629676e-01
2 0.69958 4.380174e-01
2 1.44488 5.030014e-01
11 0.0172833 3.325043e-01
1 0.421314 4.076023e-01
1 0.0987157 2.770651e-01
1 0.537941 4.210713e-01
7 0.774483 4.453722e-01
1 1.9055 1.719697e-01
1 0.245642 2.566338e-01
1 0.498224 4.166250e-01
2 0.682567 4.363078e-01
3 0.711594 2.205497e-01
1 0.196399 3.762251e-01
2 0.117776 2.737210e-01
5 0.0466395 3.439291e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 176 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.002016 for Omega_m
--> Not computing covariance matrix
2 0.508603 2.336168e-01
2 0.570257 2.293514e-01
2 0.348892 2.463845e-01
1 0.395678 2.423342e-01
1 1.29402 4.909693e-01
3 1.12205 4.766986e-01
1 2.16659 5.562321e-01
5 0.188586 3.749147e-01
7 0.111062 3.603086e-01
6 0.030132 3.381613e-01
5 0.0230212 3.352162e-01
5 1.23766 1.952094e-01
4 0.00277572 3.086453e-01
5 0.351776 3.988656e-01
1 0.816069 4.493454e-01
1 0.603415 4.281373e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 183 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.002785 for Omega_m
--> Not computing covariance matrix
1 0.776958 4.456107e-01
5 0.37336 4.016460e-01
1 1.19235 4.826120e-01
1 1.09345 4.742592e-01
1 5.53162 7.671793e-01
1 0.405279 4.056423e-01
1 0.156564 2.677443e-01
7 0.224149 3.807091e-01
2 0.198556 3.765828e-01
1 0.00469089 3.241871e-01
1 0.240375 3.832218e-01
2 4.77555 7.222868e-01
1 0.327396 3.956401e-01
5 0.00412346 3.236284e-01
2 1.44871 5.033016e-01
2 0.424143 4.079450e-01
3 3.81524 6.638524e-01
5 0.127442 3.636981e-01
6 0.617053 4.295724e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 193 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.005483 for Omega_m
--> Not computing covariance matrix
6 0.653698 4.333708e-01
3 0.752894 4.432794e-01
1 4.91985 7.309147e-01
1 4.5912 7.112135e-01
1 4.42611 7.012458e-01
1 4.23959 6.899186e-01
1 4.8337 7.257677e-01
2 2.13213 5.538138e-01
5 0.0117547 3.016935e-01
2 1.24867 4.872684e-01
3 0.0474251 2.884061e-01
1 0.339824 2.472063e-01
1 1.03037 2.041473e-01
2 0.460249 2.371895e-01
1 0.203203 2.615757e-01
1 0.887963 4.560499e-01
1 0.917637 2.095151e-01
2 0.0141659 3.003853e-01
1 1.00072 4.662000e-01
1 2.0052 5.448179e-01
4 0.0112167 3.291087e-01
2 0.108154 2.753685e-01
3 2.1695e-05 3.147404e-01
1 3.11629 6.197556e-01
1 1.52218 5.090173e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 206 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.002215 for Omega_m
--> Not computing covariance matrix
7 0.203942 3.774691e-01
2 0.233189 2.580292e-01
9 0.0163438 3.320212e-01
2 0.0968059 2.774191e-01
5 0.428725 2.396429e-01
2 0.360754 4.000302e-01
4 1.70509 1.782511e-01
4 0.687794 2.219497e-01
4 0.0452537 3.434864e-01
3 0.197286 3.763724e-01
1 0.397479 4.046777e-01
2 0.232068 3.819447e-01
1 1.27041 1.938909e-01
2 0.0150196 3.313170e-01
1 0.0141672 3.308479e-01
2 0.75807 4.437830e-01
2 0.269964 3.876268e-01
1 0.570635 2.293262e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 216 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.001961 for Omega_m
--> Not computing covariance matrix
7 0.539663 4.212611e-01
2 0.649545 4.329443e-01
3 0.00163021 3.205271e-01
1 0.0900658 3.556175e-01
2 0.872713 2.117740e-01
1 1.83671 5.326370e-01
2 0.668862 4.349193e-01
2 1.02095 4.679784e-01
1 0.383577 4.029396e-01
1 0.0156544 2.996350e-01
1 0.333283 2.478072e-01
1 0.39869 4.048280e-01
1 1.09513 4.744030e-01
2 0.752792 4.432694e-01
3 0.133339 2.712077e-01
3 1.35051 4.955224e-01
1 1.39073 4.987287e-01
2 0.728477 4.408866e-01
2 0.611484 4.289878e-01
4 0.119169 2.734889e-01
4 0.0145101 3.310382e-01
2 0.116449 3.614463e-01
1 1.04116 2.036541e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 226 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.001718 for Omega_m
--> Not computing covariance matrix
4 0.283013 2.526765e-01
1 0.160367 2.672054e-01
1 0.484066 4.150072e-01
2 0.166189 2.663940e-01
1 0.401829 2.418234e-01
2 0.187649 2.635341e-01
1 1.28474 4.902151e-01
1 1.78847 1.755776e-01
1 0.0264516 2.950484e-01
1 0.284722 3.897480e-01
2 0.134574 2.710154e-01
1 2.89332 1.465481e-01
1 1.75971 5.269689e-01
1 1.66519 5.199151e-01
3 0.778512 2.167655e-01
3 0.15017 3.680964e-01
4 0.493265 4.160605e-01
1 1.01481 4.674402e-01
2 1.78427 1.757102e-01
3 0.575363 4.251468e-01
3 0.403042 2.417231e-01
2 0.0249811 3.360665e-01
5 0.38543 4.031726e-01
1 0.441805 4.100649e-01
2 0.977813 2.065997e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 238 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.005638 for Omega_m
--> Not computing covariance matrix
5 0.272451 3.879875e-01
3 0.105242 2.758829e-01
2 0.35021 2.462662e-01
1 0.0644234 3.491485e-01
1 0.859044 2.124761e-01
1 1.2312 1.954722e-01
1 0.211289 2.605911e-01
1 0.065296 2.839240e-01
3 0.0228044 3.351200e-01
2 0.0471449 2.884831e-01
1 0.0856935 2.795594e-01
2 0.124526 2.726096e-01
2 0.0738789 2.820083e-01
1 0.127072 2.721991e-01
3 0.00132006 3.107084e-01
6 0.157086 3.693754e-01
4 0.00995749 3.282997e-01
1 1.00883 4.669147e-01
2 0.0286103 2.942586e-01
10 0.364148 2.450302e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 248 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.008176 for Omega_m
--> Not computing covariance matrix
8 0.254939 2.556184e-01
1 0.0816166 2.803824e-01
2 0.014372 3.309618e-01
4 0.0849833 3.544098e-01
1 0.0642192 3.490928e-01
1 1.0754 4.727093e-01
1 0.504085 4.172895e-01
1 0.0981403 3.574745e-01
2 2.1483 5.549494e-01
1 0.127738 2.720924e-01
1 0.174966 3.725731e-01
4 0.338054 3.970618e-01
2 1.34311 4.949293e-01
1 2.7658 5.969110e-01
3 3.77924 6.616199e-01
3 3.5434 6.468974e-01
1 3.42058 6.391611e-01
1 0.941397 4.609111e-01
2 1.19273 4.826435e-01
1 0.154451 3.688911e-01
1 0.582787 4.259434e-01
2 0.722639 4.403103e-01
4 0.0758062 3.521429e-01
2 0.17061 3.718078e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 261 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.011500 for Omega_m
--> Not computing covariance matrix
3 0.0234621 2.962004e-01
1 1.57602 1.825761e-01
2 1.65856 5.194159e-01
2 1.32299 4.933116e-01
4 1.11826 4.763770e-01
2 0.180835 3.735916e-01
10 0.997893 2.056528e-01
3 0.00140772 3.105582e-01
1 2.14716 5.548701e-01
1 1.83325 5.323833e-01
3 2.04793 5.478620e-01
1 0.778838 4.457918e-01
4 0.669752 4.350098e-01
7 0.264359 2.546112e-01
1 0.213677 2.603045e-01
3 0.00496009 3.064189e-01
1 2.57671 5.843235e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 268 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.010806 for Omega_m
--> Not computing covariance matrix
6 1.1216 4.766606e-01
2 0.641362 4.321011e-01
3 0.00511521 3.245836e-01
1 0.355426 3.993405e-01
13 0.0259752 3.364857e-01
1 0.362495 4.002547e-01
8 0.120067 3.621975e-01
12 2.17598e-05 3.147396e-01
2 0.555249 4.229691e-01
2 0.22865 3.814138e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 273 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.010034 for Omega_m
--> Not computing covariance matrix
2 0.690802 4.371373e-01
1 0.126787 2.722448e-01
4 0.584171 4.260915e-01
1 0.00244828 3.217088e-01
5 0.677325 4.357780e-01
2 0.610494 4.288837e-01
4 0.71438 2.203878e-01
5 0.072036 2.824091e-01
2 0.313858 3.938068e-01
7 0.671158 2.229467e-01
1 0.261529 2.549116e-01
2 0.56816 4.243704e-01
2 0.194709 2.626342e-01
1 0.174827 2.652191e-01
2 0.486034 2.352573e-01
2 0.390921 4.038608e-01
4 0.401944 4.052308e-01
1 0.0340844 3.396556e-01
3 0.049118 2.879462e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 283 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.014493 for Omega_m
--> Not computing covariance matrix
3 0.231344 3.818326e-01
1 0.28055 2.529275e-01
1 0.63823 4.317774e-01
2 0.180386 2.644803e-01
1 0.0428224 2.897027e-01
2 0.0918531 2.783555e-01
4 0.16646 3.710707e-01
4 0.604514 2.271033e-01
3 0.975859 4.639967e-01
3 0.488541 4.155205e-01
1 0.432385 2.393526e-01
1 0.0820321 2.802975e-01
1 0.0819229 3.536668e-01
4 0.0080921 3.039829e-01
1 5.99784e-05 3.163163e-01
1 0.000710996 3.119333e-01
2 0.0752792 2.817075e-01
5 0.637574 4.317095e-01
1 0.444651 4.104033e-01
2 0.574466 2.290709e-01
1 0.427594 4.083617e-01
3 0.0493273 3.447707e-01
3 0.0238615 2.960422e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 296 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.012596 for Omega_m
--> Not computing covariance matrix
1 0.13082 3.643725e-01
3 0.0834025 2.800192e-01
3 2.02929 5.465362e-01
4 0.735836 4.416107e-01
1 1.881 5.358670e-01
6 0.00831282 3.271639e-01
5 0.00818463 3.039191e-01
2 0.319395 2.491067e-01
1 0.5905 4.267672e-01
1 0.265024 3.869060e-01
3 0.421209 2.402437e-01
6 0.420132 2.403303e-01
1 0.784703 2.164259e-01
2 0.0306036 3.383442e-01
2 0.368371 2.446612e-01
2 1.13545 4.778347e-01
1 0.315901 2.494388e-01
2 0.301911 3.921619e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 303 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.009642 for Omega_m
--> Not computing covariance matrix
5 0.860161 2.124185e-01
7 1.19555 4.828782e-01
3 0.447636 2.381585e-01
1 0.573903 4.249897e-01
5 0.115843 2.740457e-01
5 0.20136 3.770455e-01
3 1.25111 4.874682e-01
1 0.00234534 3.215722e-01
4 0.624055 4.303045e-01
1 0.373214 4.016274e-01
1 3.02819 1.436064e-01
2 0.674731 4.355152e-01
2 0.303496 3.923816e-01
3 0.928913 4.597838e-01
2 3.12428 6.202693e-01
3 3.03516 6.145185e-01
1 0.00583687 3.252226e-01
4 0.325603 3.953991e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 313 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.008670 for Omega_m
--> Not computing covariance matrix
2 1.09129 4.740742e-01
2 2.49164 5.785913e-01
1 5.57029 1.014163e-01
1 0.779307 2.167217e-01
1 0.630936 4.310210e-01
3 0.894469 4.566470e-01
7 0.178239 3.731429e-01
1 0.0104888 3.286467e-01
4 0.0785083 2.810250e-01
2 1.09894 4.747291e-01
3 1.11633 4.762122e-01
2 0.0612469 2.848751e-01
2 0.150767 3.682077e-01
1 0.190845 2.631244e-01
5 0.194011 2.627223e-01
1 0.416163 2.406507e-01
2 0.0254246 3.362544e-01
1 0.0830982 3.539537e-01
1 0.0455604 2.889230e-01
1 0.197756 2.622515e-01
7 0.150393 3.681380e-01
1 0.0940731 2.779325e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 323 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.009038 for Omega_m
--> Not computing covariance matrix
2 0.5898 2.280590e-01
4 0.414169 2.408124e-01
1 0.113705 2.744086e-01
2 0.0273826 3.370663e-01
1 0.281006 2.528810e-01
8 0.115307 3.612070e-01
3 0.0164922 3.320983e-01
2 0.286358 2.523374e-01
1 0.0872726 3.549578e-01
1 0.31414 3.938454e-01
1 0.0142068 3.308699e-01
2 0.145358 3.671911e-01
2 0.941177 4.608913e-01
1 0.106518 3.593299e-01
2 0.405674 4.056909e-01
3 0.0202212 3.339389e-01
2 4.04071e-05 3.161374e-01
1 0.00644329 3.257303e-01
1 0.00858483 3.273588e-01
5 0.497873 2.343910e-01
1 0.44339 4.102535e-01
2 0.901485 4.572892e-01
2 0.0629134 3.487337e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 336 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.011267 for Omega_m
--> Not computing covariance matrix
6 0.668258 4.348580e-01
4 0.000948626 3.192877e-01
3 0.0185938 3.331576e-01
2 0.911329 4.581875e-01
1 0.919847 2.094058e-01
3 0.303446 3.923747e-01
1 0.140602 3.662832e-01
1 0.0534381 2.868100e-01
1 0.16088 3.700667e-01
3 0.0571129 2.858818e-01
5 0.090623 3.557480e-01
1 1.07515 2.021221e-01
2 0.421422 4.076154e-01
2 0.229756 2.584213e-01
3 0.934478 2.086869e-01
1 1.20726 1.964543e-01
3 0.0932904 3.563678e-01
1 0.175563 2.651206e-01
7 0.31415 3.938466e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 346 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.008590 for Omega_m
--> Not computing covariance matrix
1 0.465492 4.128567e-01
4 0.0283262 2.943607e-01
1 0.183777 3.740967e-01
2 0.368168 4.009832e-01
1 1.03281 4.690158e-01
3 0.128103 2.720342e-01
5 0.0137038 3.305872e-01
3 0.335778 3.967597e-01
1 0.323749 2.486958e-01
1 0.465998 4.129158e-01
5 1.30602 4.919408e-01
1 1.41379 5.005548e-01
2 1.72051 5.240572e-01
3 2.18994 5.578650e-01
1 1.25356 4.876695e-01
1 3.2571 6.287792e-01
1 0.218132 3.797580e-01
1 0.0684429 3.502317e-01
3 0.127718 3.637533e-01
1 1.28881 4.905460e-01
2 0.0560583 3.467895e-01
1 2.07727 5.499431e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 356 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.006510 for Omega_m
--> Not computing covariance matrix
7 3.13474 6.209421e-01
5 1.66049 5.195610e-01
3 0.462587 2.370117e-01
1 0.0995947 2.769034e-01
5 0.433004 4.090127e-01
1 1.14183 4.783741e-01
1 0.110517 3.601922e-01
8 0.0993437 3.577452e-01
10 0.116871 2.738727e-01
2 0.120385 2.732873e-01
4 1.7163 5.237431e-01
3 0.114876 3.611166e-01
1 0.0428087 2.897067e-01
2 0.0132367 3.303201e-01
1 1.2643 4.885484e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 363 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.002030 for Omega_m
--> Not computing covariance matrix
7 0.130033 3.642160e-01
3 0.0662502 3.496446e-01
6 0.0801564 3.532322e-01
4 0.465617 2.367819e-01
4 0.0795637 3.530854e-01
1 1.54466 1.836637e-01
2 1.07243 4.724532e-01
1 0.308439 3.930638e-01
4 2.04741 5.478251e-01
1 1.80031 1.752051e-01
5 0.0182989 2.983882e-01
6 0.00607355 3.054809e-01
2 0.129833 2.717590e-01
1 0.0890242 3.553726e-01
2 1.87099 5.351387e-01
2 0.656417 4.336494e-01
1 0.206007 3.778063e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 373 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.004113 for Omega_m
--> Not computing covariance matrix
1 0.331682 2.479553e-01
5 0.135645 3.653227e-01
3 0.0821387 2.802757e-01
1 0.0467547 2.885907e-01
1 1.7498 5.262347e-01
2 1.58179 5.135944e-01
2 0.763527 4.443127e-01
5 0.0108054 3.288496e-01
2 0.320195 2.490309e-01
1 0.534776 2.317695e-01
1 0.154379 2.680573e-01
1 0.487653 2.351381e-01
3 0.43481 4.092292e-01
6 0.0170889 3.324054e-01
6 0.281224 3.892494e-01
7 0.573374 4.249327e-01
2 0.145123 3.671465e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 381 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.002988 for Omega_m
--> Not computing covariance matrix
3 0.137601 2.705482e-01
4 0.00220777 3.093629e-01
6 0.0198201 3.337493e-01
1 0.545607 4.219147e-01
2 1.67666 1.791837e-01
5 0.0735498 3.515666e-01
2 2.37094 5.703774e-01
1 0.0155316 2.996954e-01
2 1.05048 4.705541e-01
1 0.0112235 3.020000e-01
2 0.754084 2.181221e-01
1 0.104255 3.588352e-01
2 0.159515 2.673256e-01
1 0.44587 4.105481e-01
3 0.269978 3.876287e-01
5 0.554114 4.228454e-01
2 0.562443 4.237514e-01
1 0.0668302 3.498007e-01
2 0.0173124 3.325190e-01
1 0.280876 3.891996e-01
1 0.126283 3.634649e-01
1 0.748312 2.184466e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 391 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.002874 for Omega_m
--> Not computing covariance matrix
8 0.731079 4.411429e-01
1 0.269192 2.541025e-01
1 0.503442 4.172167e-01
3 0.787248 4.465996e-01
2 0.687458 2.219697e-01
3 0.670163 2.230068e-01
2 0.0857064 3.545836e-01
6 0.198487 2.621601e-01
2 0.3873 4.034075e-01
1 0.34943 3.985591e-01
1 1.02077 4.679633e-01
2 3.81475 6.638224e-01
1 2.96657 6.100672e-01
1 2.00352 5.446980e-01
4 1.9375 5.399581e-01
1 0.344665 3.979344e-01
1 0.261843 3.864389e-01
1 0.305474 2.504430e-01
2 0.331521 3.961926e-01
3 1.57403 5.130008e-01
5 1.70954 1.781063e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 403 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.004318 for Omega_m
--> Not computing covariance matrix
2 1.29215 4.908169e-01
1 0.58245 2.285420e-01
3 0.0017443 3.100218e-01
1 0.0413529 3.422051e-01
6 0.0511629 3.453332e-01
2 3.23798 1.392241e-01
1 0.242497 3.835451e-01
6 0.0994406 3.577670e-01
2 0.456155 2.375022e-01
1 0.468812 2.365407e-01
1 0.0114305 3.018797e-01
1 0.128661 3.639423e-01
2 0.0596081 3.478092e-01
1 0.24293 3.836108e-01
5 0.0131393 3.302638e-01
2 0.617032 4.295701e-01
3 0.34826 3.984061e-01
2 0.251526 3.849072e-01
4 1.69938 5.224798e-01
1 0.0526227 3.457739e-01
1 0.67346 2.228078e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 413 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.006751 for Omega_m
--> Not computing covariance matrix
9 0.115315 3.612088e-01
1 1.32245 4.932675e-01
1 0.582808 4.259457e-01
3 1.48312 5.059889e-01
1 3.43485 6.400628e-01
1 3.14482 6.215901e-01
2 4.19877 6.874300e-01
1 5.38113 7.583013e-01
1 2.38908 5.716183e-01
2 0.919221 2.094368e-01
1 2.59749 5.857166e-01
8 2.51344 5.800647e-01
3 2.32901 5.675002e-01
1 1.0945 4.743497e-01
1 1.11783 4.763399e-01
2 0.503651 4.172405e-01
1 0.26536 3.869551e-01
2 0.677797 4.358258e-01
1 0.292696 2.517014e-01
4 0.22839 2.585783e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 423 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.005784 for Omega_m
--> Not computing covariance matrix
9 0.0359682 3.403391e-01
8 0.146831 3.674697e-01
1 0.0167309 3.322218e-01
1 0.122388 3.626739e-01
2 1.55208 1.834048e-01
2 1.95988 5.415696e-01
1 1.67199 5.204262e-01
3 1.54238 5.105736e-01
11 1.10816 2.006643e-01
6 0.275355 3.884070e-01
5 0.43189 4.088788e-01
1 0.162076 2.669656e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 428 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.008281 for Omega_m
--> Not computing covariance matrix
9 0.479777 2.357203e-01
5 0.169749 2.659057e-01
1 1.4048 4.998442e-01
2 0.952808 4.619370e-01
4 2.88661 6.048514e-01
1 2.44045 1.572497e-01
1 2.37634 5.707470e-01
1 1.72424 5.243352e-01
1 0.0268611 3.368529e-01
1 0.0793999 2.808393e-01
1 0.702353 2.210897e-01
1 0.0615876 3.483656e-01
2 0.400983 4.051119e-01
1 2.38156 5.711043e-01
8 0.0247191 2.957071e-01
4 0.242821 3.835943e-01
1 0.198833 3.766287e-01
2 0.894487 2.106700e-01
6 0.0198596 3.337680e-01
2 0.119403 3.620603e-01
1 1.17735 4.813600e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 438 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.010329 for Omega_m
--> Not computing covariance matrix
4 0.307056 2.502893e-01
1 0.605516 2.270388e-01
3 0.384945 4.031117e-01
2 0.495602 4.163268e-01
1 0.303019 2.506824e-01
5 0.0923693 3.561547e-01
1 0.0471375 2.884851e-01
2 0.232756 2.580784e-01
2 0.853 4.528142e-01
1 1.40472 4.998377e-01
4 0.658924 4.339060e-01
1 0.000580033 3.184206e-01
2 0.00382833 3.233229e-01
1 0.165991 2.664213e-01
5 0.179423 3.733479e-01
2 0.302488 2.507343e-01
3 3.60477e-06 3.151040e-01
2 0.0324616 3.390526e-01
2 0.00464023 3.067079e-01
2 0.162871 3.704268e-01
1 0.917294 4.587301e-01
1 0.304034 2.505832e-01
2 0.00736796 3.044955e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 451 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.007599 for Omega_m
--> Not computing covariance matrix
3 1.52834 5.094927e-01
1 0.934907 4.603257e-01
1 0.572071 4.247924e-01
1 1.78599 5.289109e-01
3 1.19849 4.831227e-01
1 1.56336 5.121842e-01
3 0.937709 4.605787e-01
9 0.000838413 3.190494e-01
1 0.138221 2.704534e-01
2 0.236844 2.576153e-01
7 0.0130188 3.009920e-01
2 1.51052 5.081157e-01
3 1.16498 4.803241e-01
4 0.000385819 3.128255e-01
2 1.98179 1.697017e-01
2 0.0775845 2.812187e-01
2 0.260869 2.549818e-01
4 0.39911 2.420486e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 461 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.005235 for Omega_m
--> Not computing covariance matrix
8 0.00300775 3.224065e-01
1 0.106084 3.592354e-01
1 0.280308 3.891183e-01
1 0.942164 4.609802e-01
2 1.52762 5.094367e-01
4 2.68023 1.514142e-01
2 0.00359212 3.230699e-01
1 0.921958 4.591536e-01
1 1.10115 4.749185e-01
1 1.22876 4.856303e-01
1 1.2502 4.873934e-01
2 0.836476 4.512689e-01
3 0.00878121 3.274976e-01
4 1.79017 5.292190e-01
1 1.71237 5.234502e-01
9 0.0371894 2.913951e-01
3 0.340138 2.471776e-01
4 0.11043 3.601736e-01
2 0.000304383 3.131049e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 468 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.003889 for Omega_m
--> Not computing covariance matrix
5 0.00338899 3.079501e-01
1 1.08684 2.016025e-01
1 1.43827 5.024822e-01
10 0.195391 2.625482e-01
1 0.273632 3.881584e-01
3 0.427459 4.083455e-01
2 0.115041 3.611513e-01
6 0.113097 2.745125e-01
1 1.45504 1.868585e-01
2 2.19999 1.635424e-01
1 2.20634 1.633700e-01
1 1.49985 1.852446e-01
1 2.60425 5.861692e-01
1 0.00737727 3.044888e-01
2 0.0358705 3.403041e-01
1 0.357224 2.456406e-01
4 0.0395208 3.415837e-01
1 0.111476 3.603970e-01
2 0.151554 3.683543e-01
2 0.694104 2.215755e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 478 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.002684 for Omega_m
--> Not computing covariance matrix
3 0.64408 4.323817e-01
1 1.10285 4.750631e-01
2 0.0333957 3.394014e-01
2 0.413021 2.409057e-01
2 0.895893 4.567775e-01
1 1.09501 4.743933e-01
5 0.12251 2.729379e-01
3 0.101596 2.765382e-01
7 0.679611 4.360092e-01
2 0.0357243 3.402516e-01
2 0.925251 2.091394e-01
1 0.0187263 3.332224e-01
2 2.90194 6.058532e-01
1 3.49017 6.435509e-01
2 4.66406 7.155971e-01
1 4.20397 6.877473e-01
1 2.1506 5.551110e-01
3 1.8069 5.304500e-01
7 1.64515 1.802302e-01
1 1.42441 5.013925e-01
1 0.813194 4.490732e-01
2 0.0775374 3.525797e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 491 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.004434 for Omega_m
--> Not computing covariance matrix
2 1.4476 5.032147e-01
1 1.81098 5.307495e-01
3 0.140515 3.662665e-01
1 0.205218 2.613282e-01
4 0.589396 4.266495e-01
1 1.42799 5.016742e-01
6 0.683212 4.363730e-01
3 0.0685717 3.502659e-01
2 0.264307 3.868009e-01
1 0.818835 4.496072e-01
2 0.0371768 2.913991e-01
3 0.0532811 3.459709e-01
4 0.018617 3.331690e-01
1 0.829924 4.506532e-01
3 0.431234 4.088001e-01
3 0.296483 2.513251e-01
2 0.0203049 3.339784e-01
7 0.374578 4.018009e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 498 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.003649 for Omega_m
--> Not computing covariance matrix
2 1.077 4.728465e-01
4 0.414521 4.067756e-01
2 0.541349 4.214468e-01
2 0.0980107 3.574452e-01
2 1.76335 5.272383e-01
1 3.44083 6.404402e-01
1 5.45746 7.628078e-01
1 1.0348 4.691896e-01
1 1.87161 5.351840e-01
3 0.0649464 3.492912e-01
5 0.0124647 3.298684e-01
5 0.0194306 2.978835e-01
2 0.00115955 3.109969e-01
4 0.00228907 3.092549e-01
6 0.203383 2.615535e-01
3 0.0105547 3.286892e-01
1 1.08176 4.732561e-01
2 0.702222 4.382815e-01
1 1.07344 4.725406e-01
2 0.0286823 2.942328e-01
1 0.0252595 3.361847e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 511 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.003773 for Omega_m
--> Not computing covariance matrix
6 0.00499602 3.244739e-01
6 1.058 4.712063e-01
8 0.490426 4.157362e-01
2 0.772179 4.451498e-01
1 0.815441 4.492860e-01
2 1.07426 4.726107e-01
1 0.0177695 2.986299e-01
3 0.0157034 2.996108e-01
3 0.386164 2.431338e-01
1 0.085912 3.546329e-01
4 0.156666 3.692986e-01
12 0.400505 2.419329e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 516 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.004775 for Omega_m
--> Not computing covariance matrix
3 0.120531 2.732632e-01
12 0.082575 2.801870e-01
2 1.51428 1.847319e-01
1 0.00943874 3.030889e-01
3 0.109892 2.750652e-01
4 0.216629 3.795185e-01
3 0.0479672 2.882579e-01
7 0.000341208 3.176972e-01
2 0.0793434 2.808510e-01
1 0.0600703 3.479399e-01
2 0.296537 2.513197e-01
2 0.00878936 3.035112e-01
3 0.139406 3.660528e-01
5 0.0575374 3.472179e-01
1 1.09924 2.010555e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 523 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.004581 for Omega_m
--> Not computing covariance matrix
6 0.0273034 3.370341e-01
2 0.374546 4.017969e-01
8 0.141772 2.699139e-01
3 0.014852 3.000346e-01
2 0.194952 2.626035e-01
4 0.00183966 3.098796e-01
5 0.00691739 3.261112e-01
1 2.41611 5.734631e-01
1 1.97824 5.428876e-01
2 0.523484 2.325595e-01
2 0.00897309 3.033901e-01
2 0.0358546 3.402984e-01
1 0.609963 4.288279e-01
1 3.13402 6.208961e-01
4 1.55202 5.113144e-01
2 0.0123548 3.013558e-01
2 0.00645652 3.051790e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 531 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.005869 for Omega_m
--> Not computing covariance matrix
3 0.5985 4.276173e-01
10 0.0115618 3.018040e-01
1 0.684264 4.364791e-01
1 0.216791 2.599337e-01
6 0.0745113 3.518131e-01
2 1.25098 4.874579e-01
1 0.977941 4.641819e-01
1 0.105146 3.590306e-01
2 0.0201561 3.339082e-01
3 0.296564 2.513171e-01
2 0.562181 2.298935e-01
2 0.357682 3.996330e-01
3 0.513694 2.332530e-01
4 0.12072 3.623319e-01
4 0.00038331 3.128336e-01
5 0.00368985 3.076325e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 541 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.007463 for Omega_m
--> Not computing covariance matrix
4 0.116429 2.739470e-01
1 0.596283 2.276362e-01
7 0.144677 3.670619e-01
1 1.01821 4.677383e-01
3 0.818706 4.495949e-01
1 0.224195 3.807163e-01
4 0.018923 3.333182e-01
1 0.545388 2.310361e-01
2 0.0253506 3.362232e-01
4 0.0350048 2.920879e-01
3 0.0561575 3.468184e-01
1 0.229616 3.815642e-01
5 0.0228616 3.351454e-01
1 0.136693 2.706879e-01
1 0.772559 2.170935e-01
4 6.78781e-07 3.153802e-01
2 0.441783 4.100623e-01
1 1.21985 4.848945e-01
1 0.868752 4.542775e-01
1 0.174562 3.725027e-01
2 0.088581 3.552680e-01
2 0.0742501 3.517463e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 551 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.007356 for Omega_m
--> Not computing covariance matrix
2 0.0140685 3.307927e-01
1 0.00613099 3.054351e-01
2 1.43594 1.875567e-01
7 1.13189 1.996340e-01
4 0.842933 4.518740e-01
1 1.63176 5.173929e-01
2 0.793423 4.471910e-01
2 0.122004 2.730209e-01
1 0.0506104 2.875478e-01
1 0.063921 3.490110e-01
2 1.0412 4.697478e-01
1 0.000314596 3.130679e-01
1 0.286251 3.899651e-01
9 0.0775613 3.525857e-01
2 0.14138 2.699731e-01
2 0.131202 2.715428e-01
3 0.0181569 2.984527e-01
4 0.0397953 3.416776e-01
1 0.588454 4.265490e-01
1 2.49827 1.558050e-01
1 1.82749 1.743563e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 561 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.006406 for Omega_m
--> Not computing covariance matrix
2 0.642496 4.322183e-01
2 0.75453 4.434387e-01
2 0.399641 4.049458e-01
2 0.857096 4.531957e-01
2 0.058389 3.474623e-01
5 0.0489642 2.879876e-01
2 0.155678 2.678710e-01
1 0.141765 2.699150e-01
1 0.0660037 3.495780e-01
1 0.302457 3.922377e-01
1 1.14725 4.788316e-01
1 0.50452 2.339103e-01
2 0.917801 2.095070e-01
2 1.45908 1.867116e-01
2 0.993072 2.058790e-01
1 0.059357 3.477380e-01
2 0.72432 2.198132e-01
3 0.124134 3.630299e-01
1 0.0430428 3.427668e-01
1 1.56904 1.828168e-01
1 0.162437 3.703485e-01
1 0.0786251 2.810006e-01
1 0.806386 2.152500e-01
3 0.0215012 2.969984e-01
4 0.305939 3.927193e-01
1 0.487892 4.154463e-01
1 0.954268 4.620681e-01
1 1.03476 4.691864e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 576 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.006838 for Omega_m
--> Not computing covariance matrix
2 2.69051 5.919231e-01
3 0.0633151 2.843853e-01
5 0.349059 2.463696e-01
1 1.31343 4.925399e-01
1 0.165954 2.664264e-01
5 0.439925 2.387591e-01
1 3.21182 6.258860e-01
1 4.02895 6.770359e-01
3 7.03578 8.549145e-01
1 0.19679 3.762899e-01
2 0.836012 2.136756e-01
1 0.0287384 3.376125e-01
1 0.0102042 3.284619e-01
2 0.123004 3.627997e-01
5 0.0130527 3.009737e-01
4 0.0400986 2.905053e-01
3 0.0707835 2.826846e-01
1 1.37445 4.974348e-01
1 0.781505 4.460483e-01
1 1.49503 5.069149e-01
1 2.04118 5.473820e-01
4 0.0446105 2.891906e-01
--> Scanning file _tests/chains_bao_montepython/2023-07-02_3000__1.txt: Removed 0 points of burn-in, and first 50 percent, keep 586 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.004496 for Omega_m
--> Not computing covariance matrix
6 0.213286 3.789837e-01
1 0.150674 3.681904e-01
1 1.77324 5.279693e-01
2 0.304324 3.924961e-01
1 0.697734 4.378327e-01
1 0.740844 2.188690e-01
1 1.47314 1.862023e-01
# 3000 steps done, acceptance rate: 0.393
Traceback (most recent call last):
File "classy.pyx", line 208, in classy.Class.struct_cleanup
TypeError: argument of type 'NoneType' is not iterable
Exception ignored in: 'classy.Class.__dealloc__'
Traceback (most recent call last):
File "classy.pyx", line 208, in classy.Class.struct_cleanup
TypeError: argument of type 'NoneType' is not iterable
In [35]:
# To load MontePython samples from disk
from datetime import date
from getdist.mcsamples import loadMCSamples
samples_bao_montepython = loadMCSamples('_tests/chains_bao_montepython/{}_3000_'.format(date.today()),
settings={'ignore_rows': 0.5}).copy(label='montepython')
g = plots.get_subplot_plotter()
g.triangle_plot([samples_bao_cobaya, samples_bao_desilike, samples_bao_cosmosis, samples_bao_montepython],
params=['Omega_m'], markers={'Omega_m': cosmo['Omega_m']})
[000600.65] [0/1] 07-02 10:32 root WARNING outlier fraction 0.09491525423728814
Interlude: forecasts¶
So far we have input totally ad-hoc covariance matrices. Yet, one can use desilike to produce forecasts.
In [36]:
from desilike.observables.galaxy_clustering import CutskyFootprint
from desilike.theories.galaxy_clustering import BAOPowerSpectrumTemplate, SimpleBAOWigglesTracerPowerSpectrumMultipoles
from desilike.likelihoods.galaxy_clustering import SNWeightedPowerSpectrumLikelihood
from desilike import Fisher
cosmo = DESI()
# Object holding the area and n(z) in (Mpc/h)^(-3)
footprint = CutskyFootprint(area=14000., zrange=np.linspace(0.8, 1.2, 10), nbar=np.full(10, 1e-4), cosmo=cosmo)
z = footprint.zavg
fo = cosmo.get_fourier()
s, s0 = fo.sigma8_z(z, of='delta_cb'), fo.sigma8_z(0., of='delta_cb')
b1 = 0.8 / (s / s0) # prescription for linear bias
r = 0.5 # reconstruction factor
sigmaper = 9.4 * (s / 0.9)
f = fo.sigma8_z(z, of='theta_cb') / s
params = {'b1': b1, 'sigmapar': r * (1. + f) * sigmaper, 'sigmaper': r * sigmaper} # fiducial model parameters
covariance_params = {'b1': b1, 'sigmapar': 0., 'sigmaper': 0.} # fiducial covariance parameters (simple Kaiser model)
template = BAOPowerSpectrumTemplate(z=z, fiducial='DESI', apmode='qparqper')
theory = SimpleBAOWigglesTracerPowerSpectrumMultipoles(template=template) # this BAO model shifts wiggles only
for param in theory.init.params.select(basename='al*'):
param.update(value=0., fixed=True) # fixing broadband parameters (the wiggles only shift)
# For klim=(0.01, 0.5), we only use the information from the BAO feature in the power spectrum
likelihood = SNWeightedPowerSpectrumLikelihood(theories=theory, data=params, covariance=covariance_params,
footprints=footprint, klim=(0.01, 0.5))
fisher = Fisher(likelihood) # initializing Fisher
fisher_bao = fisher(**params).view(params=['qpar', 'qper']) # computing Fisher prediction at fiducial parameters
[000601.78] [0/1] 07-02 10:32 Differentiation INFO Varied parameters: ['qpar', 'qper', 'b1', 'sigmas']. [000601.83] [0/1] 07-02 10:32 Differentiation INFO Varied parameters: ['qpar', 'qper', 'b1', 'sigmas']. [000602.13] [0/1] 07-02 10:32 Differentiation INFO Using finite-differentiation for parameter qpar. [000602.20] [0/1] 07-02 10:32 Differentiation INFO Using finite-differentiation for parameter qper. [000602.59] [0/1] 07-02 10:32 Differentiation INFO Using auto-differentiation for parameter b1. [000602.80] [0/1] 07-02 10:32 Differentiation INFO Using auto-differentiation for parameter sigmas. [000602.80] [0/1] 07-02 10:32 Differentiation INFO qpar grid is [0.998 1. 1.002]. [000602.80] [0/1] 07-02 10:32 Differentiation INFO qper grid is [0.998 1. 1.002].
In [37]:
print(fisher_bao.to_stats(tablefmt='pretty'))
+-----+---------+ | FoM | 3601.51 | +-----+---------+ +------+-------+-------+ | | qpar | qper | +------+-------+-------+ | mean | 1.000 | 1.000 | | std | 0.019 | 0.016 | +------+-------+-------+ +------+---------+---------+ | | qpar | qper | +------+---------+---------+ | qpar | 3.6e-4 | -1.3e-4 | | qper | -1.3e-4 | 2.6e-4 | +------+---------+---------+
In [38]:
# You can directly pass Fisher to BAOCompressionObservable
observable = BAOCompressionObservable(data=fisher_bao, covariance=fisher_bao,
quantities=['qpar', 'qper'], z=z)
# Or...
quantities = ['qpar', 'qper']
observable = BAOCompressionObservable(data=fisher_bao.mean(quantities), covariance=fisher_bao.covariance(quantities),
quantities=quantities, z=z)
This observable can be passed to a likelihood, just as previously, to further run cosmological inference.
ShapeFit likelihood¶
ShapeFit compressed likelihoods are similar to BAO compressed likelihoods.
In [39]:
from desilike.observables.galaxy_clustering import ShapeFitCompressionObservable
observable = ShapeFitCompressionObservable(data=[1., 1., 1., 0.], covariance=np.diag([0.01, 0.01, 0.01, 0.01]),
quantities=['qpar', 'qper', 'df', 'dm'], z=1.)
# Let's define the likelihood from this observable
likelihood = ObservablesGaussianLikelihood(observable)
This observable can be passed to a likelihood, just as previously, to further run cosmological inference.
Full likelihoods¶
Let's write full likelihoods, i.e. with nuisance parameters (bias, stochastic and counterterms not marginalized out).
In [40]:
%%file _tests/fs_likelihood.py
dirname = '_tests'
def FSLikelihood(cosmo='external'):
from desilike.theories.galaxy_clustering import DirectPowerSpectrumTemplate, KaiserTracerPowerSpectrumMultipoles, LPTVelocileptorsTracerPowerSpectrumMultipoles
from desilike.observables.galaxy_clustering import BoxFootprint, ObservablesCovarianceMatrix, TracerPowerSpectrumMultipolesObservable
from desilike.likelihoods import ObservablesGaussianLikelihood
# Let's define the template = linear power spectrum
template = DirectPowerSpectrumTemplate(z=1.)
# For the sake of running time, let us consider a simple linear Kaiser model
theory = KaiserTracerPowerSpectrumMultipoles(template=template)
b1 = 0.5
footprint = BoxFootprint(volume=5e9, nbar=1e-4) # box with volume of 5 (Gpc/h)^3 and density of 1e-4 (h/Mpc)^3
observable = TracerPowerSpectrumMultipolesObservable(\
data={'b1': b1}, # path to data, *pypower* file, array, or dictionary of parameters
covariance=None, # path to mocks, array (covariance matrix), or None
klim={0: [0.01, 0.2, 0.01], 2: [0.01, 0.2, 0.01]}, # k-limits, between 0.01 and 0.2 h/Mpc with 0.005 h/Mpc
theory=theory) # previously defined theory
covariance = ObservablesCovarianceMatrix(observables=[observable], footprints=[footprint])
cov = covariance(b1=b1) # evaluate covariance matrix at this parameter
likelihood = ObservablesGaussianLikelihood(observables=observable, covariance=cov)
observable.init.update(data=observable.flatdata) # fix the data vector
template.init.update(cosmo=cosmo) # let's pass the cosmology
return likelihood
if __name__ == '__main__':
from desilike.bindings import CobayaLikelihoodGenerator, CosmoSISLikelihoodGenerator, MontePythonLikelihoodGenerator
CobayaLikelihoodGenerator(dirname=dirname)([FSLikelihood], kw_like={'cosmo': 'external'})
CosmoSISLikelihoodGenerator(dirname=dirname)([FSLikelihood], kw_like={'cosmo': 'external'})
MontePythonLikelihoodGenerator(dirname=dirname)([FSLikelihood], kw_like={'cosmo': 'external'})
Writing _tests/fs_likelihood.py
Let's generate the static bindings by calling the above Python script
In [41]:
!python _tests/fs_likelihood.py
/bin/bash: /home/adematti/anaconda3/envs/cosmodesi/lib/libtinfo.so.6: no version information available (required by /bin/bash) WARNING:absl:No GPU/TPU found, falling back to CPU. (Set TF_CPP_MIN_LOG_LEVEL=0 and rerun for more info.) /home/adematti/anaconda3/envs/cosmodesi/lib/python3.9/site-packages/numpy/lib/polynomial.py:1337: FutureWarning: In the future extra properties will not be copied across when constructing one poly1d from another other = poly1d(other) WARNING:CosmoSISLikelihoodGenerator:Unbounded prior for parameter sn0; setting to 5-sigma = -50000000.00000001 WARNING:CosmoSISLikelihoodGenerator:Unbounded prior for parameter sn0; setting to 5-sigma = 49999999.99970176
In [42]:
!ls -la _tests/cobaya
/bin/bash: /home/adematti/anaconda3/envs/cosmodesi/lib/libtinfo.so.6: no version information available (required by /bin/bash) total 32 drwxr-xr-x 3 adematti idphp 4096 juil. 2 10:32 . drwxr-xr-x 10 adematti idphp 4096 juil. 2 10:32 .. -rw-r--r-- 1 adematti idphp 477 juil. 2 10:25 bao_likelihood.py -rw-r--r-- 1 adematti idphp 31 juil. 2 10:25 BAOLikelihood.yaml -rw-r--r-- 1 adematti idphp 471 juil. 2 10:32 fs_likelihood.py -rw-r--r-- 1 adematti idphp 411 juil. 2 10:32 FSLikelihood.yaml -rw-r--r-- 1 adematti idphp 59 juil. 2 10:32 __init__.py drwxr-xr-x 2 adematti idphp 4096 juil. 2 10:24 __pycache__
In [43]:
!ls -la _tests/cosmosis
/bin/bash: /home/adematti/anaconda3/envs/cosmodesi/lib/libtinfo.so.6: no version information available (required by /bin/bash) total 36 drwxr-xr-x 3 adematti idphp 4096 juil. 2 10:32 . drwxr-xr-x 10 adematti idphp 4096 juil. 2 10:32 .. -rw-r--r-- 1 adematti idphp 7 juil. 2 10:25 BAOLikelihood_priors.ini -rw-r--r-- 1 adematti idphp 543 juil. 2 10:25 BAOLikelihood.py -rw-r--r-- 1 adematti idphp 7 juil. 2 10:25 BAOLikelihood_values.ini -rw-r--r-- 1 adematti idphp 110 juil. 2 10:32 FSLikelihood_priors.ini -rw-r--r-- 1 adematti idphp 536 juil. 2 10:32 FSLikelihood.py -rw-r--r-- 1 adematti idphp 101 juil. 2 10:32 FSLikelihood_values.ini drwxr-xr-x 2 adematti idphp 4096 juil. 2 10:25 __pycache__
In [63]:
!ls -la _tests/montepython
/bin/bash: /home/adematti/anaconda3/envs/cosmodesi/lib/libtinfo.so.6: no version information available (required by /bin/bash) total 16 drwxr-xr-x 4 adematti idphp 4096 juil. 2 10:32 . drwxr-xr-x 13 adematti idphp 4096 juil. 2 10:39 .. drwxr-xr-x 2 adematti idphp 4096 juil. 2 10:25 BAOLikelihood drwxr-xr-x 2 adematti idphp 4096 juil. 2 10:32 FSLikelihood
Yet, the above likelihood will take a significant time to evaluate, especially for a 1-loop EFT model. Let's emulate the theory.
In [45]:
likelihood = FSLikelihood(cosmo=None)
theory = likelihood.observables[0].wmatrix.theory
from desilike.emulators import Emulator, TaylorEmulatorEngine, EmulatedCalculator
emulator = Emulator(theory.pt,
engine=TaylorEmulatorEngine(order={'*': 1}))
emulator.set_samples()
emulator.fit() # set Taylor expansion
# Emulator can be saved with:
emulator.save('_tests/emulator.npy')
np.save('_tests/data.npy', likelihood.flatdata)
np.save('_tests/covariance.npy', likelihood.covariance)
theory.init.update(pt=emulator)
[000626.19] [0/1] 07-02 10:32 Emulator INFO Varied parameters: ['h', 'Omega_m', 'omega_b', 'logA']. [000626.19] [0/1] 07-02 10:32 Emulator INFO Found varying ['pk_dd', 'pk_dt', 'pk_tt', 'pk11'] and fixed ['k', 'z', 'ells', 'names'] outputs. [000626.71] [0/1] 07-02 10:32 Differentiation INFO Varied parameters: ['h', 'Omega_m', 'omega_b', 'logA']. [000629.76] [0/1] 07-02 10:33 Differentiation INFO Using finite-differentiation for parameter h. [000630.37] [0/1] 07-02 10:33 Differentiation INFO Using finite-differentiation for parameter Omega_m. [000630.91] [0/1] 07-02 10:33 Differentiation INFO Using finite-differentiation for parameter omega_b. [000631.44] [0/1] 07-02 10:33 Differentiation INFO Using finite-differentiation for parameter logA. [000631.44] [0/1] 07-02 10:33 Differentiation INFO h grid is [0.6706 0.6736 0.6766]. [000631.44] [0/1] 07-02 10:33 Differentiation INFO Omega_m grid is [0.31019172 0.31519172 0.32019172]. [000631.44] [0/1] 07-02 10:33 Differentiation INFO omega_b grid is [0.02227 0.02237 0.02247]. [000631.44] [0/1] 07-02 10:33 Differentiation INFO logA grid is [3.03499426 3.03639426 3.03779426]. [000636.56] [0/1] 07-02 10:33 Emulator INFO Saving _tests/emulator.npy. [000636.56] [0/1] 07-02 10:33 BaseConfig INFO Saving _tests/emulator.yaml.
Now we can write our likelihood, using the emulated PT!
In [46]:
%%file _tests/fs_likelihood.py
dirname = '_tests'
def FSLikelihood():
import os
import numpy as np
from desilike.theories.galaxy_clustering import DirectPowerSpectrumTemplate
from desilike.observables.galaxy_clustering import TracerPowerSpectrumMultipolesObservable
from desilike.likelihoods import ObservablesGaussianLikelihood
from desilike.emulators import EmulatedCalculator
# Let's define the template
template = DirectPowerSpectrumTemplate(z=1.)
# For the sake of running time, let us consider a simple linear Kaiser model
theory = KaiserTracerPowerSpectrumMultipoles(template=template, pt=EmulatedCalculator.load(os.path.join(dirname, 'emulator.npy')))
observable = TracerPowerSpectrumMultipolesObservable(\
data=np.load(os.path.join(dirname, 'data.npy')), # path to data, *pypower* file, array, or dictionary of parameters
klim={0: [0.01, 0.2, 0.01], 2: [0.01, 0.2, 0.01]}, # k-limits, between 0.01 and 0.2 h/Mpc with 0.005 h/Mpc
theory=theory,
covariance=np.load(os.path.join(dirname, 'covariance.npy')))
likelihood = ObservablesGaussianLikelihood(observables=observable)
likelihood.all_params['sn0'].update(derived='.auto')
return likelihood
if __name__ == '__main__':
from desilike.bindings import CobayaLikelihoodGenerator, CosmoSISLikelihoodGenerator, MontePythonLikelihoodGenerator
CobayaLikelihoodGenerator(dirname=dirname)(FSLikelihood, kw_like={})
CosmoSISLikelihoodGenerator(dirname=dirname)(FSLikelihood, kw_like={})
MontePythonLikelihoodGenerator(dirname=dirname)(FSLikelihood, kw_like={})
Overwriting _tests/fs_likelihood.py
Let's generate the static bindings by calling the above Python script
In [47]:
!python _tests/fs_likelihood.py
/bin/bash: /home/adematti/anaconda3/envs/cosmodesi/lib/libtinfo.so.6: no version information available (required by /bin/bash) WARNING:absl:No GPU/TPU found, falling back to CPU. (Set TF_CPP_MIN_LOG_LEVEL=0 and rerun for more info.)
Cobaya¶
In [48]:
%%file _tests/config_bao_fs.yaml
theory:
classy:
extra_args:
N_ncdm: 1
N_ur: 2.0328
likelihood:
bao_likelihood.BAOLikelihood:
python_path: _tests/cobaya
fs_likelihood.FSLikelihood:
python_path: _tests/cobaya
params:
Omega_m:
prior:
min: 0.1
max: 1.
ref:
dist: norm
loc: 0.3
scale: 0.01
latex: \Omega_{m}
omega_b: 0.02237
H0: 67.36
As: 2.083e-09
n_s: 0.9649
tau_reio: 0.0544
sampler:
mcmc:
Rminus1_stop: 0.05
debug: True
output: _tests/chains_bao_fs_cobaya/chain
Writing _tests/config_bao_fs.yaml
Let's sample!
In [49]:
!cobaya-run _tests/config_bao_fs.yaml
/bin/bash: /home/adematti/anaconda3/envs/cosmodesi/lib/libtinfo.so.6: no version information available (required by /bin/bash)
2023-07-02 10:33:11,778 [output] Creating output folder '_tests/chains_bao_fs_cobaya'
2023-07-02 10:33:11,778 [output] Output to be read-from/written-into folder '_tests/chains_bao_fs_cobaya', with prefix 'chain'
2023-07-02 10:33:14,016 [root] Initializing MLIR with module: _mlirRegisterEverything
2023-07-02 10:33:14,016 [root] Registering dialects from initializer <module 'jaxlib.mlir._mlir_libs._mlirRegisterEverything' from '/home/adematti/anaconda3/envs/cosmodesi/lib/python3.9/site-packages/jaxlib/mlir/_mlir_libs/_mlirRegisterEverything.so'>
2023-07-02 10:33:14,171 [absl] Finished tracing + transforming prim_fun for jit in 0.0002155303955078125 sec
2023-07-02 10:33:14,171 [absl] Initializing backend 'interpreter'
2023-07-02 10:33:14,172 [absl] Backend 'interpreter' initialized
2023-07-02 10:33:14,172 [absl] Initializing backend 'cpu'
2023-07-02 10:33:14,173 [absl] Backend 'cpu' initialized
2023-07-02 10:33:14,173 [absl] Initializing backend 'tpu_driver'
2023-07-02 10:33:14,173 [absl] Unable to initialize backend 'tpu_driver': NOT_FOUND: Unable to find driver in registry given worker:
2023-07-02 10:33:14,173 [absl] Initializing backend 'cuda'
2023-07-02 10:33:14,173 [absl] Unable to initialize backend 'cuda': module 'jaxlib.xla_extension' has no attribute 'GpuAllocatorConfig'
2023-07-02 10:33:14,173 [absl] Initializing backend 'rocm'
2023-07-02 10:33:14,173 [absl] Unable to initialize backend 'rocm': module 'jaxlib.xla_extension' has no attribute 'GpuAllocatorConfig'
2023-07-02 10:33:14,173 [absl] Initializing backend 'tpu'
2023-07-02 10:33:14,174 [absl] Unable to initialize backend 'tpu': INVALID_ARGUMENT: TpuPlatform is not available.
2023-07-02 10:33:14,174 [absl] *WARNING* No GPU/TPU found, falling back to CPU. (Set TF_CPP_MIN_LOG_LEVEL=0 and rerun for more info.)
2023-07-02 10:33:14,174 [absl] Compiling prim_fun (140345258472048 for args (ShapedArray(int64[]),).
2023-07-02 10:33:14,185 [absl] Finished XLA compilation of convert_element_type in 0.007681846618652344 sec
2023-07-02 10:33:14,444 [classy] Attempting global import (no `path` or Cobaya installation path given).
2023-07-02 10:33:14,446 [classy] `classy` module loaded successfully from /home/adematti/anaconda3/envs/cosmodesi/lib/python3.9/site-packages/classy-3.2.0-py3.9-linux-x86_64.egg
2023-07-02 10:33:14,503 [BAOCompressionObservable] Found quantities ['qpar', 'qper'].
2023-07-02 10:33:14,551 [BAOCompressionObservable] Found quantities ['qiso'].
2023-07-02 10:33:14,745 [Emulator] Loading _tests/emulator.npy.
2023-07-02 10:33:14,750 [absl] Finished tracing + transforming prim_fun for jit in 0.00023412704467773438 sec
2023-07-02 10:33:14,750 [absl] Finished tracing + transforming <lambda> for jit in 0.0002548694610595703 sec
2023-07-02 10:33:14,751 [absl] Compiling <lambda> (140345237477792 for args (ShapedArray(float64[4]), ShapedArray(float64[4])).
2023-07-02 10:33:14,760 [absl] Finished XLA compilation of <lambda> in 0.0066030025482177734 sec
2023-07-02 10:33:14,761 [absl] Finished tracing + transforming prim_fun for jit in 0.0001995563507080078 sec
2023-07-02 10:33:14,761 [absl] Compiling prim_fun (140345237696320 for args (ShapedArray(float64[4]),).
2023-07-02 10:33:14,769 [absl] Finished XLA compilation of copy in 0.005262851715087891 sec
2023-07-02 10:33:14,771 [absl] Finished tracing + transforming _power for jit in 0.0007116794586181641 sec
2023-07-02 10:33:14,771 [absl] Compiling _power (140345279968496 for args (ShapedArray(float64[4]), ShapedArray(int32[5,4])).
2023-07-02 10:33:14,782 [absl] Finished XLA compilation of _power in 0.00912618637084961 sec
2023-07-02 10:33:14,784 [absl] Finished tracing + transforming _where for jit in 0.0010313987731933594 sec
2023-07-02 10:33:14,784 [absl] Compiling _where (140345279969216 for args (ShapedArray(bool[5,4]), ShapedArray(float64[5,4]), ShapedArray(float64[], weak_type=True)).
2023-07-02 10:33:14,795 [absl] Finished XLA compilation of _where in 0.00801229476928711 sec
2023-07-02 10:33:14,796 [absl] Finished tracing + transforming _reduce_prod for jit in 0.0004315376281738281 sec
2023-07-02 10:33:14,796 [absl] Compiling _reduce_prod (140345279968336 for args (ShapedArray(float64[5,4]),).
2023-07-02 10:33:14,807 [absl] Finished XLA compilation of _reduce_prod in 0.008159160614013672 sec
2023-07-02 10:33:14,808 [absl] Finished tracing + transforming prim_fun for jit in 0.00019240379333496094 sec
2023-07-02 10:33:14,809 [absl] Finished tracing + transforming prim_fun for jit in 0.0002732276916503906 sec
2023-07-02 10:33:14,809 [absl] Compiling prim_fun (140345279968896 for args (ShapedArray(float64[5,38]), ShapedArray(float64[5])).
2023-07-02 10:33:14,823 [absl] Finished XLA compilation of dot_general in 0.011621475219726562 sec
2023-07-02 10:33:14,824 [absl] Finished tracing + transforming prim_fun for jit in 0.00026917457580566406 sec
2023-07-02 10:33:14,824 [absl] Compiling prim_fun (140345279969696 for args (ShapedArray(float64[38]),).
2023-07-02 10:33:14,832 [absl] Finished XLA compilation of reshape in 0.0055561065673828125 sec
2023-07-02 10:33:14,946 [model] Parameters were assigned as follows:
2023-07-02 10:33:14,946 [model] - bao_likelihood.BAOLikelihood:
2023-07-02 10:33:14,946 [model] Input: []
2023-07-02 10:33:14,946 [model] Output: []
2023-07-02 10:33:14,946 [model] - fs_likelihood.FSLikelihood:
2023-07-02 10:33:14,946 [model] Input: ['b1', 'sigmapar', 'sigmaper']
2023-07-02 10:33:14,946 [model] Output: []
2023-07-02 10:33:14,946 [model] - classy:
2023-07-02 10:33:14,946 [model] Input: ['Omega_m', 'omega_b', 'H0', 'As', 'n_s', 'tau_reio']
2023-07-02 10:33:14,946 [model] Output: []
2023-07-02 10:33:14,948 [model] Components will be computed in the order:
2023-07-02 10:33:14,948 [model] - [classy, bao_likelihood.BAOLikelihood, fs_likelihood.FSLikelihood]
2023-07-02 10:33:14,948 [model] Requirements will be calculated by these components:
2023-07-02 10:33:14,948 [model] - rdrag: classy
2023-07-02 10:33:14,949 [model] - Hubble: classy
2023-07-02 10:33:14,949 [model] - angular_diameter_distance: classy
2023-07-02 10:33:14,967 [mcmc] Initializing
2023-07-02 10:33:14,971 [mcmc] Getting initial point... (this may take a few seconds)
2023-07-02 10:33:14,971 [prior] Evaluating prior at array([0.28996824, 1.63228392])
2023-07-02 10:33:14,971 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:14,972 [model] Posterior to be computed for parameters {'Omega_m': 0.2899682376349314, 'b1': 1.6322839223318795}
2023-07-02 10:33:14,972 [prior] Evaluating prior at array([0.28996824, 1.63228392])
2023-07-02 10:33:14,972 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:14,972 [model] Got input parameters: {'Omega_m': 0.2899682376349314, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.6322839223318795, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:14,972 [classy] Got parameters {'Omega_m': 0.2899682376349314, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:14,972 [classy] Computing new state
2023-07-02 10:33:14,972 [classy] Setting parameters: {'Omega_m': 0.2899682376349314, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:15,043 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.05941093030333}
2023-07-02 10:33:15,043 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:15,044 [absl] Finished tracing + transforming prim_fun for jit in 0.00022792816162109375 sec
2023-07-02 10:33:15,045 [absl] Finished tracing + transforming prim_fun for jit in 0.00015974044799804688 sec
2023-07-02 10:33:15,045 [absl] Finished tracing + transforming prim_fun for jit in 0.00018644332885742188 sec
2023-07-02 10:33:15,045 [absl] Compiling prim_fun (140344366076848 for args (ShapedArray(float64[2]), ShapedArray(float64[1])).
2023-07-02 10:33:15,054 [absl] Finished XLA compilation of concatenate in 0.006158351898193359 sec
2023-07-02 10:33:15,055 [absl] Finished tracing + transforming <lambda> for jit in 0.0003414154052734375 sec
2023-07-02 10:33:15,056 [absl] Compiling <lambda> (140344366077168 for args (ShapedArray(float64[3]), ShapedArray(float64[3])).
2023-07-02 10:33:15,065 [absl] Finished XLA compilation of <lambda> in 0.007318973541259766 sec
2023-07-02 10:33:15,067 [absl] Finished tracing + transforming dot for jit in 0.00047278404235839844 sec
2023-07-02 10:33:15,067 [absl] Compiling dot (140344366077408 for args (ShapedArray(float64[3]), ShapedArray(float64[3,3])).
2023-07-02 10:33:15,081 [absl] Finished XLA compilation of dot in 0.010323524475097656 sec
2023-07-02 10:33:15,082 [absl] Finished tracing + transforming dot for jit in 0.0004627704620361328 sec
2023-07-02 10:33:15,082 [absl] Compiling dot (140344366077168 for args (ShapedArray(float64[3]), ShapedArray(float64[3])).
2023-07-02 10:33:15,093 [absl] Finished XLA compilation of dot in 0.008072137832641602 sec
2023-07-02 10:33:15,094 [absl] Finished tracing + transforming fn for jit in 0.00041294097900390625 sec
2023-07-02 10:33:15,095 [absl] Compiling fn (140344366077008 for args (ShapedArray(float64[], weak_type=True), ShapedArray(float64[])).
2023-07-02 10:33:15,103 [absl] Finished XLA compilation of fn in 0.005791187286376953 sec
2023-07-02 10:33:15,105 [absl] Finished tracing + transforming fn for jit in 0.0004019737243652344 sec
2023-07-02 10:33:15,105 [absl] Compiling fn (140344366077408 for args (ShapedArray(float64[]), ShapedArray(float64[], weak_type=True)).
2023-07-02 10:33:15,113 [absl] Finished XLA compilation of fn in 0.005861043930053711 sec
2023-07-02 10:33:15,115 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0331218
2023-07-02 10:33:15,115 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.6322839223318795, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:15,115 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:15,136 [absl] Finished tracing + transforming fn for jit in 0.00031185150146484375 sec
2023-07-02 10:33:15,136 [absl] Compiling fn (140344366079328 for args (ShapedArray(float64[]), ShapedArray(float64[2,19])).
2023-07-02 10:33:15,148 [absl] Finished XLA compilation of fn in 0.008717060089111328 sec
2023-07-02 10:33:15,149 [absl] Finished tracing + transforming fn for jit in 0.0003635883331298828 sec
2023-07-02 10:33:15,150 [absl] Compiling fn (140344366078208 for args (ShapedArray(float64[2,19]), ShapedArray(float64[2,19])).
2023-07-02 10:33:15,161 [absl] Finished XLA compilation of fn in 0.008719205856323242 sec
2023-07-02 10:33:15,162 [absl] Finished tracing + transforming fn for jit in 0.00034308433532714844 sec
2023-07-02 10:33:15,163 [absl] Compiling fn (140344366077328 for args (ShapedArray(float64[2,19]), ShapedArray(float64[2,1])).
2023-07-02 10:33:15,174 [absl] Finished XLA compilation of fn in 0.008681535720825195 sec
2023-07-02 10:33:15,175 [absl] Finished tracing + transforming ravel for jit in 0.0003216266632080078 sec
2023-07-02 10:33:15,176 [absl] Compiling ravel (140344366077168 for args (ShapedArray(float64[2,19]),).
2023-07-02 10:33:15,184 [absl] Finished XLA compilation of ravel in 0.005652427673339844 sec
2023-07-02 10:33:15,185 [absl] Finished tracing + transforming <lambda> for jit in 0.00035071372985839844 sec
2023-07-02 10:33:15,185 [absl] Compiling <lambda> (140344366078688 for args (ShapedArray(float64[38]), ShapedArray(float64[38])).
2023-07-02 10:33:15,195 [absl] Finished XLA compilation of <lambda> in 0.007729291915893555 sec
2023-07-02 10:33:15,197 [absl] Finished tracing + transforming dot for jit in 0.0004360675811767578 sec
2023-07-02 10:33:15,197 [absl] Compiling dot (140344366077168 for args (ShapedArray(float64[38]), ShapedArray(float64[38,38])).
2023-07-02 10:33:15,224 [absl] Finished XLA compilation of dot in 0.024365901947021484 sec
2023-07-02 10:33:15,226 [absl] Finished tracing + transforming dot for jit in 0.00043487548828125 sec
2023-07-02 10:33:15,226 [absl] Compiling dot (140344366077168 for args (ShapedArray(float64[38]), ShapedArray(float64[38])).
2023-07-02 10:33:15,241 [absl] Finished XLA compilation of dot in 0.012979745864868164 sec
2023-07-02 10:33:15,243 [absl] Finished tracing + transforming prim_fun for jit in 0.00019621849060058594 sec
2023-07-02 10:33:15,243 [absl] Compiling prim_fun (140344366078688 for args (ShapedArray(float64[]),).
2023-07-02 10:33:15,251 [absl] Finished XLA compilation of convert_element_type in 0.0054781436920166016 sec
2023-07-02 10:33:15,252 [absl] Finished tracing + transforming prim_fun for jit in 0.00020360946655273438 sec
2023-07-02 10:33:15,253 [absl] Finished tracing + transforming prim_fun for jit in 0.0001926422119140625 sec
2023-07-02 10:33:15,253 [absl] Compiling prim_fun (140344366078448 for args (ShapedArray(float64[], weak_type=True), ShapedArray(float64[], weak_type=True)).
2023-07-02 10:33:15,261 [absl] Finished XLA compilation of gt in 0.005736351013183594 sec
2023-07-02 10:33:15,263 [absl] Finished tracing + transforming prim_fun for jit in 0.000308990478515625 sec
2023-07-02 10:33:15,263 [absl] Compiling prim_fun (140344366078448 for args (ShapedArray(float64[], weak_type=True), ShapedArray(float64[], weak_type=True)).
2023-07-02 10:33:15,271 [absl] Finished XLA compilation of lt in 0.0058135986328125 sec
2023-07-02 10:33:15,273 [absl] Finished tracing + transforming <lambda> for jit in 0.00043010711669921875 sec
2023-07-02 10:33:15,273 [absl] Compiling <lambda> (140344366140208 for args (ShapedArray(bool[], weak_type=True), ShapedArray(bool[], weak_type=True)).
2023-07-02 10:33:15,282 [absl] Finished XLA compilation of <lambda> in 0.005909442901611328 sec
2023-07-02 10:33:15,284 [absl] Finished tracing + transforming _where for jit in 0.0005702972412109375 sec
2023-07-02 10:33:15,284 [absl] Compiling _where (140344366138608 for args (ShapedArray(bool[]), ShapedArray(int64[], weak_type=True), ShapedArray(float64[], weak_type=True)).
2023-07-02 10:33:15,293 [absl] Finished XLA compilation of _where in 0.006242990493774414 sec
2023-07-02 10:33:15,294 [absl] Finished tracing + transforming fn for jit in 0.0003616809844970703 sec
2023-07-02 10:33:15,294 [absl] Compiling fn (140344366138608 for args (ShapedArray(float64[], weak_type=True), ShapedArray(float64[], weak_type=True)).
2023-07-02 10:33:15,303 [absl] Finished XLA compilation of fn in 0.005687713623046875 sec
2023-07-02 10:33:15,305 [absl] Finished tracing + transforming prim_fun for jit in 0.0001952648162841797 sec
2023-07-02 10:33:15,306 [absl] Finished tracing + transforming prim_fun for jit in 0.00014662742614746094 sec
2023-07-02 10:33:15,306 [absl] Compiling prim_fun (140344366140848 for args (ShapedArray(float64[], weak_type=True),).
2023-07-02 10:33:15,314 [absl] Finished XLA compilation of convert_element_type in 0.0054814815521240234 sec
2023-07-02 10:33:15,315 [absl] Finished tracing + transforming prim_fun for jit in 0.00024247169494628906 sec
2023-07-02 10:33:15,315 [absl] Compiling prim_fun (140344366139568 for args (ShapedArray(float64[]), ShapedArray(float64[])).
2023-07-02 10:33:15,323 [absl] Finished XLA compilation of gt in 0.005784273147583008 sec
2023-07-02 10:33:15,324 [absl] Finished tracing + transforming prim_fun for jit in 0.00024390220642089844 sec
2023-07-02 10:33:15,325 [absl] Compiling prim_fun (140344366139008 for args (ShapedArray(float64[]), ShapedArray(float64[])).
2023-07-02 10:33:15,333 [absl] Finished XLA compilation of lt in 0.00564265251159668 sec
2023-07-02 10:33:15,334 [absl] Finished tracing + transforming <lambda> for jit in 0.0003275871276855469 sec
2023-07-02 10:33:15,334 [absl] Compiling <lambda> (140344365712224 for args (ShapedArray(bool[]), ShapedArray(bool[])).
2023-07-02 10:33:15,342 [absl] Finished XLA compilation of <lambda> in 0.005549430847167969 sec
2023-07-02 10:33:15,350 [Differentiation] Varied parameters: ['sn0'].
2023-07-02 10:33:15,351 [Differentiation] Varied parameters: ['sn0'].
2023-07-02 10:33:15,352 [absl] Finished tracing + transforming prim_fun for jit in 0.0001964569091796875 sec
2023-07-02 10:33:15,352 [absl] Compiling prim_fun (140344365712544 for args ().
2023-07-02 10:33:15,360 [absl] Finished XLA compilation of iota in 0.005384683609008789 sec
2023-07-02 10:33:15,361 [absl] Finished tracing + transforming prim_fun for jit in 0.00026345252990722656 sec
2023-07-02 10:33:15,361 [absl] Compiling prim_fun (140344365712784 for args (ShapedArray(int32[1,1]), ShapedArray(int32[])).
2023-07-02 10:33:15,370 [absl] Finished XLA compilation of add in 0.006165981292724609 sec
2023-07-02 10:33:15,371 [absl] Finished tracing + transforming prim_fun for jit in 0.00022459030151367188 sec
2023-07-02 10:33:15,371 [absl] Compiling prim_fun (140344365712384 for args ().
2023-07-02 10:33:15,379 [absl] Finished XLA compilation of iota in 0.0053822994232177734 sec
2023-07-02 10:33:15,380 [absl] Finished tracing + transforming prim_fun for jit in 0.0002541542053222656 sec
2023-07-02 10:33:15,380 [absl] Compiling prim_fun (140344365712784 for args (ShapedArray(int32[1,1]), ShapedArray(int32[1,1])).
2023-07-02 10:33:15,389 [absl] Finished XLA compilation of eq in 0.005829811096191406 sec
2023-07-02 10:33:15,390 [absl] Finished tracing + transforming prim_fun for jit in 0.00021886825561523438 sec
2023-07-02 10:33:15,390 [absl] Compiling prim_fun (140344365712224 for args (ShapedArray(bool[1,1]),).
2023-07-02 10:33:15,398 [absl] Finished XLA compilation of convert_element_type in 0.00564122200012207 sec
2023-07-02 10:33:15,400 [absl] Finished tracing + transforming prim_fun for jit in 0.0002770423889160156 sec
2023-07-02 10:33:15,400 [absl] Compiling prim_fun (140344365711824 for args (ShapedArray(float64[1,1]),).
2023-07-02 10:33:15,408 [absl] Finished XLA compilation of slice in 0.005150794982910156 sec
2023-07-02 10:33:15,409 [absl] Finished tracing + transforming prim_fun for jit in 0.0002753734588623047 sec
2023-07-02 10:33:15,409 [absl] Compiling prim_fun (140344365715024 for args (ShapedArray(float64[1,1]),).
2023-07-02 10:33:15,417 [absl] Finished XLA compilation of reshape in 0.005318403244018555 sec
2023-07-02 10:33:15,418 [absl] Finished tracing + transforming prim_fun for jit in 0.0002167224884033203 sec
2023-07-02 10:33:15,418 [absl] Compiling prim_fun (140344365711824 for args (ShapedArray(float64[1]),).
2023-07-02 10:33:15,426 [absl] Finished XLA compilation of convert_element_type in 0.0054662227630615234 sec
2023-07-02 10:33:15,429 [absl] Finished tracing + transforming fn for jit in 0.0014188289642333984 sec
2023-07-02 10:33:15,430 [absl] Compiling fn (140344365906176 for args (ShapedArray(float64[2,1]), ShapedArray(float64[], weak_type=True), ShapedArray(float64[1], weak_type=True)).
2023-07-02 10:33:15,441 [absl] Finished XLA compilation of fn in 0.007873296737670898 sec
2023-07-02 10:33:15,443 [absl] Finished tracing + transforming fn for jit in 0.0011246204376220703 sec
2023-07-02 10:33:15,443 [absl] Compiling fn (140344365906896 for args (ShapedArray(float64[2,19]), ShapedArray(float64[2,1]), ShapedArray(float64[1,2,1])).
2023-07-02 10:33:15,456 [absl] Finished XLA compilation of fn in 0.009931325912475586 sec
2023-07-02 10:33:15,458 [absl] Finished tracing + transforming fn for jit in 0.0006442070007324219 sec
2023-07-02 10:33:15,458 [absl] Compiling fn (140344365906256 for args (ShapedArray(float64[2,19]), ShapedArray(float64[2,1]), ShapedArray(float64[1,2,19])).
2023-07-02 10:33:15,469 [absl] Finished XLA compilation of fn in 0.00915670394897461 sec
2023-07-02 10:33:15,472 [absl] Finished tracing + transforming ravel for jit in 0.0008857250213623047 sec
2023-07-02 10:33:15,472 [absl] Compiling ravel (140344365499152 for args (ShapedArray(float64[2,19]), ShapedArray(float64[1,2,19])).
2023-07-02 10:33:15,480 [absl] Finished XLA compilation of ravel in 0.006064891815185547 sec
2023-07-02 10:33:15,482 [absl] Finished tracing + transforming <lambda> for jit in 0.0006434917449951172 sec
2023-07-02 10:33:15,482 [absl] Compiling <lambda> (140344365712544 for args (ShapedArray(float64[38]), ShapedArray(float64[38]), ShapedArray(float64[1,38])).
2023-07-02 10:33:15,493 [absl] Finished XLA compilation of <lambda> in 0.00842595100402832 sec
2023-07-02 10:33:15,496 [absl] Finished tracing + transforming dot for jit in 0.0009377002716064453 sec
2023-07-02 10:33:15,496 [absl] Compiling dot (140344365499632 for args (ShapedArray(float64[38]), ShapedArray(float64[38,38]), ShapedArray(float64[1,38])).
2023-07-02 10:33:15,519 [absl] Finished XLA compilation of dot in 0.020000696182250977 sec
2023-07-02 10:33:15,521 [absl] Finished tracing + transforming dot for jit in 0.0014214515686035156 sec
2023-07-02 10:33:15,522 [absl] Compiling dot (140344365500752 for args (ShapedArray(float64[38]), ShapedArray(float64[38]), ShapedArray(float64[1,38]), ShapedArray(float64[1,38])).
2023-07-02 10:33:15,547 [absl] Finished XLA compilation of dot in 0.022290706634521484 sec
2023-07-02 10:33:15,549 [absl] Finished tracing + transforming fn for jit in 0.0008902549743652344 sec
2023-07-02 10:33:15,549 [absl] Compiling fn (140344365499952 for args (ShapedArray(float64[], weak_type=True), ShapedArray(float64[]), ShapedArray(float64[1])).
2023-07-02 10:33:15,558 [absl] Finished XLA compilation of fn in 0.006411552429199219 sec
2023-07-02 10:33:15,561 [absl] Finished tracing + transforming fn for jit in 0.0005729198455810547 sec
2023-07-02 10:33:15,561 [absl] Compiling fn (140344365499552 for args (ShapedArray(float64[]), ShapedArray(float64[], weak_type=True), ShapedArray(float64[1])).
2023-07-02 10:33:15,570 [absl] Finished XLA compilation of fn in 0.0061798095703125 sec
2023-07-02 10:33:15,572 [absl] Finished tracing + transforming prim_fun for jit in 0.00020003318786621094 sec
2023-07-02 10:33:15,572 [absl] Compiling prim_fun (140344365904976 for args (ShapedArray(float64[1,38]),).
2023-07-02 10:33:15,580 [absl] Finished XLA compilation of transpose in 0.0054399967193603516 sec
2023-07-02 10:33:15,582 [absl] Finished tracing + transforming prim_fun for jit in 0.0002522468566894531 sec
2023-07-02 10:33:15,582 [absl] Compiling prim_fun (140344365715104 for args (ShapedArray(float64[38,1]),).
2023-07-02 10:33:15,590 [absl] Finished XLA compilation of slice in 0.005415439605712891 sec
2023-07-02 10:33:15,591 [absl] Finished tracing + transforming prim_fun for jit in 0.00025463104248046875 sec
2023-07-02 10:33:15,592 [absl] Compiling prim_fun (140344365712544 for args (ShapedArray(float64[38,1]),).
2023-07-02 10:33:15,599 [absl] Finished XLA compilation of reshape in 0.005372047424316406 sec
2023-07-02 10:33:15,608 [absl] Finished tracing + transforming fn for jit in 0.0007321834564208984 sec
2023-07-02 10:33:15,608 [absl] Compiling fn (140344365615520 for args (ShapedArray(float64[2,1]), ShapedArray(float64[]), ShapedArray(float64[1])).
2023-07-02 10:33:15,619 [absl] Finished XLA compilation of fn in 0.007681131362915039 sec
2023-07-02 10:33:15,631 [fs_likelihood.fslikelihood] Computed log-likelihood = -8939.07
2023-07-02 10:33:15,631 [model] Computed derived parameters: {}
2023-07-02 10:33:15,631 [model] Measuring speeds... (this may take a few seconds)
2023-07-02 10:33:15,631 [prior] Evaluating prior at array([0.30468482, 1.9978405 ])
2023-07-02 10:33:15,631 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:15,632 [model] Got input parameters: {'Omega_m': 0.30468481980267054, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.9978405048140404, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:15,632 [classy] Got parameters {'Omega_m': 0.30468481980267054, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:15,632 [classy] Computing new state
2023-07-02 10:33:15,632 [classy] Setting parameters: {'Omega_m': 0.30468481980267054, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:15,677 [classy] First evaluation time: 0.0449889 s
2023-07-02 10:33:15,677 [classy] Average evaluation time: 0.0449889 s
2023-07-02 10:33:15,677 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.20910683340315}
2023-07-02 10:33:15,677 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:15,679 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00400606
2023-07-02 10:33:15,679 [bao_likelihood.baolikelihood] First evaluation time: 0.00172929 s
2023-07-02 10:33:15,679 [bao_likelihood.baolikelihood] Average evaluation time: 0.00172929 s
2023-07-02 10:33:15,679 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.9978405048140404, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:15,679 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:15,699 [fs_likelihood.fslikelihood] Computed log-likelihood = -18781.9
2023-07-02 10:33:15,699 [fs_likelihood.fslikelihood] First evaluation time: 0.0202169 s
2023-07-02 10:33:15,699 [fs_likelihood.fslikelihood] Average evaluation time: 0.0202169 s
2023-07-02 10:33:15,699 [model] Computed derived parameters: {}
2023-07-02 10:33:15,699 [prior] Evaluating prior at array([0.29855374, 1.58274357])
2023-07-02 10:33:15,699 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:15,699 [model] Got input parameters: {'Omega_m': 0.2985537413973935, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.5827435664776845, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:15,699 [classy] Got parameters {'Omega_m': 0.2985537413973935, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:15,699 [classy] Computing new state
2023-07-02 10:33:15,700 [classy] Setting parameters: {'Omega_m': 0.2985537413973935, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:15,743 [classy] Average evaluation time: 0.0437982 s
2023-07-02 10:33:15,743 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.97024650096066}
2023-07-02 10:33:15,743 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:15,745 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.012527
2023-07-02 10:33:15,745 [bao_likelihood.baolikelihood] Average evaluation time: 0.00174019 s
2023-07-02 10:33:15,745 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.5827435664776845, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:15,745 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:15,765 [fs_likelihood.fslikelihood] Computed log-likelihood = -7095.09
2023-07-02 10:33:15,765 [fs_likelihood.fslikelihood] Average evaluation time: 0.0199828 s
2023-07-02 10:33:15,765 [model] Computed derived parameters: {}
2023-07-02 10:33:15,766 [prior] Evaluating prior at array([0.31633011, 1.54137877])
2023-07-02 10:33:15,766 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:15,766 [model] Got input parameters: {'Omega_m': 0.31633010761514957, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.5413787730443058, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:15,766 [classy] Got parameters {'Omega_m': 0.31633010761514957, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:15,766 [classy] Computing new state
2023-07-02 10:33:15,766 [classy] Setting parameters: {'Omega_m': 0.31633010761514957, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:15,809 [classy] Average evaluation time: 0.0437099 s
2023-07-02 10:33:15,810 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.7998430455232}
2023-07-02 10:33:15,810 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:15,811 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0011009
2023-07-02 10:33:15,811 [bao_likelihood.baolikelihood] Average evaluation time: 0.00172499 s
2023-07-02 10:33:15,811 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.5413787730443058, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:15,811 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:15,832 [fs_likelihood.fslikelihood] Computed log-likelihood = -7143.48
2023-07-02 10:33:15,832 [fs_likelihood.fslikelihood] Average evaluation time: 0.0202939 s
2023-07-02 10:33:15,832 [model] Computed derived parameters: {}
2023-07-02 10:33:15,832 [model] Computed 3 points to measure speeds.
2023-07-02 10:33:15,832 [model] Setting measured speeds (per sec): {bao_likelihood.BAOLikelihood: 580.0, fs_likelihood.FSLikelihood: 49.3, classy: 22.9}
2023-07-02 10:33:15,832 [mcmc] Initial point: Omega_m:0.2899682, b1:1.632284
2023-07-02 10:33:15,832 [model] Cost, oversampling factor and parameters per block, in optimal order:
2023-07-02 10:33:15,833 [model] * 0.0666291 : 1 : ['Omega_m']
2023-07-02 10:33:15,833 [model] * 0.020594 : 1 : ['b1']
2023-07-02 10:33:15,833 [mcmc] Cycle length in steps: 2
2023-07-02 10:33:15,833 [mcmc] Covariance matrix not present. We will start learning the covariance of the proposal earlier: R-1 = 30 (would be 2 if all params loaded).
2023-07-02 10:33:15,835 [mcmc] Sampling with covmat:
Omega_m b1
Omega_m 0.000025 0.000000
b1 0.000000 0.083333
2023-07-02 10:33:15,844 [mcmc] Dumped checkpoint and progress info, and current covmat.
2023-07-02 10:33:15,849 [mcmc] Sampling!
2023-07-02 10:33:15,849 [model] Posterior to be computed for parameters {'Omega_m': 0.30159681038606223, 'b1': 1.6322839223318795}
2023-07-02 10:33:15,849 [prior] Evaluating prior at array([0.30159681, 1.63228392])
2023-07-02 10:33:15,850 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:15,850 [model] Got input parameters: {'Omega_m': 0.30159681038606223, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.6322839223318795, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:15,850 [classy] Got parameters {'Omega_m': 0.30159681038606223, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:15,850 [classy] Computing new state
2023-07-02 10:33:15,850 [classy] Setting parameters: {'Omega_m': 0.30159681038606223, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:15,894 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.59075634576806}
2023-07-02 10:33:15,894 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:15,896 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00767221
2023-07-02 10:33:15,896 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.6322839223318795, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:15,896 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:15,917 [fs_likelihood.fslikelihood] Computed log-likelihood = -8209.22
2023-07-02 10:33:15,917 [model] Computed derived parameters: {}
2023-07-02 10:33:15,917 [mcmc] Burn-in sample:
Omega_m:0.2899682, b1:1.632284
2023-07-02 10:33:15,917 [mcmc] Progress @ 2023-07-02 10:33:15 : 1 steps taken, and 0 accepted.
2023-07-02 10:33:15,917 [model] Posterior to be computed for parameters {'Omega_m': 0.30159681038606223, 'b1': 1.1793575939907832}
2023-07-02 10:33:15,917 [prior] Evaluating prior at array([0.30159681, 1.17935759])
2023-07-02 10:33:15,917 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:15,917 [model] Got input parameters: {'Omega_m': 0.30159681038606223, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.1793575939907832, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:15,917 [classy] Got parameters {'Omega_m': 0.30159681038606223, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:15,917 [classy] Re-using computed results
2023-07-02 10:33:15,917 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.59075634576806}
2023-07-02 10:33:15,917 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:15,917 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.1793575939907832, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:15,917 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:15,938 [fs_likelihood.fslikelihood] Computed log-likelihood = -2045.99
2023-07-02 10:33:15,938 [model] Computed derived parameters: {}
2023-07-02 10:33:15,938 [mcmc] New sample, #1:
Omega_m:0.3015968, b1:1.632284
2023-07-02 10:33:15,938 [model] Posterior to be computed for parameters {'Omega_m': 0.30675679491331304, 'b1': 1.1793575939907832}
2023-07-02 10:33:15,938 [prior] Evaluating prior at array([0.30675679, 1.17935759])
2023-07-02 10:33:15,938 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:15,938 [model] Got input parameters: {'Omega_m': 0.30675679491331304, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.1793575939907832, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:15,938 [classy] Got parameters {'Omega_m': 0.30675679491331304, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:15,938 [classy] Computing new state
2023-07-02 10:33:15,938 [classy] Setting parameters: {'Omega_m': 0.30675679491331304, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:15,984 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.95492952552055}
2023-07-02 10:33:15,984 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:15,986 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00224291
2023-07-02 10:33:15,986 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.1793575939907832, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:15,986 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:16,006 [fs_likelihood.fslikelihood] Computed log-likelihood = -2136.74
2023-07-02 10:33:16,006 [model] Computed derived parameters: {}
2023-07-02 10:33:16,006 [model] Posterior to be computed for parameters {'Omega_m': 0.30159681038606223, 'b1': 0.8182528959083948}
2023-07-02 10:33:16,006 [prior] Evaluating prior at array([0.30159681, 0.8182529 ])
2023-07-02 10:33:16,006 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:16,006 [model] Got input parameters: {'Omega_m': 0.30159681038606223, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:16,006 [classy] Got parameters {'Omega_m': 0.30159681038606223, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:16,006 [classy] Re-using computed results
2023-07-02 10:33:16,006 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.59075634576806}
2023-07-02 10:33:16,006 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:16,006 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:16,007 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:16,026 [fs_likelihood.fslikelihood] Computed log-likelihood = -301.064
2023-07-02 10:33:16,026 [model] Computed derived parameters: {}
2023-07-02 10:33:16,026 [mcmc] New sample, #2:
Omega_m:0.3015968, b1:1.179358
2023-07-02 10:33:16,026 [model] Posterior to be computed for parameters {'Omega_m': 0.309038032519737, 'b1': 0.8182528959083948}
2023-07-02 10:33:16,026 [prior] Evaluating prior at array([0.30903803, 0.8182529 ])
2023-07-02 10:33:16,026 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:16,027 [model] Got input parameters: {'Omega_m': 0.309038032519737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:16,027 [classy] Got parameters {'Omega_m': 0.309038032519737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:16,027 [classy] Computing new state
2023-07-02 10:33:16,027 [classy] Setting parameters: {'Omega_m': 0.309038032519737, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:16,071 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.6768183540687}
2023-07-02 10:33:16,071 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:16,073 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000936895
2023-07-02 10:33:16,073 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:16,073 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:16,093 [fs_likelihood.fslikelihood] Computed log-likelihood = -335.882
2023-07-02 10:33:16,093 [model] Computed derived parameters: {}
2023-07-02 10:33:16,093 [model] Posterior to be computed for parameters {'Omega_m': 0.30159681038606223, 'b1': 1.4305969951339712}
2023-07-02 10:33:16,093 [prior] Evaluating prior at array([0.30159681, 1.430597 ])
2023-07-02 10:33:16,093 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:16,093 [model] Got input parameters: {'Omega_m': 0.30159681038606223, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.4305969951339712, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:16,093 [classy] Got parameters {'Omega_m': 0.30159681038606223, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:16,093 [classy] Re-using computed results
2023-07-02 10:33:16,093 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.59075634576806}
2023-07-02 10:33:16,093 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:16,093 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.4305969951339712, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:16,093 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:16,113 [fs_likelihood.fslikelihood] Computed log-likelihood = -4753.93
2023-07-02 10:33:16,113 [model] Computed derived parameters: {}
2023-07-02 10:33:16,113 [model] Posterior to be computed for parameters {'Omega_m': 0.2878456715432816, 'b1': 0.8182528959083948}
2023-07-02 10:33:16,113 [prior] Evaluating prior at array([0.28784567, 0.8182529 ])
2023-07-02 10:33:16,113 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:16,113 [model] Got input parameters: {'Omega_m': 0.2878456715432816, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:16,113 [classy] Got parameters {'Omega_m': 0.2878456715432816, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:16,113 [classy] Computing new state
2023-07-02 10:33:16,113 [classy] Setting parameters: {'Omega_m': 0.2878456715432816, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:16,160 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.3329796495312}
2023-07-02 10:33:16,160 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:16,162 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0398389
2023-07-02 10:33:16,162 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:16,162 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:16,182 [fs_likelihood.fslikelihood] Computed log-likelihood = -245.311
2023-07-02 10:33:16,182 [model] Computed derived parameters: {}
2023-07-02 10:33:16,182 [mcmc] New sample, #3:
Omega_m:0.3015968, b1:0.8182529
2023-07-02 10:33:16,183 [model] Posterior to be computed for parameters {'Omega_m': 0.2878456715432816, 'b1': 0.053800055942150204}
2023-07-02 10:33:16,183 [prior] Evaluating prior at array([0.28784567, 0.05380006])
2023-07-02 10:33:16,183 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:16,183 [model] Got input parameters: {'Omega_m': 0.2878456715432816, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.053800055942150204, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:16,183 [classy] Got parameters {'Omega_m': 0.2878456715432816, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:16,183 [classy] Re-using computed results
2023-07-02 10:33:16,183 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.3329796495312}
2023-07-02 10:33:16,183 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:16,183 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.053800055942150204, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:16,183 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:16,203 [fs_likelihood.fslikelihood] Computed log-likelihood = -381.553
2023-07-02 10:33:16,203 [model] Computed derived parameters: {}
2023-07-02 10:33:16,203 [model] Posterior to be computed for parameters {'Omega_m': 0.2726188687271508, 'b1': 0.8182528959083948}
2023-07-02 10:33:16,203 [prior] Evaluating prior at array([0.27261887, 0.8182529 ])
2023-07-02 10:33:16,203 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:16,203 [model] Got input parameters: {'Omega_m': 0.2726188687271508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:16,203 [classy] Got parameters {'Omega_m': 0.2726188687271508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:16,203 [classy] Computing new state
2023-07-02 10:33:16,203 [classy] Setting parameters: {'Omega_m': 0.2726188687271508, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:16,249 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.3481585604555}
2023-07-02 10:33:16,249 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:16,250 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.108248
2023-07-02 10:33:16,250 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:16,250 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:16,270 [fs_likelihood.fslikelihood] Computed log-likelihood = -196.584
2023-07-02 10:33:16,270 [model] Computed derived parameters: {}
2023-07-02 10:33:16,270 [mcmc] New sample, #4:
Omega_m:0.2878457, b1:0.8182529
2023-07-02 10:33:16,271 [model] Posterior to be computed for parameters {'Omega_m': 0.2726188687271508, 'b1': -0.09514461076074388}
2023-07-02 10:33:16,271 [prior] Evaluating prior at array([ 0.27261887, -0.09514461])
2023-07-02 10:33:16,271 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:16,271 [model] Posterior to be computed for parameters {'Omega_m': 0.28203941896651996, 'b1': 0.8182528959083948}
2023-07-02 10:33:16,271 [prior] Evaluating prior at array([0.28203942, 0.8182529 ])
2023-07-02 10:33:16,271 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:16,271 [model] Got input parameters: {'Omega_m': 0.28203941896651996, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:16,271 [classy] Got parameters {'Omega_m': 0.28203941896651996, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:16,271 [classy] Computing new state
2023-07-02 10:33:16,271 [classy] Setting parameters: {'Omega_m': 0.28203941896651996, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:16,316 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.09038791501067}
2023-07-02 10:33:16,316 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:16,317 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0616535
2023-07-02 10:33:16,317 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:16,317 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:16,338 [fs_likelihood.fslikelihood] Computed log-likelihood = -225.118
2023-07-02 10:33:16,338 [model] Computed derived parameters: {}
2023-07-02 10:33:16,338 [model] Posterior to be computed for parameters {'Omega_m': 0.2726188687271508, 'b1': 0.9589805399331686}
2023-07-02 10:33:16,338 [prior] Evaluating prior at array([0.27261887, 0.95898054])
2023-07-02 10:33:16,338 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:16,338 [model] Got input parameters: {'Omega_m': 0.2726188687271508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.9589805399331686, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:16,338 [classy] Got parameters {'Omega_m': 0.2726188687271508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:16,338 [classy] Re-using computed results
2023-07-02 10:33:16,338 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.3481585604555}
2023-07-02 10:33:16,338 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:16,338 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.9589805399331686, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:16,338 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:16,358 [fs_likelihood.fslikelihood] Computed log-likelihood = -540.713
2023-07-02 10:33:16,358 [model] Computed derived parameters: {}
2023-07-02 10:33:16,358 [model] Posterior to be computed for parameters {'Omega_m': 0.2957629172298728, 'b1': 0.8182528959083948}
2023-07-02 10:33:16,358 [prior] Evaluating prior at array([0.29576292, 0.8182529 ])
2023-07-02 10:33:16,358 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:16,358 [model] Got input parameters: {'Omega_m': 0.2957629172298728, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:16,358 [classy] Got parameters {'Omega_m': 0.2957629172298728, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:16,358 [classy] Computing new state
2023-07-02 10:33:16,358 [classy] Setting parameters: {'Omega_m': 0.2957629172298728, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:16,403 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.3212767904241}
2023-07-02 10:33:16,403 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:16,405 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0180881
2023-07-02 10:33:16,405 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:16,405 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:16,424 [fs_likelihood.fslikelihood] Computed log-likelihood = -276.049
2023-07-02 10:33:16,424 [model] Computed derived parameters: {}
2023-07-02 10:33:16,424 [model] Posterior to be computed for parameters {'Omega_m': 0.2726188687271508, 'b1': 1.2858471165446863}
2023-07-02 10:33:16,424 [prior] Evaluating prior at array([0.27261887, 1.28584712])
2023-07-02 10:33:16,425 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:16,425 [model] Got input parameters: {'Omega_m': 0.2726188687271508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.2858471165446863, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:16,425 [classy] Got parameters {'Omega_m': 0.2726188687271508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:16,425 [classy] Re-using computed results
2023-07-02 10:33:16,425 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.3481585604555}
2023-07-02 10:33:16,425 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:16,425 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.2858471165446863, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:16,425 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:16,445 [fs_likelihood.fslikelihood] Computed log-likelihood = -2394.92
2023-07-02 10:33:16,445 [model] Computed derived parameters: {}
2023-07-02 10:33:16,445 [model] Posterior to be computed for parameters {'Omega_m': 0.28602613176017117, 'b1': 0.8182528959083948}
2023-07-02 10:33:16,445 [prior] Evaluating prior at array([0.28602613, 0.8182529 ])
2023-07-02 10:33:16,445 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:16,445 [model] Got input parameters: {'Omega_m': 0.28602613176017117, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:16,445 [classy] Got parameters {'Omega_m': 0.28602613176017117, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:16,445 [classy] Computing new state
2023-07-02 10:33:16,446 [classy] Setting parameters: {'Omega_m': 0.28602613176017117, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:16,489 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.56889102530823}
2023-07-02 10:33:16,489 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:16,491 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0461272
2023-07-02 10:33:16,491 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:16,491 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:16,511 [fs_likelihood.fslikelihood] Computed log-likelihood = -238.77
2023-07-02 10:33:16,511 [model] Computed derived parameters: {}
2023-07-02 10:33:16,511 [model] Posterior to be computed for parameters {'Omega_m': 0.2726188687271508, 'b1': 1.128211509064688}
2023-07-02 10:33:16,511 [prior] Evaluating prior at array([0.27261887, 1.12821151])
2023-07-02 10:33:16,511 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:16,511 [model] Got input parameters: {'Omega_m': 0.2726188687271508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.128211509064688, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:16,511 [classy] Got parameters {'Omega_m': 0.2726188687271508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:16,511 [classy] Re-using computed results
2023-07-02 10:33:16,511 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.3481585604555}
2023-07-02 10:33:16,511 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:16,511 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.128211509064688, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:16,511 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:16,531 [fs_likelihood.fslikelihood] Computed log-likelihood = -1283.4
2023-07-02 10:33:16,531 [model] Computed derived parameters: {}
2023-07-02 10:33:16,531 [model] Posterior to be computed for parameters {'Omega_m': 0.27592580202259703, 'b1': 0.8182528959083948}
2023-07-02 10:33:16,531 [prior] Evaluating prior at array([0.2759258, 0.8182529])
2023-07-02 10:33:16,531 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:16,531 [model] Got input parameters: {'Omega_m': 0.27592580202259703, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:16,531 [classy] Got parameters {'Omega_m': 0.27592580202259703, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:16,531 [classy] Computing new state
2023-07-02 10:33:16,531 [classy] Setting parameters: {'Omega_m': 0.27592580202259703, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:16,575 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.9024831105214}
2023-07-02 10:33:16,575 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:16,576 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0902643
2023-07-02 10:33:16,576 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:16,576 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:16,596 [fs_likelihood.fslikelihood] Computed log-likelihood = -206.005
2023-07-02 10:33:16,596 [model] Computed derived parameters: {}
2023-07-02 10:33:16,597 [model] Posterior to be computed for parameters {'Omega_m': 0.2726188687271508, 'b1': 0.944089927588688}
2023-07-02 10:33:16,597 [prior] Evaluating prior at array([0.27261887, 0.94408993])
2023-07-02 10:33:16,597 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:16,597 [model] Got input parameters: {'Omega_m': 0.2726188687271508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.944089927588688, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:16,597 [classy] Got parameters {'Omega_m': 0.2726188687271508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:16,597 [classy] Re-using computed results
2023-07-02 10:33:16,597 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.3481585604555}
2023-07-02 10:33:16,597 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:16,597 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.944089927588688, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:16,597 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:16,616 [fs_likelihood.fslikelihood] Computed log-likelihood = -493.843
2023-07-02 10:33:16,617 [model] Computed derived parameters: {}
2023-07-02 10:33:16,617 [model] Posterior to be computed for parameters {'Omega_m': 0.26225838904316323, 'b1': 0.8182528959083948}
2023-07-02 10:33:16,617 [prior] Evaluating prior at array([0.26225839, 0.8182529 ])
2023-07-02 10:33:16,617 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:16,617 [model] Got input parameters: {'Omega_m': 0.26225838904316323, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:16,617 [classy] Got parameters {'Omega_m': 0.26225838904316323, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:16,617 [classy] Computing new state
2023-07-02 10:33:16,617 [classy] Setting parameters: {'Omega_m': 0.26225838904316323, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:16,661 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.77484301414668}
2023-07-02 10:33:16,661 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:16,663 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.176623
2023-07-02 10:33:16,663 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:16,663 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:16,683 [fs_likelihood.fslikelihood] Computed log-likelihood = -171.244
2023-07-02 10:33:16,683 [model] Computed derived parameters: {}
2023-07-02 10:33:16,683 [mcmc] New sample, #5:
Omega_m:0.2726189, b1:0.8182529
2023-07-02 10:33:16,683 [model] Posterior to be computed for parameters {'Omega_m': 0.26225838904316323, 'b1': 1.5625394088617082}
2023-07-02 10:33:16,683 [prior] Evaluating prior at array([0.26225839, 1.56253941])
2023-07-02 10:33:16,683 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:16,683 [model] Got input parameters: {'Omega_m': 0.26225838904316323, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.5625394088617082, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:16,683 [classy] Got parameters {'Omega_m': 0.26225838904316323, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:16,683 [classy] Re-using computed results
2023-07-02 10:33:16,683 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.77484301414668}
2023-07-02 10:33:16,683 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:16,683 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.5625394088617082, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:16,683 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:16,703 [fs_likelihood.fslikelihood] Computed log-likelihood = -5273.7
2023-07-02 10:33:16,703 [model] Computed derived parameters: {}
2023-07-02 10:33:16,703 [model] Posterior to be computed for parameters {'Omega_m': 0.27294701790625175, 'b1': 0.8182528959083948}
2023-07-02 10:33:16,704 [prior] Evaluating prior at array([0.27294702, 0.8182529 ])
2023-07-02 10:33:16,704 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:16,704 [model] Got input parameters: {'Omega_m': 0.27294701790625175, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:16,704 [classy] Got parameters {'Omega_m': 0.27294701790625175, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:16,704 [classy] Computing new state
2023-07-02 10:33:16,704 [classy] Setting parameters: {'Omega_m': 0.27294701790625175, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:16,748 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.30373159833172}
2023-07-02 10:33:16,748 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:16,750 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.106383
2023-07-02 10:33:16,750 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:16,750 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:16,769 [fs_likelihood.fslikelihood] Computed log-likelihood = -197.49
2023-07-02 10:33:16,769 [model] Computed derived parameters: {}
2023-07-02 10:33:16,769 [model] Posterior to be computed for parameters {'Omega_m': 0.26225838904316323, 'b1': 1.456962531561599}
2023-07-02 10:33:16,769 [prior] Evaluating prior at array([0.26225839, 1.45696253])
2023-07-02 10:33:16,770 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:16,770 [model] Got input parameters: {'Omega_m': 0.26225838904316323, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.456962531561599, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:16,770 [classy] Got parameters {'Omega_m': 0.26225838904316323, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:16,770 [classy] Re-using computed results
2023-07-02 10:33:16,770 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.77484301414668}
2023-07-02 10:33:16,770 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:16,770 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.456962531561599, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:16,770 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:16,790 [fs_likelihood.fslikelihood] Computed log-likelihood = -3886.41
2023-07-02 10:33:16,790 [model] Computed derived parameters: {}
2023-07-02 10:33:16,790 [model] Posterior to be computed for parameters {'Omega_m': 0.2609899719629662, 'b1': 0.8182528959083948}
2023-07-02 10:33:16,791 [prior] Evaluating prior at array([0.26098997, 0.8182529 ])
2023-07-02 10:33:16,791 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:16,791 [model] Got input parameters: {'Omega_m': 0.2609899719629662, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:16,791 [classy] Got parameters {'Omega_m': 0.2609899719629662, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:16,791 [classy] Computing new state
2023-07-02 10:33:16,791 [classy] Setting parameters: {'Omega_m': 0.2609899719629662, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:16,834 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.9527458653329}
2023-07-02 10:33:16,834 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:16,836 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.186296
2023-07-02 10:33:16,836 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:16,836 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:16,857 [fs_likelihood.fslikelihood] Computed log-likelihood = -168.577
2023-07-02 10:33:16,857 [model] Computed derived parameters: {}
2023-07-02 10:33:16,857 [mcmc] New sample, #6:
Omega_m:0.2622584, b1:0.8182529
2023-07-02 10:33:16,857 [model] Posterior to be computed for parameters {'Omega_m': 0.2609899719629662, 'b1': 1.67375319713257}
2023-07-02 10:33:16,857 [prior] Evaluating prior at array([0.26098997, 1.6737532 ])
2023-07-02 10:33:16,857 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:16,857 [model] Got input parameters: {'Omega_m': 0.2609899719629662, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.67375319713257, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:16,857 [classy] Got parameters {'Omega_m': 0.2609899719629662, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:16,857 [classy] Re-using computed results
2023-07-02 10:33:16,857 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.9527458653329}
2023-07-02 10:33:16,857 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:16,857 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.67375319713257, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:16,857 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:16,877 [fs_likelihood.fslikelihood] Computed log-likelihood = -7014.08
2023-07-02 10:33:16,877 [model] Computed derived parameters: {}
2023-07-02 10:33:16,877 [model] Posterior to be computed for parameters {'Omega_m': 0.27302154852603616, 'b1': 0.8182528959083948}
2023-07-02 10:33:16,877 [prior] Evaluating prior at array([0.27302155, 0.8182529 ])
2023-07-02 10:33:16,877 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:16,877 [model] Got input parameters: {'Omega_m': 0.27302154852603616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:16,877 [classy] Got parameters {'Omega_m': 0.27302154852603616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:16,877 [classy] Computing new state
2023-07-02 10:33:16,877 [classy] Setting parameters: {'Omega_m': 0.27302154852603616, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:16,921 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.29364377597815}
2023-07-02 10:33:16,921 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:16,923 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.105962
2023-07-02 10:33:16,923 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:16,923 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:16,943 [fs_likelihood.fslikelihood] Computed log-likelihood = -197.697
2023-07-02 10:33:16,943 [model] Computed derived parameters: {}
2023-07-02 10:33:16,943 [model] Posterior to be computed for parameters {'Omega_m': 0.2609899719629662, 'b1': 0.004751808353729903}
2023-07-02 10:33:16,944 [prior] Evaluating prior at array([0.26098997, 0.00475181])
2023-07-02 10:33:16,944 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:16,944 [model] Got input parameters: {'Omega_m': 0.2609899719629662, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.004751808353729903, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:16,944 [classy] Got parameters {'Omega_m': 0.2609899719629662, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:16,944 [classy] Re-using computed results
2023-07-02 10:33:16,944 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.9527458653329}
2023-07-02 10:33:16,944 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:16,944 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.004751808353729903, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:16,944 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:16,963 [fs_likelihood.fslikelihood] Computed log-likelihood = -487.921
2023-07-02 10:33:16,963 [model] Computed derived parameters: {}
2023-07-02 10:33:16,964 [model] Posterior to be computed for parameters {'Omega_m': 0.25977404455312525, 'b1': 0.8182528959083948}
2023-07-02 10:33:16,964 [prior] Evaluating prior at array([0.25977404, 0.8182529 ])
2023-07-02 10:33:16,964 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:16,964 [model] Got input parameters: {'Omega_m': 0.25977404455312525, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:16,964 [classy] Got parameters {'Omega_m': 0.25977404455312525, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:16,964 [classy] Computing new state
2023-07-02 10:33:16,964 [classy] Setting parameters: {'Omega_m': 0.25977404455312525, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:17,008 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 154.1239605473226}
2023-07-02 10:33:17,008 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:17,010 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.195844
2023-07-02 10:33:17,010 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:17,010 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:17,031 [fs_likelihood.fslikelihood] Computed log-likelihood = -166.109
2023-07-02 10:33:17,031 [model] Computed derived parameters: {}
2023-07-02 10:33:17,031 [mcmc] New sample, #7:
Omega_m:0.26099, b1:0.8182529
2023-07-02 10:33:17,032 [model] Posterior to be computed for parameters {'Omega_m': 0.25977404455312525, 'b1': 1.2843110112976766}
2023-07-02 10:33:17,032 [prior] Evaluating prior at array([0.25977404, 1.28431101])
2023-07-02 10:33:17,032 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:17,032 [model] Got input parameters: {'Omega_m': 0.25977404455312525, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.2843110112976766, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:17,032 [classy] Got parameters {'Omega_m': 0.25977404455312525, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:17,032 [classy] Re-using computed results
2023-07-02 10:33:17,032 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 154.1239605473226}
2023-07-02 10:33:17,032 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:17,032 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.2843110112976766, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:17,032 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:17,052 [fs_likelihood.fslikelihood] Computed log-likelihood = -2149.11
2023-07-02 10:33:17,052 [model] Computed derived parameters: {}
2023-07-02 10:33:17,053 [model] Posterior to be computed for parameters {'Omega_m': 0.2721898618308027, 'b1': 0.8182528959083948}
2023-07-02 10:33:17,053 [prior] Evaluating prior at array([0.27218986, 0.8182529 ])
2023-07-02 10:33:17,053 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:17,053 [model] Got input parameters: {'Omega_m': 0.2721898618308027, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:17,053 [classy] Got parameters {'Omega_m': 0.2721898618308027, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:17,053 [classy] Computing new state
2023-07-02 10:33:17,053 [classy] Setting parameters: {'Omega_m': 0.2721898618308027, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:17,098 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.40631930126844}
2023-07-02 10:33:17,098 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:17,099 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.110714
2023-07-02 10:33:17,099 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:17,099 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:17,120 [fs_likelihood.fslikelihood] Computed log-likelihood = -195.409
2023-07-02 10:33:17,120 [model] Computed derived parameters: {}
2023-07-02 10:33:17,120 [model] Posterior to be computed for parameters {'Omega_m': 0.25977404455312525, 'b1': -0.4338354439874048}
2023-07-02 10:33:17,120 [prior] Evaluating prior at array([ 0.25977404, -0.43383544])
2023-07-02 10:33:17,120 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:17,121 [model] Posterior to be computed for parameters {'Omega_m': 0.25204277059003577, 'b1': 0.8182528959083948}
2023-07-02 10:33:17,121 [prior] Evaluating prior at array([0.25204277, 0.8182529 ])
2023-07-02 10:33:17,121 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:17,121 [model] Got input parameters: {'Omega_m': 0.25204277059003577, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:17,121 [classy] Got parameters {'Omega_m': 0.25204277059003577, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:17,121 [classy] Computing new state
2023-07-02 10:33:17,121 [classy] Setting parameters: {'Omega_m': 0.25204277059003577, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:17,174 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 155.22862410571764}
2023-07-02 10:33:17,174 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:17,176 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.26307
2023-07-02 10:33:17,176 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:17,176 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:17,198 [fs_likelihood.fslikelihood] Computed log-likelihood = -152.456
2023-07-02 10:33:17,198 [model] Computed derived parameters: {}
2023-07-02 10:33:17,198 [mcmc] New sample, #8:
Omega_m:0.259774, b1:0.8182529
2023-07-02 10:33:17,199 [model] Posterior to be computed for parameters {'Omega_m': 0.25204277059003577, 'b1': 2.0700062583797143}
2023-07-02 10:33:17,199 [prior] Evaluating prior at array([0.25204277, 2.07000626])
2023-07-02 10:33:17,199 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:17,199 [model] Got input parameters: {'Omega_m': 0.25204277059003577, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 2.0700062583797143, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:17,199 [classy] Got parameters {'Omega_m': 0.25204277059003577, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:17,199 [classy] Re-using computed results
2023-07-02 10:33:17,199 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 155.22862410571764}
2023-07-02 10:33:17,199 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:17,199 [fs_likelihood.fslikelihood] Got parameters {'b1': 2.0700062583797143, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:17,199 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:17,219 [fs_likelihood.fslikelihood] Computed log-likelihood = -16031.9
2023-07-02 10:33:17,219 [model] Computed derived parameters: {}
2023-07-02 10:33:17,219 [model] Posterior to be computed for parameters {'Omega_m': 0.24251082666719687, 'b1': 0.8182528959083948}
2023-07-02 10:33:17,219 [prior] Evaluating prior at array([0.24251083, 0.8182529 ])
2023-07-02 10:33:17,219 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:17,219 [model] Got input parameters: {'Omega_m': 0.24251082666719687, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:17,219 [classy] Got parameters {'Omega_m': 0.24251082666719687, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:17,219 [classy] Computing new state
2023-07-02 10:33:17,219 [classy] Setting parameters: {'Omega_m': 0.24251082666719687, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:17,265 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 156.62976245517348}
2023-07-02 10:33:17,265 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:17,266 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.362221
2023-07-02 10:33:17,267 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8182528959083948, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:17,267 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:17,286 [fs_likelihood.fslikelihood] Computed log-likelihood = -140.473
2023-07-02 10:33:17,286 [model] Computed derived parameters: {}
2023-07-02 10:33:17,286 [mcmc] New sample, #9:
Omega_m:0.2520428, b1:0.8182529
2023-07-02 10:33:17,286 [model] Posterior to be computed for parameters {'Omega_m': 0.24251082666719687, 'b1': 0.600728251405974}
2023-07-02 10:33:17,286 [prior] Evaluating prior at array([0.24251083, 0.60072825])
2023-07-02 10:33:17,286 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:17,286 [model] Got input parameters: {'Omega_m': 0.24251082666719687, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:17,286 [classy] Got parameters {'Omega_m': 0.24251082666719687, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:17,287 [classy] Re-using computed results
2023-07-02 10:33:17,287 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 156.62976245517348}
2023-07-02 10:33:17,287 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:17,287 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:17,287 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:17,306 [fs_likelihood.fslikelihood] Computed log-likelihood = -39.3114
2023-07-02 10:33:17,306 [model] Computed derived parameters: {}
2023-07-02 10:33:17,306 [mcmc] New sample, #10:
Omega_m:0.2425108, b1:0.8182529
2023-07-02 10:33:17,307 [model] Posterior to be computed for parameters {'Omega_m': 0.24324011743928295, 'b1': 0.600728251405974}
2023-07-02 10:33:17,307 [prior] Evaluating prior at array([0.24324012, 0.60072825])
2023-07-02 10:33:17,307 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:17,307 [model] Got input parameters: {'Omega_m': 0.24324011743928295, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:17,307 [classy] Got parameters {'Omega_m': 0.24324011743928295, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:17,307 [classy] Computing new state
2023-07-02 10:33:17,307 [classy] Setting parameters: {'Omega_m': 0.24324011743928295, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:17,351 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 156.52097813775873}
2023-07-02 10:33:17,351 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:17,353 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.35397
2023-07-02 10:33:17,353 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:17,353 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:17,373 [fs_likelihood.fslikelihood] Computed log-likelihood = -38.2243
2023-07-02 10:33:17,373 [model] Computed derived parameters: {}
2023-07-02 10:33:17,373 [mcmc] New sample, #11:
Omega_m:0.2425108, b1:0.6007283
2023-07-02 10:33:17,373 [model] Posterior to be computed for parameters {'Omega_m': 0.24324011743928295, 'b1': 1.7955126374360098}
2023-07-02 10:33:17,373 [prior] Evaluating prior at array([0.24324012, 1.79551264])
2023-07-02 10:33:17,373 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:17,373 [model] Got input parameters: {'Omega_m': 0.24324011743928295, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.7955126374360098, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:17,373 [classy] Got parameters {'Omega_m': 0.24324011743928295, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:17,373 [classy] Re-using computed results
2023-07-02 10:33:17,373 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 156.52097813775873}
2023-07-02 10:33:17,373 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:17,373 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.7955126374360098, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:17,373 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:17,392 [fs_likelihood.fslikelihood] Computed log-likelihood = -8425.15
2023-07-02 10:33:17,393 [model] Computed derived parameters: {}
2023-07-02 10:33:17,393 [model] Posterior to be computed for parameters {'Omega_m': 0.26799843593273476, 'b1': 0.600728251405974}
2023-07-02 10:33:17,393 [prior] Evaluating prior at array([0.26799844, 0.60072825])
2023-07-02 10:33:17,393 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:17,393 [model] Got input parameters: {'Omega_m': 0.26799843593273476, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:17,393 [classy] Got parameters {'Omega_m': 0.26799843593273476, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:17,393 [classy] Computing new state
2023-07-02 10:33:17,393 [classy] Setting parameters: {'Omega_m': 0.26799843593273476, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:17,437 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.97867406055138}
2023-07-02 10:33:17,437 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:17,438 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.136443
2023-07-02 10:33:17,439 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:17,439 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:17,459 [fs_likelihood.fslikelihood] Computed log-likelihood = -12.9418
2023-07-02 10:33:17,459 [model] Computed derived parameters: {}
2023-07-02 10:33:17,459 [mcmc] New sample, #12:
Omega_m:0.2432401, b1:0.6007283
2023-07-02 10:33:17,460 [model] Posterior to be computed for parameters {'Omega_m': 0.26799843593273476, 'b1': 0.21654010019951703}
2023-07-02 10:33:17,460 [prior] Evaluating prior at array([0.26799844, 0.2165401 ])
2023-07-02 10:33:17,460 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:17,460 [model] Got input parameters: {'Omega_m': 0.26799843593273476, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.21654010019951703, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:17,460 [classy] Got parameters {'Omega_m': 0.26799843593273476, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:17,460 [classy] Re-using computed results
2023-07-02 10:33:17,460 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.97867406055138}
2023-07-02 10:33:17,460 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:17,460 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.21654010019951703, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:17,460 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:17,479 [fs_likelihood.fslikelihood] Computed log-likelihood = -248.869
2023-07-02 10:33:17,479 [model] Computed derived parameters: {}
2023-07-02 10:33:17,479 [model] Posterior to be computed for parameters {'Omega_m': 0.24947118981260316, 'b1': 0.600728251405974}
2023-07-02 10:33:17,479 [prior] Evaluating prior at array([0.24947119, 0.60072825])
2023-07-02 10:33:17,480 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:17,480 [model] Got input parameters: {'Omega_m': 0.24947118981260316, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:17,480 [classy] Got parameters {'Omega_m': 0.24947118981260316, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:17,480 [classy] Computing new state
2023-07-02 10:33:17,480 [classy] Setting parameters: {'Omega_m': 0.24947118981260316, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:17,523 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 155.60227355220965}
2023-07-02 10:33:17,524 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:17,525 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.287999
2023-07-02 10:33:17,525 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:17,525 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:17,545 [fs_likelihood.fslikelihood] Computed log-likelihood = -29.7348
2023-07-02 10:33:17,545 [model] Computed derived parameters: {}
2023-07-02 10:33:17,545 [model] Posterior to be computed for parameters {'Omega_m': 0.26799843593273476, 'b1': -0.06319943150551888}
2023-07-02 10:33:17,545 [prior] Evaluating prior at array([ 0.26799844, -0.06319943])
2023-07-02 10:33:17,545 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:17,545 [model] Posterior to be computed for parameters {'Omega_m': 0.2591363027905965, 'b1': 0.600728251405974}
2023-07-02 10:33:17,545 [prior] Evaluating prior at array([0.2591363 , 0.60072825])
2023-07-02 10:33:17,546 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:17,546 [model] Got input parameters: {'Omega_m': 0.2591363027905965, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:17,546 [classy] Got parameters {'Omega_m': 0.2591363027905965, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:17,546 [classy] Computing new state
2023-07-02 10:33:17,546 [classy] Setting parameters: {'Omega_m': 0.2591363027905965, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:17,589 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 154.2140316674361}
2023-07-02 10:33:17,589 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:17,591 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.200961
2023-07-02 10:33:17,591 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:17,591 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:17,611 [fs_likelihood.fslikelihood] Computed log-likelihood = -19.3967
2023-07-02 10:33:17,611 [model] Computed derived parameters: {}
2023-07-02 10:33:17,611 [model] Posterior to be computed for parameters {'Omega_m': 0.26799843593273476, 'b1': 0.7327582733801161}
2023-07-02 10:33:17,611 [prior] Evaluating prior at array([0.26799844, 0.73275827])
2023-07-02 10:33:17,611 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:17,611 [model] Got input parameters: {'Omega_m': 0.26799843593273476, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.7327582733801161, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:17,612 [classy] Got parameters {'Omega_m': 0.26799843593273476, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:17,612 [classy] Re-using computed results
2023-07-02 10:33:17,612 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.97867406055138}
2023-07-02 10:33:17,612 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:17,612 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.7327582733801161, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:17,612 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:17,631 [fs_likelihood.fslikelihood] Computed log-likelihood = -76.1298
2023-07-02 10:33:17,631 [model] Computed derived parameters: {}
2023-07-02 10:33:17,631 [model] Posterior to be computed for parameters {'Omega_m': 0.2673629437719531, 'b1': 0.600728251405974}
2023-07-02 10:33:17,632 [prior] Evaluating prior at array([0.26736294, 0.60072825])
2023-07-02 10:33:17,632 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:17,632 [model] Got input parameters: {'Omega_m': 0.2673629437719531, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:17,632 [classy] Got parameters {'Omega_m': 0.2673629437719531, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:17,632 [classy] Computing new state
2023-07-02 10:33:17,632 [classy] Setting parameters: {'Omega_m': 0.2673629437719531, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:17,676 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.06611034114562}
2023-07-02 10:33:17,676 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:17,677 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.140607
2023-07-02 10:33:17,677 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:17,677 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:17,697 [fs_likelihood.fslikelihood] Computed log-likelihood = -13.3083
2023-07-02 10:33:17,697 [model] Computed derived parameters: {}
2023-07-02 10:33:17,697 [mcmc] New sample, #13:
Omega_m:0.2679984, b1:0.6007283
2023-07-02 10:33:17,697 [model] Posterior to be computed for parameters {'Omega_m': 0.2673629437719531, 'b1': 1.1809589973077994}
2023-07-02 10:33:17,697 [prior] Evaluating prior at array([0.26736294, 1.180959 ])
2023-07-02 10:33:17,697 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:17,697 [model] Got input parameters: {'Omega_m': 0.2673629437719531, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.1809589973077994, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:17,697 [classy] Got parameters {'Omega_m': 0.2673629437719531, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:17,698 [classy] Re-using computed results
2023-07-02 10:33:17,698 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.06611034114562}
2023-07-02 10:33:17,698 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:17,698 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.1809589973077994, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:17,698 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:17,717 [fs_likelihood.fslikelihood] Computed log-likelihood = -1533.3
2023-07-02 10:33:17,717 [model] Computed derived parameters: {}
2023-07-02 10:33:17,718 [model] Posterior to be computed for parameters {'Omega_m': 0.28501101895354913, 'b1': 0.600728251405974}
2023-07-02 10:33:17,718 [prior] Evaluating prior at array([0.28501102, 0.60072825])
2023-07-02 10:33:17,718 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:17,718 [model] Got input parameters: {'Omega_m': 0.28501101895354913, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:17,718 [classy] Got parameters {'Omega_m': 0.28501101895354913, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:17,718 [classy] Computing new state
2023-07-02 10:33:17,718 [classy] Setting parameters: {'Omega_m': 0.28501101895354913, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:17,762 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.70108148648268}
2023-07-02 10:33:17,762 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:17,764 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0498515
2023-07-02 10:33:17,764 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:17,764 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:17,783 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.65868
2023-07-02 10:33:17,783 [model] Computed derived parameters: {}
2023-07-02 10:33:17,783 [mcmc] New sample, #14:
Omega_m:0.2673629, b1:0.6007283
2023-07-02 10:33:17,784 [model] Posterior to be computed for parameters {'Omega_m': 0.28501101895354913, 'b1': 0.9471683789005036}
2023-07-02 10:33:17,784 [prior] Evaluating prior at array([0.28501102, 0.94716838])
2023-07-02 10:33:17,784 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:17,784 [model] Got input parameters: {'Omega_m': 0.28501101895354913, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.9471683789005036, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:17,784 [classy] Got parameters {'Omega_m': 0.28501101895354913, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:17,784 [classy] Re-using computed results
2023-07-02 10:33:17,784 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.70108148648268}
2023-07-02 10:33:17,784 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:17,784 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.9471683789005036, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:17,784 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:17,804 [fs_likelihood.fslikelihood] Computed log-likelihood = -580.106
2023-07-02 10:33:17,804 [model] Computed derived parameters: {}
2023-07-02 10:33:17,804 [model] Posterior to be computed for parameters {'Omega_m': 0.2910488232832707, 'b1': 0.600728251405974}
2023-07-02 10:33:17,804 [prior] Evaluating prior at array([0.29104882, 0.60072825])
2023-07-02 10:33:17,804 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:17,804 [model] Got input parameters: {'Omega_m': 0.2910488232832707, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:17,804 [classy] Got parameters {'Omega_m': 0.2910488232832707, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:17,804 [classy] Computing new state
2023-07-02 10:33:17,804 [classy] Setting parameters: {'Omega_m': 0.2910488232832707, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:17,848 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.92080070373154}
2023-07-02 10:33:17,848 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:17,850 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0299544
2023-07-02 10:33:17,850 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:17,850 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:17,870 [fs_likelihood.fslikelihood] Computed log-likelihood = -9.70215
2023-07-02 10:33:17,870 [model] Computed derived parameters: {}
2023-07-02 10:33:17,870 [model] Posterior to be computed for parameters {'Omega_m': 0.28501101895354913, 'b1': 0.12874436354977098}
2023-07-02 10:33:17,870 [prior] Evaluating prior at array([0.28501102, 0.12874436])
2023-07-02 10:33:17,870 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:17,870 [model] Got input parameters: {'Omega_m': 0.28501101895354913, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.12874436354977098, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:17,870 [classy] Got parameters {'Omega_m': 0.28501101895354913, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:17,870 [classy] Re-using computed results
2023-07-02 10:33:17,870 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.70108148648268}
2023-07-02 10:33:17,870 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:17,870 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.12874436354977098, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:17,870 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:17,890 [fs_likelihood.fslikelihood] Computed log-likelihood = -305.159
2023-07-02 10:33:17,890 [model] Computed derived parameters: {}
2023-07-02 10:33:17,890 [model] Posterior to be computed for parameters {'Omega_m': 0.2800024670833354, 'b1': 0.600728251405974}
2023-07-02 10:33:17,890 [prior] Evaluating prior at array([0.28000247, 0.60072825])
2023-07-02 10:33:17,890 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:17,890 [model] Got input parameters: {'Omega_m': 0.2800024670833354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:17,890 [classy] Got parameters {'Omega_m': 0.2800024670833354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:17,890 [classy] Computing new state
2023-07-02 10:33:17,890 [classy] Setting parameters: {'Omega_m': 0.2800024670833354, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:17,934 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.35928062445623}
2023-07-02 10:33:17,934 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:17,936 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0705304
2023-07-02 10:33:17,936 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:17,936 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:17,955 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.81218
2023-07-02 10:33:17,956 [model] Computed derived parameters: {}
2023-07-02 10:33:17,956 [mcmc] New sample, #15:
Omega_m:0.285011, b1:0.6007283
2023-07-02 10:33:17,956 [model] Posterior to be computed for parameters {'Omega_m': 0.2800024670833354, 'b1': 1.5773709427986682}
2023-07-02 10:33:17,956 [prior] Evaluating prior at array([0.28000247, 1.57737094])
2023-07-02 10:33:17,956 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:17,956 [model] Got input parameters: {'Omega_m': 0.2800024670833354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.5773709427986682, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:17,956 [classy] Got parameters {'Omega_m': 0.2800024670833354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:17,956 [classy] Re-using computed results
2023-07-02 10:33:17,956 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.35928062445623}
2023-07-02 10:33:17,956 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:17,956 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.5773709427986682, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:17,956 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:17,976 [fs_likelihood.fslikelihood] Computed log-likelihood = -6189.92
2023-07-02 10:33:17,976 [model] Computed derived parameters: {}
2023-07-02 10:33:17,976 [model] Posterior to be computed for parameters {'Omega_m': 0.2719862039772243, 'b1': 0.600728251405974}
2023-07-02 10:33:17,976 [prior] Evaluating prior at array([0.2719862 , 0.60072825])
2023-07-02 10:33:17,976 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:17,976 [model] Got input parameters: {'Omega_m': 0.2719862039772243, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:17,976 [classy] Got parameters {'Omega_m': 0.2719862039772243, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:17,976 [classy] Computing new state
2023-07-02 10:33:17,976 [classy] Setting parameters: {'Omega_m': 0.2719862039772243, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:18,020 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.43395664695288}
2023-07-02 10:33:18,020 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:18,022 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.111896
2023-07-02 10:33:18,022 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:18,022 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:18,041 [fs_likelihood.fslikelihood] Computed log-likelihood = -10.9811
2023-07-02 10:33:18,041 [model] Computed derived parameters: {}
2023-07-02 10:33:18,042 [model] Posterior to be computed for parameters {'Omega_m': 0.2800024670833354, 'b1': 1.6541951931372925}
2023-07-02 10:33:18,042 [prior] Evaluating prior at array([0.28000247, 1.65419519])
2023-07-02 10:33:18,042 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:18,042 [model] Got input parameters: {'Omega_m': 0.2800024670833354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.6541951931372925, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:18,042 [classy] Got parameters {'Omega_m': 0.2800024670833354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:18,042 [classy] Re-using computed results
2023-07-02 10:33:18,042 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.35928062445623}
2023-07-02 10:33:18,042 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:18,042 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.6541951931372925, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:18,042 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:18,063 [fs_likelihood.fslikelihood] Computed log-likelihood = -7553.62
2023-07-02 10:33:18,063 [model] Computed derived parameters: {}
2023-07-02 10:33:18,063 [model] Posterior to be computed for parameters {'Omega_m': 0.29501559010083983, 'b1': 0.600728251405974}
2023-07-02 10:33:18,063 [prior] Evaluating prior at array([0.29501559, 0.60072825])
2023-07-02 10:33:18,063 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:18,063 [model] Got input parameters: {'Omega_m': 0.29501559010083983, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:18,063 [classy] Got parameters {'Omega_m': 0.29501559010083983, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:18,063 [classy] Computing new state
2023-07-02 10:33:18,063 [classy] Setting parameters: {'Omega_m': 0.29501559010083983, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:18,107 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.41576250430415}
2023-07-02 10:33:18,107 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:18,109 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0197601
2023-07-02 10:33:18,109 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:18,109 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:18,129 [fs_likelihood.fslikelihood] Computed log-likelihood = -11.1187
2023-07-02 10:33:18,129 [model] Computed derived parameters: {}
2023-07-02 10:33:18,129 [model] Posterior to be computed for parameters {'Omega_m': 0.2800024670833354, 'b1': 0.1136152282061541}
2023-07-02 10:33:18,129 [prior] Evaluating prior at array([0.28000247, 0.11361523])
2023-07-02 10:33:18,130 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:18,130 [model] Got input parameters: {'Omega_m': 0.2800024670833354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.1136152282061541, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:18,130 [classy] Got parameters {'Omega_m': 0.2800024670833354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:18,130 [classy] Re-using computed results
2023-07-02 10:33:18,130 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.35928062445623}
2023-07-02 10:33:18,130 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:18,130 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.1136152282061541, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:18,130 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:18,150 [fs_likelihood.fslikelihood] Computed log-likelihood = -331.838
2023-07-02 10:33:18,150 [model] Computed derived parameters: {}
2023-07-02 10:33:18,150 [model] Posterior to be computed for parameters {'Omega_m': 0.26638360771154507, 'b1': 0.600728251405974}
2023-07-02 10:33:18,150 [prior] Evaluating prior at array([0.26638361, 0.60072825])
2023-07-02 10:33:18,150 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:18,150 [model] Got input parameters: {'Omega_m': 0.26638360771154507, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:18,150 [classy] Got parameters {'Omega_m': 0.26638360771154507, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:18,150 [classy] Computing new state
2023-07-02 10:33:18,150 [classy] Setting parameters: {'Omega_m': 0.26638360771154507, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:18,194 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.20119947178603}
2023-07-02 10:33:18,194 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:18,196 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.14716
2023-07-02 10:33:18,196 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:18,196 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:18,216 [fs_likelihood.fslikelihood] Computed log-likelihood = -13.9024
2023-07-02 10:33:18,216 [model] Computed derived parameters: {}
2023-07-02 10:33:18,216 [model] Posterior to be computed for parameters {'Omega_m': 0.2800024670833354, 'b1': 1.1323255545419308}
2023-07-02 10:33:18,216 [prior] Evaluating prior at array([0.28000247, 1.13232555])
2023-07-02 10:33:18,216 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:18,216 [model] Got input parameters: {'Omega_m': 0.2800024670833354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.1323255545419308, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:18,216 [classy] Got parameters {'Omega_m': 0.2800024670833354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:18,216 [classy] Re-using computed results
2023-07-02 10:33:18,216 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.35928062445623}
2023-07-02 10:33:18,216 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:18,216 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.1323255545419308, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:18,216 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:18,235 [fs_likelihood.fslikelihood] Computed log-likelihood = -1397.53
2023-07-02 10:33:18,236 [model] Computed derived parameters: {}
2023-07-02 10:33:18,236 [model] Posterior to be computed for parameters {'Omega_m': 0.2717608427172804, 'b1': 0.600728251405974}
2023-07-02 10:33:18,236 [prior] Evaluating prior at array([0.27176084, 0.60072825])
2023-07-02 10:33:18,236 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:18,236 [model] Got input parameters: {'Omega_m': 0.2717608427172804, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:18,236 [classy] Got parameters {'Omega_m': 0.2717608427172804, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:18,236 [classy] Computing new state
2023-07-02 10:33:18,236 [classy] Setting parameters: {'Omega_m': 0.2717608427172804, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:18,280 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.4645612571393}
2023-07-02 10:33:18,280 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:18,282 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.113212
2023-07-02 10:33:18,282 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:18,282 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:18,301 [fs_likelihood.fslikelihood] Computed log-likelihood = -11.0763
2023-07-02 10:33:18,301 [model] Computed derived parameters: {}
2023-07-02 10:33:18,301 [model] Posterior to be computed for parameters {'Omega_m': 0.2800024670833354, 'b1': 1.4057531596575807}
2023-07-02 10:33:18,301 [prior] Evaluating prior at array([0.28000247, 1.40575316])
2023-07-02 10:33:18,302 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:18,302 [model] Got input parameters: {'Omega_m': 0.2800024670833354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.4057531596575807, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:18,302 [classy] Got parameters {'Omega_m': 0.2800024670833354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:18,302 [classy] Re-using computed results
2023-07-02 10:33:18,302 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.35928062445623}
2023-07-02 10:33:18,302 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:18,302 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.4057531596575807, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:18,302 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:18,322 [fs_likelihood.fslikelihood] Computed log-likelihood = -3777.39
2023-07-02 10:33:18,322 [model] Computed derived parameters: {}
2023-07-02 10:33:18,322 [model] Posterior to be computed for parameters {'Omega_m': 0.2689337940628663, 'b1': 0.600728251405974}
2023-07-02 10:33:18,322 [prior] Evaluating prior at array([0.26893379, 0.60072825])
2023-07-02 10:33:18,322 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:18,322 [model] Got input parameters: {'Omega_m': 0.2689337940628663, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:18,322 [classy] Got parameters {'Omega_m': 0.2689337940628663, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:18,322 [classy] Computing new state
2023-07-02 10:33:18,322 [classy] Setting parameters: {'Omega_m': 0.2689337940628663, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:18,366 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.85029604885995}
2023-07-02 10:33:18,366 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:18,368 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.130442
2023-07-02 10:33:18,368 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:18,368 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:18,387 [fs_likelihood.fslikelihood] Computed log-likelihood = -12.4293
2023-07-02 10:33:18,387 [model] Computed derived parameters: {}
2023-07-02 10:33:18,387 [model] Posterior to be computed for parameters {'Omega_m': 0.2800024670833354, 'b1': 0.3696776200111712}
2023-07-02 10:33:18,387 [prior] Evaluating prior at array([0.28000247, 0.36967762])
2023-07-02 10:33:18,387 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:18,387 [model] Got input parameters: {'Omega_m': 0.2800024670833354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.3696776200111712, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:18,387 [classy] Got parameters {'Omega_m': 0.2800024670833354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:18,387 [classy] Re-using computed results
2023-07-02 10:33:18,387 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.35928062445623}
2023-07-02 10:33:18,387 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:18,387 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.3696776200111712, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:18,387 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:18,407 [fs_likelihood.fslikelihood] Computed log-likelihood = -85.3618
2023-07-02 10:33:18,407 [model] Computed derived parameters: {}
2023-07-02 10:33:18,407 [model] Posterior to be computed for parameters {'Omega_m': 0.29901708086262907, 'b1': 0.600728251405974}
2023-07-02 10:33:18,407 [prior] Evaluating prior at array([0.29901708, 0.60072825])
2023-07-02 10:33:18,407 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:18,407 [model] Got input parameters: {'Omega_m': 0.29901708086262907, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:18,407 [classy] Got parameters {'Omega_m': 0.29901708086262907, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:18,407 [classy] Computing new state
2023-07-02 10:33:18,407 [classy] Setting parameters: {'Omega_m': 0.29901708086262907, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:18,452 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.9122456701418}
2023-07-02 10:33:18,452 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:18,454 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0117071
2023-07-02 10:33:18,454 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.600728251405974, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:18,454 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:18,473 [fs_likelihood.fslikelihood] Computed log-likelihood = -13.135
2023-07-02 10:33:18,473 [model] Computed derived parameters: {}
2023-07-02 10:33:18,474 [model] Posterior to be computed for parameters {'Omega_m': 0.2800024670833354, 'b1': 0.5641542472169249}
2023-07-02 10:33:18,474 [prior] Evaluating prior at array([0.28000247, 0.56415425])
2023-07-02 10:33:18,474 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:18,474 [model] Got input parameters: {'Omega_m': 0.2800024670833354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:18,474 [classy] Got parameters {'Omega_m': 0.2800024670833354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:18,474 [classy] Re-using computed results
2023-07-02 10:33:18,474 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.35928062445623}
2023-07-02 10:33:18,474 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:18,474 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:18,474 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:18,493 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.14193
2023-07-02 10:33:18,493 [model] Computed derived parameters: {}
2023-07-02 10:33:18,494 [mcmc] New sample, #16:
Omega_m:0.2800025, b1:0.6007283
2023-07-02 10:33:18,494 [model] Posterior to be computed for parameters {'Omega_m': 0.28115025895647344, 'b1': 0.5641542472169249}
2023-07-02 10:33:18,494 [prior] Evaluating prior at array([0.28115026, 0.56415425])
2023-07-02 10:33:18,494 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:18,494 [model] Got input parameters: {'Omega_m': 0.28115025895647344, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:18,494 [classy] Got parameters {'Omega_m': 0.28115025895647344, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:18,494 [classy] Computing new state
2023-07-02 10:33:18,494 [classy] Setting parameters: {'Omega_m': 0.28115025895647344, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:18,538 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.20755764461194}
2023-07-02 10:33:18,538 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:18,539 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0654488
2023-07-02 10:33:18,540 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:18,540 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:18,559 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.60338
2023-07-02 10:33:18,559 [model] Computed derived parameters: {}
2023-07-02 10:33:18,559 [mcmc] New sample, #17:
Omega_m:0.2800025, b1:0.5641542
2023-07-02 10:33:18,559 [model] Posterior to be computed for parameters {'Omega_m': 0.28115025895647344, 'b1': -2.012416078758141}
2023-07-02 10:33:18,559 [prior] Evaluating prior at array([ 0.28115026, -2.01241608])
2023-07-02 10:33:18,559 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:18,560 [model] Posterior to be computed for parameters {'Omega_m': 0.29063803593301774, 'b1': 0.5641542472169249}
2023-07-02 10:33:18,560 [prior] Evaluating prior at array([0.29063804, 0.56415425])
2023-07-02 10:33:18,560 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:18,560 [model] Got input parameters: {'Omega_m': 0.29063803593301774, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:18,560 [classy] Got parameters {'Omega_m': 0.29063803593301774, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:18,560 [classy] Computing new state
2023-07-02 10:33:18,560 [classy] Setting parameters: {'Omega_m': 0.29063803593301774, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:18,605 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.97344050117687}
2023-07-02 10:33:18,605 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:18,606 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0311386
2023-07-02 10:33:18,606 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:18,606 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:18,626 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.85931
2023-07-02 10:33:18,626 [model] Computed derived parameters: {}
2023-07-02 10:33:18,626 [mcmc] New sample, #18:
Omega_m:0.2811503, b1:0.5641542
2023-07-02 10:33:18,627 [model] Posterior to be computed for parameters {'Omega_m': 0.29063803593301774, 'b1': 0.11978222459916943}
2023-07-02 10:33:18,627 [prior] Evaluating prior at array([0.29063804, 0.11978222])
2023-07-02 10:33:18,627 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:18,627 [model] Got input parameters: {'Omega_m': 0.29063803593301774, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.11978222459916943, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:18,627 [classy] Got parameters {'Omega_m': 0.29063803593301774, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:18,627 [classy] Re-using computed results
2023-07-02 10:33:18,627 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.97344050117687}
2023-07-02 10:33:18,627 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:18,627 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.11978222459916943, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:18,627 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:18,647 [fs_likelihood.fslikelihood] Computed log-likelihood = -303.604
2023-07-02 10:33:18,647 [model] Computed derived parameters: {}
2023-07-02 10:33:18,647 [model] Posterior to be computed for parameters {'Omega_m': 0.2777024260879715, 'b1': 0.5641542472169249}
2023-07-02 10:33:18,647 [prior] Evaluating prior at array([0.27770243, 0.56415425])
2023-07-02 10:33:18,647 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:18,647 [model] Got input parameters: {'Omega_m': 0.2777024260879715, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:18,647 [classy] Got parameters {'Omega_m': 0.2777024260879715, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:18,647 [classy] Computing new state
2023-07-02 10:33:18,647 [classy] Setting parameters: {'Omega_m': 0.2777024260879715, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:18,691 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.66491972708485}
2023-07-02 10:33:18,691 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:18,693 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0813379
2023-07-02 10:33:18,693 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:18,693 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:18,712 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.3553
2023-07-02 10:33:18,712 [model] Computed derived parameters: {}
2023-07-02 10:33:18,712 [model] Posterior to be computed for parameters {'Omega_m': 0.29063803593301774, 'b1': 1.111948483680984}
2023-07-02 10:33:18,712 [prior] Evaluating prior at array([0.29063804, 1.11194848])
2023-07-02 10:33:18,713 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:18,713 [model] Got input parameters: {'Omega_m': 0.29063803593301774, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.111948483680984, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:18,713 [classy] Got parameters {'Omega_m': 0.29063803593301774, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:18,713 [classy] Re-using computed results
2023-07-02 10:33:18,713 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.97344050117687}
2023-07-02 10:33:18,713 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:18,713 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.111948483680984, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:18,713 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:18,732 [fs_likelihood.fslikelihood] Computed log-likelihood = -1410.25
2023-07-02 10:33:18,732 [model] Computed derived parameters: {}
2023-07-02 10:33:18,732 [model] Posterior to be computed for parameters {'Omega_m': 0.2832057139110705, 'b1': 0.5641542472169249}
2023-07-02 10:33:18,733 [prior] Evaluating prior at array([0.28320571, 0.56415425])
2023-07-02 10:33:18,733 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:18,733 [model] Got input parameters: {'Omega_m': 0.2832057139110705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:18,733 [classy] Got parameters {'Omega_m': 0.2832057139110705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:18,733 [classy] Computing new state
2023-07-02 10:33:18,733 [classy] Setting parameters: {'Omega_m': 0.2832057139110705, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:18,777 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.93717686683792}
2023-07-02 10:33:18,777 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:18,779 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0568605
2023-07-02 10:33:18,779 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:18,779 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:18,798 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.75039
2023-07-02 10:33:18,798 [model] Computed derived parameters: {}
2023-07-02 10:33:18,799 [model] Posterior to be computed for parameters {'Omega_m': 0.29063803593301774, 'b1': -1.1661240927395355}
2023-07-02 10:33:18,799 [prior] Evaluating prior at array([ 0.29063804, -1.16612409])
2023-07-02 10:33:18,799 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:18,799 [model] Posterior to be computed for parameters {'Omega_m': 0.2964020393345352, 'b1': 0.5641542472169249}
2023-07-02 10:33:18,799 [prior] Evaluating prior at array([0.29640204, 0.56415425])
2023-07-02 10:33:18,799 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:18,799 [model] Got input parameters: {'Omega_m': 0.2964020393345352, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:18,799 [classy] Got parameters {'Omega_m': 0.2964020393345352, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:18,799 [classy] Computing new state
2023-07-02 10:33:18,799 [classy] Setting parameters: {'Omega_m': 0.2964020393345352, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:18,843 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.24063190904653}
2023-07-02 10:33:18,843 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:18,845 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0167196
2023-07-02 10:33:18,845 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:18,845 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:18,865 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.6799
2023-07-02 10:33:18,865 [model] Computed derived parameters: {}
2023-07-02 10:33:18,865 [mcmc] New sample, #19:
Omega_m:0.290638, b1:0.5641542
2023-07-02 10:33:18,865 [model] Posterior to be computed for parameters {'Omega_m': 0.2964020393345352, 'b1': 0.39815527679972185}
2023-07-02 10:33:18,865 [prior] Evaluating prior at array([0.29640204, 0.39815528])
2023-07-02 10:33:18,865 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:18,865 [model] Got input parameters: {'Omega_m': 0.2964020393345352, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.39815527679972185, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:18,865 [classy] Got parameters {'Omega_m': 0.2964020393345352, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:18,865 [classy] Re-using computed results
2023-07-02 10:33:18,865 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.24063190904653}
2023-07-02 10:33:18,865 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:18,865 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.39815527679972185, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:18,865 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:18,885 [fs_likelihood.fslikelihood] Computed log-likelihood = -41.8102
2023-07-02 10:33:18,885 [model] Computed derived parameters: {}
2023-07-02 10:33:18,885 [model] Posterior to be computed for parameters {'Omega_m': 0.2939256037104231, 'b1': 0.5641542472169249}
2023-07-02 10:33:18,885 [prior] Evaluating prior at array([0.2939256 , 0.56415425])
2023-07-02 10:33:18,885 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:18,885 [model] Got input parameters: {'Omega_m': 0.2939256037104231, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:18,885 [classy] Got parameters {'Omega_m': 0.2939256037104231, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:18,885 [classy] Computing new state
2023-07-02 10:33:18,885 [classy] Setting parameters: {'Omega_m': 0.2939256037104231, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:18,929 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.55394635761508}
2023-07-02 10:33:18,929 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:18,931 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0223391
2023-07-02 10:33:18,931 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:18,931 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:18,950 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.61921
2023-07-02 10:33:18,950 [model] Computed derived parameters: {}
2023-07-02 10:33:18,950 [mcmc] New sample, #20:
Omega_m:0.296402, b1:0.5641542
2023-07-02 10:33:18,951 [model] Posterior to be computed for parameters {'Omega_m': 0.2939256037104231, 'b1': 0.013091685842807177}
2023-07-02 10:33:18,951 [prior] Evaluating prior at array([0.2939256 , 0.01309169])
2023-07-02 10:33:18,951 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:18,951 [model] Got input parameters: {'Omega_m': 0.2939256037104231, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.013091685842807177, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:18,951 [classy] Got parameters {'Omega_m': 0.2939256037104231, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:18,951 [classy] Re-using computed results
2023-07-02 10:33:18,951 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.55394635761508}
2023-07-02 10:33:18,951 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:18,951 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.013091685842807177, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:18,951 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:18,971 [fs_likelihood.fslikelihood] Computed log-likelihood = -415.081
2023-07-02 10:33:18,971 [model] Computed derived parameters: {}
2023-07-02 10:33:18,971 [model] Posterior to be computed for parameters {'Omega_m': 0.28103501242931417, 'b1': 0.5641542472169249}
2023-07-02 10:33:18,971 [prior] Evaluating prior at array([0.28103501, 0.56415425])
2023-07-02 10:33:18,971 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:18,971 [model] Got input parameters: {'Omega_m': 0.28103501242931417, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:18,971 [classy] Got parameters {'Omega_m': 0.28103501242931417, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:18,971 [classy] Computing new state
2023-07-02 10:33:18,971 [classy] Setting parameters: {'Omega_m': 0.28103501242931417, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:19,015 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.22277016819226}
2023-07-02 10:33:19,015 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:19,017 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0659499
2023-07-02 10:33:19,017 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:19,017 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:19,037 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.65544
2023-07-02 10:33:19,037 [model] Computed derived parameters: {}
2023-07-02 10:33:19,037 [model] Posterior to be computed for parameters {'Omega_m': 0.2939256037104231, 'b1': 0.4922984444056192}
2023-07-02 10:33:19,037 [prior] Evaluating prior at array([0.2939256 , 0.49229844])
2023-07-02 10:33:19,037 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:19,037 [model] Got input parameters: {'Omega_m': 0.2939256037104231, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4922984444056192, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:19,037 [classy] Got parameters {'Omega_m': 0.2939256037104231, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:19,037 [classy] Re-using computed results
2023-07-02 10:33:19,037 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.55394635761508}
2023-07-02 10:33:19,037 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:19,037 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4922984444056192, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:19,037 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:19,057 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.25311
2023-07-02 10:33:19,057 [model] Computed derived parameters: {}
2023-07-02 10:33:19,057 [model] Posterior to be computed for parameters {'Omega_m': 0.2907050934637481, 'b1': 0.5641542472169249}
2023-07-02 10:33:19,057 [prior] Evaluating prior at array([0.29070509, 0.56415425])
2023-07-02 10:33:19,057 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:19,057 [model] Got input parameters: {'Omega_m': 0.2907050934637481, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:19,058 [classy] Got parameters {'Omega_m': 0.2907050934637481, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:19,058 [classy] Computing new state
2023-07-02 10:33:19,058 [classy] Setting parameters: {'Omega_m': 0.2907050934637481, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:19,102 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.96484413873634}
2023-07-02 10:33:19,102 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:19,103 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0309436
2023-07-02 10:33:19,103 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:19,103 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:19,125 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.85076
2023-07-02 10:33:19,125 [model] Computed derived parameters: {}
2023-07-02 10:33:19,125 [mcmc] New sample, #21:
Omega_m:0.2939256, b1:0.5641542
2023-07-02 10:33:19,125 [model] Posterior to be computed for parameters {'Omega_m': 0.2907050934637481, 'b1': -0.9116768543470722}
2023-07-02 10:33:19,125 [prior] Evaluating prior at array([ 0.29070509, -0.91167685])
2023-07-02 10:33:19,126 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:19,126 [model] Posterior to be computed for parameters {'Omega_m': 0.2621977489060774, 'b1': 0.5641542472169249}
2023-07-02 10:33:19,126 [prior] Evaluating prior at array([0.26219775, 0.56415425])
2023-07-02 10:33:19,126 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:19,126 [model] Got input parameters: {'Omega_m': 0.2621977489060774, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:19,126 [classy] Got parameters {'Omega_m': 0.2621977489060774, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:19,126 [classy] Computing new state
2023-07-02 10:33:19,126 [classy] Setting parameters: {'Omega_m': 0.2621977489060774, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:19,171 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.7833330260691}
2023-07-02 10:33:19,171 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:19,173 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.177079
2023-07-02 10:33:19,173 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:19,173 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:19,193 [fs_likelihood.fslikelihood] Computed log-likelihood = -19.2062
2023-07-02 10:33:19,193 [model] Computed derived parameters: {}
2023-07-02 10:33:19,193 [model] Posterior to be computed for parameters {'Omega_m': 0.2907050934637481, 'b1': -0.745652029519498}
2023-07-02 10:33:19,193 [prior] Evaluating prior at array([ 0.29070509, -0.74565203])
2023-07-02 10:33:19,193 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:19,193 [model] Posterior to be computed for parameters {'Omega_m': 0.29242131069025074, 'b1': 0.5641542472169249}
2023-07-02 10:33:19,193 [prior] Evaluating prior at array([0.29242131, 0.56415425])
2023-07-02 10:33:19,193 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:19,193 [model] Got input parameters: {'Omega_m': 0.29242131069025074, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:19,193 [classy] Got parameters {'Omega_m': 0.29242131069025074, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:19,193 [classy] Computing new state
2023-07-02 10:33:19,193 [classy] Setting parameters: {'Omega_m': 0.29242131069025074, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:19,237 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.74538977626483}
2023-07-02 10:33:19,237 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:19,239 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.026174
2023-07-02 10:33:19,239 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:19,239 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:19,259 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.68368
2023-07-02 10:33:19,259 [model] Computed derived parameters: {}
2023-07-02 10:33:19,259 [mcmc] New sample, #22:
Omega_m:0.2907051, b1:0.5641542
2023-07-02 10:33:19,259 [model] Posterior to be computed for parameters {'Omega_m': 0.29242131069025074, 'b1': 0.5123966182377673}
2023-07-02 10:33:19,259 [prior] Evaluating prior at array([0.29242131, 0.51239662])
2023-07-02 10:33:19,260 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:19,260 [model] Got input parameters: {'Omega_m': 0.29242131069025074, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5123966182377673, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:19,260 [classy] Got parameters {'Omega_m': 0.29242131069025074, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:19,260 [classy] Re-using computed results
2023-07-02 10:33:19,260 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.74538977626483}
2023-07-02 10:33:19,260 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:19,260 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5123966182377673, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:19,260 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:19,280 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.42254
2023-07-02 10:33:19,280 [model] Computed derived parameters: {}
2023-07-02 10:33:19,280 [model] Posterior to be computed for parameters {'Omega_m': 0.2784923906684726, 'b1': 0.5641542472169249}
2023-07-02 10:33:19,280 [prior] Evaluating prior at array([0.27849239, 0.56415425])
2023-07-02 10:33:19,280 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:19,280 [model] Got input parameters: {'Omega_m': 0.2784923906684726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:19,280 [classy] Got parameters {'Omega_m': 0.2784923906684726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:19,281 [classy] Computing new state
2023-07-02 10:33:19,281 [classy] Setting parameters: {'Omega_m': 0.2784923906684726, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:19,324 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.55970275676412}
2023-07-02 10:33:19,324 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:19,326 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0775313
2023-07-02 10:33:19,326 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:19,326 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:19,346 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.91837
2023-07-02 10:33:19,346 [model] Computed derived parameters: {}
2023-07-02 10:33:19,346 [model] Posterior to be computed for parameters {'Omega_m': 0.29242131069025074, 'b1': -0.2808724116435116}
2023-07-02 10:33:19,346 [prior] Evaluating prior at array([ 0.29242131, -0.28087241])
2023-07-02 10:33:19,346 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:19,346 [model] Posterior to be computed for parameters {'Omega_m': 0.2948301460839422, 'b1': 0.5641542472169249}
2023-07-02 10:33:19,346 [prior] Evaluating prior at array([0.29483015, 0.56415425])
2023-07-02 10:33:19,346 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:19,346 [model] Got input parameters: {'Omega_m': 0.2948301460839422, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:19,346 [classy] Got parameters {'Omega_m': 0.2948301460839422, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:19,346 [classy] Computing new state
2023-07-02 10:33:19,346 [classy] Setting parameters: {'Omega_m': 0.2948301460839422, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:19,391 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.43924136186516}
2023-07-02 10:33:19,391 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:19,392 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0201871
2023-07-02 10:33:19,392 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:19,392 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:19,412 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.61732
2023-07-02 10:33:19,413 [model] Computed derived parameters: {}
2023-07-02 10:33:19,413 [mcmc] New sample, #23:
Omega_m:0.2924213, b1:0.5641542
2023-07-02 10:33:19,413 [model] Posterior to be computed for parameters {'Omega_m': 0.2948301460839422, 'b1': -0.9085892166087045}
2023-07-02 10:33:19,413 [prior] Evaluating prior at array([ 0.29483015, -0.90858922])
2023-07-02 10:33:19,413 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:19,413 [model] Posterior to be computed for parameters {'Omega_m': 0.30607781746448515, 'b1': 0.5641542472169249}
2023-07-02 10:33:19,413 [prior] Evaluating prior at array([0.30607782, 0.56415425])
2023-07-02 10:33:19,413 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:19,413 [model] Got input parameters: {'Omega_m': 0.30607781746448515, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:19,413 [classy] Got parameters {'Omega_m': 0.30607781746448515, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:19,413 [classy] Computing new state
2023-07-02 10:33:19,413 [classy] Setting parameters: {'Omega_m': 0.30607781746448515, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:19,458 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.038054614937}
2023-07-02 10:33:19,458 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:19,459 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00275973
2023-07-02 10:33:19,460 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:19,460 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:19,480 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.90676
2023-07-02 10:33:19,480 [model] Computed derived parameters: {}
2023-07-02 10:33:19,480 [model] Posterior to be computed for parameters {'Omega_m': 0.2948301460839422, 'b1': 0.13587497981547075}
2023-07-02 10:33:19,480 [prior] Evaluating prior at array([0.29483015, 0.13587498])
2023-07-02 10:33:19,480 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:19,480 [model] Got input parameters: {'Omega_m': 0.2948301460839422, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.13587497981547075, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:19,480 [classy] Got parameters {'Omega_m': 0.2948301460839422, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:19,480 [classy] Re-using computed results
2023-07-02 10:33:19,480 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.43924136186516}
2023-07-02 10:33:19,480 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:19,480 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.13587497981547075, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:19,480 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:19,500 [fs_likelihood.fslikelihood] Computed log-likelihood = -277.953
2023-07-02 10:33:19,500 [model] Computed derived parameters: {}
2023-07-02 10:33:19,500 [model] Posterior to be computed for parameters {'Omega_m': 0.27439333666368143, 'b1': 0.5641542472169249}
2023-07-02 10:33:19,500 [prior] Evaluating prior at array([0.27439334, 0.56415425])
2023-07-02 10:33:19,500 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:19,500 [model] Got input parameters: {'Omega_m': 0.27439333666368143, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:19,500 [classy] Got parameters {'Omega_m': 0.27439333666368143, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:19,500 [classy] Computing new state
2023-07-02 10:33:19,501 [classy] Setting parameters: {'Omega_m': 0.27439333666368143, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:19,544 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.10844810552507}
2023-07-02 10:33:19,544 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:19,546 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.098375
2023-07-02 10:33:19,546 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:19,546 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:19,566 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.41509
2023-07-02 10:33:19,566 [model] Computed derived parameters: {}
2023-07-02 10:33:19,566 [model] Posterior to be computed for parameters {'Omega_m': 0.2948301460839422, 'b1': -0.37872999904416405}
2023-07-02 10:33:19,566 [prior] Evaluating prior at array([ 0.29483015, -0.37873 ])
2023-07-02 10:33:19,566 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:19,567 [model] Posterior to be computed for parameters {'Omega_m': 0.2616583785661771, 'b1': 0.5641542472169249}
2023-07-02 10:33:19,567 [prior] Evaluating prior at array([0.26165838, 0.56415425])
2023-07-02 10:33:19,567 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:19,567 [model] Got input parameters: {'Omega_m': 0.2616583785661771, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:19,567 [classy] Got parameters {'Omega_m': 0.2616583785661771, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:19,567 [classy] Computing new state
2023-07-02 10:33:19,567 [classy] Setting parameters: {'Omega_m': 0.2616583785661771, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:19,611 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.8589102645998}
2023-07-02 10:33:19,611 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:19,612 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.181162
2023-07-02 10:33:19,612 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:19,612 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:19,632 [fs_likelihood.fslikelihood] Computed log-likelihood = -19.7997
2023-07-02 10:33:19,632 [model] Computed derived parameters: {}
2023-07-02 10:33:19,633 [model] Posterior to be computed for parameters {'Omega_m': 0.2948301460839422, 'b1': 0.24683867263038728}
2023-07-02 10:33:19,633 [prior] Evaluating prior at array([0.29483015, 0.24683867])
2023-07-02 10:33:19,633 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:19,633 [model] Got input parameters: {'Omega_m': 0.2948301460839422, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.24683867263038728, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:19,633 [classy] Got parameters {'Omega_m': 0.2948301460839422, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:19,633 [classy] Re-using computed results
2023-07-02 10:33:19,633 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.43924136186516}
2023-07-02 10:33:19,633 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:19,633 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.24683867263038728, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:19,633 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:19,653 [fs_likelihood.fslikelihood] Computed log-likelihood = -164.072
2023-07-02 10:33:19,653 [model] Computed derived parameters: {}
2023-07-02 10:33:19,653 [model] Posterior to be computed for parameters {'Omega_m': 0.2867979817404427, 'b1': 0.5641542472169249}
2023-07-02 10:33:19,653 [prior] Evaluating prior at array([0.28679798, 0.56415425])
2023-07-02 10:33:19,653 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:19,653 [model] Got input parameters: {'Omega_m': 0.2867979817404427, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:19,653 [classy] Got parameters {'Omega_m': 0.2867979817404427, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:19,653 [classy] Computing new state
2023-07-02 10:33:19,653 [classy] Setting parameters: {'Omega_m': 0.2867979817404427, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:19,697 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.46865684672377}
2023-07-02 10:33:19,697 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:19,699 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0433994
2023-07-02 10:33:19,699 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:19,699 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:19,719 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.60294
2023-07-02 10:33:19,719 [model] Computed derived parameters: {}
2023-07-02 10:33:19,719 [model] Posterior to be computed for parameters {'Omega_m': 0.2948301460839422, 'b1': 0.19366152525108582}
2023-07-02 10:33:19,719 [prior] Evaluating prior at array([0.29483015, 0.19366153])
2023-07-02 10:33:19,719 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:19,719 [model] Got input parameters: {'Omega_m': 0.2948301460839422, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.19366152525108582, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:19,720 [classy] Got parameters {'Omega_m': 0.2948301460839422, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:19,720 [classy] Re-using computed results
2023-07-02 10:33:19,720 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.43924136186516}
2023-07-02 10:33:19,720 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:19,720 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.19366152525108582, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:19,720 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:19,740 [fs_likelihood.fslikelihood] Computed log-likelihood = -216.937
2023-07-02 10:33:19,740 [model] Computed derived parameters: {}
2023-07-02 10:33:19,740 [model] Posterior to be computed for parameters {'Omega_m': 0.31167255996161713, 'b1': 0.5641542472169249}
2023-07-02 10:33:19,740 [prior] Evaluating prior at array([0.31167256, 0.56415425])
2023-07-02 10:33:19,740 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:19,740 [model] Got input parameters: {'Omega_m': 0.31167255996161713, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:19,741 [classy] Got parameters {'Omega_m': 0.31167255996161713, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:19,741 [classy] Computing new state
2023-07-02 10:33:19,741 [classy] Setting parameters: {'Omega_m': 0.31167255996161713, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:19,790 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.35787829275043}
2023-07-02 10:33:19,790 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:19,792 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000242827
2023-07-02 10:33:19,792 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:19,792 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:19,812 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.64013
2023-07-02 10:33:19,812 [model] Computed derived parameters: {}
2023-07-02 10:33:19,812 [model] Posterior to be computed for parameters {'Omega_m': 0.2948301460839422, 'b1': 1.6426111202284543}
2023-07-02 10:33:19,812 [prior] Evaluating prior at array([0.29483015, 1.64261112])
2023-07-02 10:33:19,812 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:19,812 [model] Got input parameters: {'Omega_m': 0.2948301460839422, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.6426111202284543, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:19,812 [classy] Got parameters {'Omega_m': 0.2948301460839422, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:19,812 [classy] Re-using computed results
2023-07-02 10:33:19,812 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.43924136186516}
2023-07-02 10:33:19,812 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:19,812 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.6426111202284543, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:19,812 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:19,832 [fs_likelihood.fslikelihood] Computed log-likelihood = -8069.5
2023-07-02 10:33:19,833 [model] Computed derived parameters: {}
2023-07-02 10:33:19,833 [model] Posterior to be computed for parameters {'Omega_m': 0.2945983862465899, 'b1': 0.5641542472169249}
2023-07-02 10:33:19,833 [prior] Evaluating prior at array([0.29459839, 0.56415425])
2023-07-02 10:33:19,833 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:19,833 [model] Got input parameters: {'Omega_m': 0.2945983862465899, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:19,833 [classy] Got parameters {'Omega_m': 0.2945983862465899, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:19,833 [classy] Computing new state
2023-07-02 10:33:19,833 [classy] Setting parameters: {'Omega_m': 0.2945983862465899, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:19,877 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.468603360845}
2023-07-02 10:33:19,877 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:19,879 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0207276
2023-07-02 10:33:19,879 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:19,879 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:19,899 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.61516
2023-07-02 10:33:19,899 [model] Computed derived parameters: {}
2023-07-02 10:33:19,899 [mcmc] New sample, #24:
Omega_m:0.2948301, b1:0.5641542
2023-07-02 10:33:19,899 [model] Posterior to be computed for parameters {'Omega_m': 0.2945983862465899, 'b1': 0.7746668380209869}
2023-07-02 10:33:19,899 [prior] Evaluating prior at array([0.29459839, 0.77466684])
2023-07-02 10:33:19,899 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:19,899 [model] Got input parameters: {'Omega_m': 0.2945983862465899, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.7746668380209869, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:19,899 [classy] Got parameters {'Omega_m': 0.2945983862465899, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:19,899 [classy] Re-using computed results
2023-07-02 10:33:19,899 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.468603360845}
2023-07-02 10:33:19,899 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:19,899 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.7746668380209869, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:19,900 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:19,919 [fs_likelihood.fslikelihood] Computed log-likelihood = -186.004
2023-07-02 10:33:19,919 [model] Computed derived parameters: {}
2023-07-02 10:33:19,919 [model] Posterior to be computed for parameters {'Omega_m': 0.3005330784593588, 'b1': 0.5641542472169249}
2023-07-02 10:33:19,920 [prior] Evaluating prior at array([0.30053308, 0.56415425])
2023-07-02 10:33:19,920 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:19,920 [model] Got input parameters: {'Omega_m': 0.3005330784593588, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:19,920 [classy] Got parameters {'Omega_m': 0.3005330784593588, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:19,920 [classy] Computing new state
2023-07-02 10:33:19,920 [classy] Setting parameters: {'Omega_m': 0.3005330784593588, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:19,964 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.72301580729032}
2023-07-02 10:33:19,964 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:19,965 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00922739
2023-07-02 10:33:19,965 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:19,965 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:19,986 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.24304
2023-07-02 10:33:19,986 [model] Computed derived parameters: {}
2023-07-02 10:33:19,986 [mcmc] New sample, #25:
Omega_m:0.2945984, b1:0.5641542
2023-07-02 10:33:19,986 [model] Posterior to be computed for parameters {'Omega_m': 0.3005330784593588, 'b1': -0.2128396236237371}
2023-07-02 10:33:19,986 [prior] Evaluating prior at array([ 0.30053308, -0.21283962])
2023-07-02 10:33:19,986 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:19,986 [model] Posterior to be computed for parameters {'Omega_m': 0.2804668243338576, 'b1': 0.5641542472169249}
2023-07-02 10:33:19,987 [prior] Evaluating prior at array([0.28046682, 0.56415425])
2023-07-02 10:33:19,987 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:19,987 [model] Got input parameters: {'Omega_m': 0.2804668243338576, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:19,987 [classy] Got parameters {'Omega_m': 0.2804668243338576, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:19,987 [classy] Computing new state
2023-07-02 10:33:19,987 [classy] Setting parameters: {'Omega_m': 0.2804668243338576, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:20,031 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.29783400633306}
2023-07-02 10:33:20,031 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:20,033 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0684497
2023-07-02 10:33:20,033 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:20,033 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:20,053 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.91868
2023-07-02 10:33:20,053 [model] Computed derived parameters: {}
2023-07-02 10:33:20,053 [model] Posterior to be computed for parameters {'Omega_m': 0.3005330784593588, 'b1': 1.0225938183602998}
2023-07-02 10:33:20,053 [prior] Evaluating prior at array([0.30053308, 1.02259382])
2023-07-02 10:33:20,053 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:20,053 [model] Got input parameters: {'Omega_m': 0.3005330784593588, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.0225938183602998, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:20,054 [classy] Got parameters {'Omega_m': 0.3005330784593588, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:20,054 [classy] Re-using computed results
2023-07-02 10:33:20,054 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.72301580729032}
2023-07-02 10:33:20,054 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:20,054 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.0225938183602998, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:20,054 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:20,074 [fs_likelihood.fslikelihood] Computed log-likelihood = -1028.49
2023-07-02 10:33:20,074 [model] Computed derived parameters: {}
2023-07-02 10:33:20,074 [model] Posterior to be computed for parameters {'Omega_m': 0.3001152593925499, 'b1': 0.5641542472169249}
2023-07-02 10:33:20,074 [prior] Evaluating prior at array([0.30011526, 0.56415425])
2023-07-02 10:33:20,074 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:20,074 [model] Got input parameters: {'Omega_m': 0.3001152593925499, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:20,074 [classy] Got parameters {'Omega_m': 0.3001152593925499, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:20,074 [classy] Computing new state
2023-07-02 10:33:20,074 [classy] Setting parameters: {'Omega_m': 0.3001152593925499, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:20,118 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.77508512200663}
2023-07-02 10:33:20,118 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:20,120 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00987987
2023-07-02 10:33:20,120 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:20,120 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:20,148 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.15983
2023-07-02 10:33:20,148 [model] Computed derived parameters: {}
2023-07-02 10:33:20,148 [mcmc] New sample, #26:
Omega_m:0.3005331, b1:0.5641542
2023-07-02 10:33:20,148 [model] Posterior to be computed for parameters {'Omega_m': 0.3001152593925499, 'b1': -0.1714778572676373}
2023-07-02 10:33:20,148 [prior] Evaluating prior at array([ 0.30011526, -0.17147786])
2023-07-02 10:33:20,148 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:20,149 [model] Posterior to be computed for parameters {'Omega_m': 0.2997795967688109, 'b1': 0.5641542472169249}
2023-07-02 10:33:20,149 [prior] Evaluating prior at array([0.2997796 , 0.56415425])
2023-07-02 10:33:20,149 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:20,149 [model] Got input parameters: {'Omega_m': 0.2997795967688109, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:20,149 [classy] Got parameters {'Omega_m': 0.2997795967688109, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:20,149 [classy] Computing new state
2023-07-02 10:33:20,149 [classy] Setting parameters: {'Omega_m': 0.2997795967688109, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:20,192 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.81696070230657}
2023-07-02 10:33:20,193 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:20,194 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.010421
2023-07-02 10:33:20,194 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:20,194 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:20,214 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.09726
2023-07-02 10:33:20,214 [model] Computed derived parameters: {}
2023-07-02 10:33:20,214 [mcmc] New sample, #27:
Omega_m:0.3001153, b1:0.5641542
2023-07-02 10:33:20,214 [model] Posterior to be computed for parameters {'Omega_m': 0.2997795967688109, 'b1': -1.1325434295810015}
2023-07-02 10:33:20,215 [prior] Evaluating prior at array([ 0.2997796 , -1.13254343])
2023-07-02 10:33:20,215 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:20,215 [model] Posterior to be computed for parameters {'Omega_m': 0.2905610819816365, 'b1': 0.5641542472169249}
2023-07-02 10:33:20,215 [prior] Evaluating prior at array([0.29056108, 0.56415425])
2023-07-02 10:33:20,215 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:20,215 [model] Got input parameters: {'Omega_m': 0.2905610819816365, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:20,215 [classy] Got parameters {'Omega_m': 0.2905610819816365, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:20,215 [classy] Computing new state
2023-07-02 10:33:20,215 [classy] Setting parameters: {'Omega_m': 0.2905610819816365, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:20,259 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.98330711916648}
2023-07-02 10:33:20,259 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:20,261 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.031363
2023-07-02 10:33:20,261 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:20,261 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:20,281 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.86932
2023-07-02 10:33:20,281 [model] Computed derived parameters: {}
2023-07-02 10:33:20,281 [mcmc] New sample, #28:
Omega_m:0.2997796, b1:0.5641542
2023-07-02 10:33:20,281 [model] Posterior to be computed for parameters {'Omega_m': 0.2905610819816365, 'b1': 0.8013423566117592}
2023-07-02 10:33:20,281 [prior] Evaluating prior at array([0.29056108, 0.80134236])
2023-07-02 10:33:20,281 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:20,281 [model] Got input parameters: {'Omega_m': 0.2905610819816365, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8013423566117592, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:20,281 [classy] Got parameters {'Omega_m': 0.2905610819816365, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:20,281 [classy] Re-using computed results
2023-07-02 10:33:20,281 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.98330711916648}
2023-07-02 10:33:20,281 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:20,281 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8013423566117592, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:20,281 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:20,301 [fs_likelihood.fslikelihood] Computed log-likelihood = -221.534
2023-07-02 10:33:20,301 [model] Computed derived parameters: {}
2023-07-02 10:33:20,302 [model] Posterior to be computed for parameters {'Omega_m': 0.28944174754008106, 'b1': 0.5641542472169249}
2023-07-02 10:33:20,302 [prior] Evaluating prior at array([0.28944175, 0.56415425])
2023-07-02 10:33:20,302 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:20,302 [model] Got input parameters: {'Omega_m': 0.28944174754008106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:20,302 [classy] Got parameters {'Omega_m': 0.28944174754008106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:20,302 [classy] Computing new state
2023-07-02 10:33:20,302 [classy] Setting parameters: {'Omega_m': 0.28944174754008106, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:20,346 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.12710943696197}
2023-07-02 10:33:20,346 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:20,347 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0347266
2023-07-02 10:33:20,348 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:20,348 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:20,368 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.03746
2023-07-02 10:33:20,368 [model] Computed derived parameters: {}
2023-07-02 10:33:20,368 [mcmc] New sample, #29:
Omega_m:0.2905611, b1:0.5641542
2023-07-02 10:33:20,368 [model] Posterior to be computed for parameters {'Omega_m': 0.28944174754008106, 'b1': 0.8037144210457337}
2023-07-02 10:33:20,368 [prior] Evaluating prior at array([0.28944175, 0.80371442])
2023-07-02 10:33:20,368 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:20,368 [model] Got input parameters: {'Omega_m': 0.28944174754008106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8037144210457337, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:20,368 [classy] Got parameters {'Omega_m': 0.28944174754008106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:20,368 [classy] Re-using computed results
2023-07-02 10:33:20,368 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.12710943696197}
2023-07-02 10:33:20,368 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:20,368 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8037144210457337, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:20,368 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:20,388 [fs_likelihood.fslikelihood] Computed log-likelihood = -222.234
2023-07-02 10:33:20,389 [model] Computed derived parameters: {}
2023-07-02 10:33:20,389 [model] Posterior to be computed for parameters {'Omega_m': 0.28690029986869875, 'b1': 0.5641542472169249}
2023-07-02 10:33:20,389 [prior] Evaluating prior at array([0.2869003 , 0.56415425])
2023-07-02 10:33:20,389 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:20,389 [model] Got input parameters: {'Omega_m': 0.28690029986869875, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:20,389 [classy] Got parameters {'Omega_m': 0.28690029986869875, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:20,389 [classy] Computing new state
2023-07-02 10:33:20,389 [classy] Setting parameters: {'Omega_m': 0.28690029986869875, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:20,433 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.45538929862505}
2023-07-02 10:33:20,433 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:20,434 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0430445
2023-07-02 10:33:20,434 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:20,434 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:20,455 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.57665
2023-07-02 10:33:20,455 [model] Computed derived parameters: {}
2023-07-02 10:33:20,455 [model] Posterior to be computed for parameters {'Omega_m': 0.28944174754008106, 'b1': 1.6742641404200946}
2023-07-02 10:33:20,455 [prior] Evaluating prior at array([0.28944175, 1.67426414])
2023-07-02 10:33:20,455 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:20,455 [model] Got input parameters: {'Omega_m': 0.28944174754008106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.6742641404200946, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:20,455 [classy] Got parameters {'Omega_m': 0.28944174754008106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:20,455 [classy] Re-using computed results
2023-07-02 10:33:20,455 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.12710943696197}
2023-07-02 10:33:20,455 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:20,455 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.6742641404200946, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:20,455 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:20,475 [fs_likelihood.fslikelihood] Computed log-likelihood = -8433.9
2023-07-02 10:33:20,475 [model] Computed derived parameters: {}
2023-07-02 10:33:20,475 [model] Posterior to be computed for parameters {'Omega_m': 0.32277554293051863, 'b1': 0.5641542472169249}
2023-07-02 10:33:20,475 [prior] Evaluating prior at array([0.32277554, 0.56415425])
2023-07-02 10:33:20,476 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:20,476 [model] Got input parameters: {'Omega_m': 0.32277554293051863, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:20,476 [classy] Got parameters {'Omega_m': 0.32277554293051863, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:20,476 [classy] Computing new state
2023-07-02 10:33:20,476 [classy] Setting parameters: {'Omega_m': 0.32277554293051863, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:20,520 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.03958908034917}
2023-07-02 10:33:20,520 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:20,521 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00653414
2023-07-02 10:33:20,521 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:20,521 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:20,542 [fs_likelihood.fslikelihood] Computed log-likelihood = -15.2019
2023-07-02 10:33:20,542 [model] Computed derived parameters: {}
2023-07-02 10:33:20,542 [model] Posterior to be computed for parameters {'Omega_m': 0.28944174754008106, 'b1': 1.4340643419224306}
2023-07-02 10:33:20,542 [prior] Evaluating prior at array([0.28944175, 1.43406434])
2023-07-02 10:33:20,542 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:20,542 [model] Got input parameters: {'Omega_m': 0.28944174754008106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.4340643419224306, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:20,542 [classy] Got parameters {'Omega_m': 0.28944174754008106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:20,542 [classy] Re-using computed results
2023-07-02 10:33:20,542 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.12710943696197}
2023-07-02 10:33:20,542 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:20,542 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.4340643419224306, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:20,542 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:20,563 [fs_likelihood.fslikelihood] Computed log-likelihood = -4408.03
2023-07-02 10:33:20,563 [model] Computed derived parameters: {}
2023-07-02 10:33:20,563 [model] Posterior to be computed for parameters {'Omega_m': 0.30295063089933244, 'b1': 0.5641542472169249}
2023-07-02 10:33:20,563 [prior] Evaluating prior at array([0.30295063, 0.56415425])
2023-07-02 10:33:20,563 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:20,563 [model] Got input parameters: {'Omega_m': 0.30295063089933244, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:20,563 [classy] Got parameters {'Omega_m': 0.30295063089933244, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:20,563 [classy] Computing new state
2023-07-02 10:33:20,563 [classy] Setting parameters: {'Omega_m': 0.30295063089933244, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:20,607 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.42301723965483}
2023-07-02 10:33:20,607 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:20,609 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00591048
2023-07-02 10:33:20,609 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:20,609 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:20,629 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.8405
2023-07-02 10:33:20,629 [model] Computed derived parameters: {}
2023-07-02 10:33:20,629 [mcmc] New sample, #30:
Omega_m:0.2894417, b1:0.5641542
2023-07-02 10:33:20,630 [model] Posterior to be computed for parameters {'Omega_m': 0.30295063089933244, 'b1': -0.2732113224454442}
2023-07-02 10:33:20,630 [prior] Evaluating prior at array([ 0.30295063, -0.27321132])
2023-07-02 10:33:20,630 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:20,630 [model] Posterior to be computed for parameters {'Omega_m': 0.30366844514979685, 'b1': 0.5641542472169249}
2023-07-02 10:33:20,630 [prior] Evaluating prior at array([0.30366845, 0.56415425])
2023-07-02 10:33:20,630 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:20,630 [model] Got input parameters: {'Omega_m': 0.30366844514979685, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:20,630 [classy] Got parameters {'Omega_m': 0.30366844514979685, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:20,630 [classy] Computing new state
2023-07-02 10:33:20,630 [classy] Setting parameters: {'Omega_m': 0.30366844514979685, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:20,674 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.3343464303195}
2023-07-02 10:33:20,674 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:20,676 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00507447
2023-07-02 10:33:20,676 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:20,676 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:20,696 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.05599
2023-07-02 10:33:20,697 [model] Computed derived parameters: {}
2023-07-02 10:33:20,697 [mcmc] New sample, #31:
Omega_m:0.3029506, b1:0.5641542
2023-07-02 10:33:20,697 [model] Posterior to be computed for parameters {'Omega_m': 0.30366844514979685, 'b1': 0.11577309985055517}
2023-07-02 10:33:20,697 [prior] Evaluating prior at array([0.30366845, 0.1157731 ])
2023-07-02 10:33:20,697 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:20,697 [model] Got input parameters: {'Omega_m': 0.30366844514979685, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.11577309985055517, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:20,697 [classy] Got parameters {'Omega_m': 0.30366844514979685, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:20,697 [classy] Re-using computed results
2023-07-02 10:33:20,697 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.3343464303195}
2023-07-02 10:33:20,697 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:20,697 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.11577309985055517, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:20,697 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:20,717 [fs_likelihood.fslikelihood] Computed log-likelihood = -283.026
2023-07-02 10:33:20,717 [model] Computed derived parameters: {}
2023-07-02 10:33:20,717 [model] Posterior to be computed for parameters {'Omega_m': 0.2854367779256794, 'b1': 0.5641542472169249}
2023-07-02 10:33:20,717 [prior] Evaluating prior at array([0.28543678, 0.56415425])
2023-07-02 10:33:20,718 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:20,718 [model] Got input parameters: {'Omega_m': 0.2854367779256794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:20,718 [classy] Got parameters {'Omega_m': 0.2854367779256794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:20,718 [classy] Computing new state
2023-07-02 10:33:20,718 [classy] Setting parameters: {'Omega_m': 0.2854367779256794, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:20,761 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.64559075835916}
2023-07-02 10:33:20,761 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:20,763 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0482707
2023-07-02 10:33:20,763 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:20,763 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:20,783 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.98634
2023-07-02 10:33:20,783 [model] Computed derived parameters: {}
2023-07-02 10:33:20,783 [mcmc] New sample, #32:
Omega_m:0.3036684, b1:0.5641542
2023-07-02 10:33:20,784 [model] Posterior to be computed for parameters {'Omega_m': 0.2854367779256794, 'b1': 0.42099387633952906}
2023-07-02 10:33:20,784 [prior] Evaluating prior at array([0.28543678, 0.42099388])
2023-07-02 10:33:20,784 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:20,784 [model] Got input parameters: {'Omega_m': 0.2854367779256794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42099387633952906, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:20,784 [classy] Got parameters {'Omega_m': 0.2854367779256794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:20,784 [classy] Re-using computed results
2023-07-02 10:33:20,784 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.64559075835916}
2023-07-02 10:33:20,784 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:20,784 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42099387633952906, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:20,784 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:20,804 [fs_likelihood.fslikelihood] Computed log-likelihood = -43.0887
2023-07-02 10:33:20,804 [model] Computed derived parameters: {}
2023-07-02 10:33:20,805 [model] Posterior to be computed for parameters {'Omega_m': 0.2966337824155873, 'b1': 0.5641542472169249}
2023-07-02 10:33:20,805 [prior] Evaluating prior at array([0.29663378, 0.56415425])
2023-07-02 10:33:20,805 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:20,805 [model] Got input parameters: {'Omega_m': 0.2966337824155873, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:20,805 [classy] Got parameters {'Omega_m': 0.2966337824155873, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:20,805 [classy] Computing new state
2023-07-02 10:33:20,805 [classy] Setting parameters: {'Omega_m': 0.2966337824155873, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:20,849 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.21143016255388}
2023-07-02 10:33:20,849 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:20,851 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0162375
2023-07-02 10:33:20,851 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:20,851 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:20,871 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.6962
2023-07-02 10:33:20,871 [model] Computed derived parameters: {}
2023-07-02 10:33:20,871 [mcmc] New sample, #33:
Omega_m:0.2854368, b1:0.5641542
2023-07-02 10:33:20,871 [model] Posterior to be computed for parameters {'Omega_m': 0.2966337824155873, 'b1': 0.3522189405098124}
2023-07-02 10:33:20,871 [prior] Evaluating prior at array([0.29663378, 0.35221894])
2023-07-02 10:33:20,871 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:20,871 [model] Got input parameters: {'Omega_m': 0.2966337824155873, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.3522189405098124, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:20,872 [classy] Got parameters {'Omega_m': 0.2966337824155873, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:20,872 [classy] Re-using computed results
2023-07-02 10:33:20,872 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.21143016255388}
2023-07-02 10:33:20,872 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:20,872 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.3522189405098124, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:20,872 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:20,891 [fs_likelihood.fslikelihood] Computed log-likelihood = -71.5437
2023-07-02 10:33:20,891 [model] Computed derived parameters: {}
2023-07-02 10:33:20,892 [model] Posterior to be computed for parameters {'Omega_m': 0.29448202161638226, 'b1': 0.5641542472169249}
2023-07-02 10:33:20,892 [prior] Evaluating prior at array([0.29448202, 0.56415425])
2023-07-02 10:33:20,892 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:20,892 [model] Got input parameters: {'Omega_m': 0.29448202161638226, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:20,892 [classy] Got parameters {'Omega_m': 0.29448202161638226, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:20,892 [classy] Computing new state
2023-07-02 10:33:20,892 [classy] Setting parameters: {'Omega_m': 0.29448202161638226, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:20,936 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.48335070944594}
2023-07-02 10:33:20,936 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:20,937 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0210017
2023-07-02 10:33:20,937 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:20,937 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:20,958 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.61477
2023-07-02 10:33:20,958 [model] Computed derived parameters: {}
2023-07-02 10:33:20,958 [mcmc] New sample, #34:
Omega_m:0.2966338, b1:0.5641542
2023-07-02 10:33:20,958 [model] Posterior to be computed for parameters {'Omega_m': 0.29448202161638226, 'b1': 0.47492093010750247}
2023-07-02 10:33:20,958 [prior] Evaluating prior at array([0.29448202, 0.47492093])
2023-07-02 10:33:20,958 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:20,958 [model] Got input parameters: {'Omega_m': 0.29448202161638226, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47492093010750247, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:20,958 [classy] Got parameters {'Omega_m': 0.29448202161638226, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:20,958 [classy] Re-using computed results
2023-07-02 10:33:20,958 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.48335070944594}
2023-07-02 10:33:20,958 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:20,958 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47492093010750247, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:20,959 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:20,978 [fs_likelihood.fslikelihood] Computed log-likelihood = -9.43943
2023-07-02 10:33:20,978 [model] Computed derived parameters: {}
2023-07-02 10:33:20,979 [model] Posterior to be computed for parameters {'Omega_m': 0.2821014324407688, 'b1': 0.5641542472169249}
2023-07-02 10:33:20,979 [prior] Evaluating prior at array([0.28210143, 0.56415425])
2023-07-02 10:33:20,979 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:20,979 [model] Got input parameters: {'Omega_m': 0.2821014324407688, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:20,979 [classy] Got parameters {'Omega_m': 0.2821014324407688, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:20,979 [classy] Computing new state
2023-07-02 10:33:20,979 [classy] Setting parameters: {'Omega_m': 0.2821014324407688, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:21,023 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.0822287036112}
2023-07-02 10:33:21,023 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:21,025 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0613934
2023-07-02 10:33:21,025 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:21,025 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:21,045 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.19088
2023-07-02 10:33:21,045 [model] Computed derived parameters: {}
2023-07-02 10:33:21,045 [model] Posterior to be computed for parameters {'Omega_m': 0.29448202161638226, 'b1': 1.226053315941949}
2023-07-02 10:33:21,045 [prior] Evaluating prior at array([0.29448202, 1.22605332])
2023-07-02 10:33:21,045 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:21,045 [model] Got input parameters: {'Omega_m': 0.29448202161638226, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.226053315941949, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:21,045 [classy] Got parameters {'Omega_m': 0.29448202161638226, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:21,045 [classy] Re-using computed results
2023-07-02 10:33:21,045 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.48335070944594}
2023-07-02 10:33:21,045 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:21,045 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.226053315941949, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:21,045 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:21,066 [fs_likelihood.fslikelihood] Computed log-likelihood = -2300.08
2023-07-02 10:33:21,066 [model] Computed derived parameters: {}
2023-07-02 10:33:21,066 [model] Posterior to be computed for parameters {'Omega_m': 0.31203035024093445, 'b1': 0.5641542472169249}
2023-07-02 10:33:21,066 [prior] Evaluating prior at array([0.31203035, 0.56415425])
2023-07-02 10:33:21,066 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:21,066 [model] Got input parameters: {'Omega_m': 0.31203035024093445, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:21,066 [classy] Got parameters {'Omega_m': 0.31203035024093445, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:21,067 [classy] Computing new state
2023-07-02 10:33:21,067 [classy] Setting parameters: {'Omega_m': 0.31203035024093445, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:21,110 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.31474783532698}
2023-07-02 10:33:21,110 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:21,112 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000215002
2023-07-02 10:33:21,112 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:21,112 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:21,135 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.85098
2023-07-02 10:33:21,135 [model] Computed derived parameters: {}
2023-07-02 10:33:21,135 [model] Posterior to be computed for parameters {'Omega_m': 0.29448202161638226, 'b1': 0.8280079237581743}
2023-07-02 10:33:21,135 [prior] Evaluating prior at array([0.29448202, 0.82800792])
2023-07-02 10:33:21,135 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:21,135 [model] Got input parameters: {'Omega_m': 0.29448202161638226, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8280079237581743, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:21,135 [classy] Got parameters {'Omega_m': 0.29448202161638226, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:21,135 [classy] Re-using computed results
2023-07-02 10:33:21,135 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.48335070944594}
2023-07-02 10:33:21,135 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:21,135 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8280079237581743, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:21,135 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:21,156 [fs_likelihood.fslikelihood] Computed log-likelihood = -292.563
2023-07-02 10:33:21,156 [model] Computed derived parameters: {}
2023-07-02 10:33:21,156 [model] Posterior to be computed for parameters {'Omega_m': 0.3156198531201341, 'b1': 0.5641542472169249}
2023-07-02 10:33:21,156 [prior] Evaluating prior at array([0.31561985, 0.56415425])
2023-07-02 10:33:21,157 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:21,157 [model] Got input parameters: {'Omega_m': 0.3156198531201341, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:21,157 [classy] Got parameters {'Omega_m': 0.3156198531201341, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:21,157 [classy] Computing new state
2023-07-02 10:33:21,157 [classy] Setting parameters: {'Omega_m': 0.3156198531201341, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:21,201 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.88446042732156}
2023-07-02 10:33:21,201 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:21,202 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000800791
2023-07-02 10:33:21,202 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641542472169249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:21,202 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:21,222 [fs_likelihood.fslikelihood] Computed log-likelihood = -9.206
2023-07-02 10:33:21,223 [model] Computed derived parameters: {}
2023-07-02 10:33:21,223 [model] Posterior to be computed for parameters {'Omega_m': 0.29448202161638226, 'b1': 0.5519221298133538}
2023-07-02 10:33:21,223 [prior] Evaluating prior at array([0.29448202, 0.55192213])
2023-07-02 10:33:21,223 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:21,223 [model] Got input parameters: {'Omega_m': 0.29448202161638226, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:21,223 [classy] Got parameters {'Omega_m': 0.29448202161638226, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:21,223 [classy] Re-using computed results
2023-07-02 10:33:21,223 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.48335070944594}
2023-07-02 10:33:21,223 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:21,223 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:21,223 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:21,243 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.253267
2023-07-02 10:33:21,243 [model] Computed derived parameters: {}
2023-07-02 10:33:21,243 [mcmc] New sample, #35:
Omega_m:0.294482, b1:0.5641542
2023-07-02 10:33:21,243 [model] Posterior to be computed for parameters {'Omega_m': 0.31237177930015986, 'b1': 0.5519221298133538}
2023-07-02 10:33:21,243 [prior] Evaluating prior at array([0.31237178, 0.55192213])
2023-07-02 10:33:21,244 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:21,244 [model] Got input parameters: {'Omega_m': 0.31237177930015986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:21,244 [classy] Got parameters {'Omega_m': 0.31237177930015986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:21,244 [classy] Computing new state
2023-07-02 10:33:21,244 [classy] Setting parameters: {'Omega_m': 0.31237177930015986, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:21,288 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.27363139301724}
2023-07-02 10:33:21,288 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:21,290 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00020314
2023-07-02 10:33:21,290 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:21,290 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:21,312 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.28974
2023-07-02 10:33:21,312 [model] Computed derived parameters: {}
2023-07-02 10:33:21,312 [model] Posterior to be computed for parameters {'Omega_m': 0.29448202161638226, 'b1': -0.20367294250460577}
2023-07-02 10:33:21,312 [prior] Evaluating prior at array([ 0.29448202, -0.20367294])
2023-07-02 10:33:21,312 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:21,312 [model] Posterior to be computed for parameters {'Omega_m': 0.2950824490263358, 'b1': 0.5519221298133538}
2023-07-02 10:33:21,312 [prior] Evaluating prior at array([0.29508245, 0.55192213])
2023-07-02 10:33:21,312 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:21,312 [model] Got input parameters: {'Omega_m': 0.2950824490263358, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:21,312 [classy] Got parameters {'Omega_m': 0.2950824490263358, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:21,313 [classy] Computing new state
2023-07-02 10:33:21,313 [classy] Setting parameters: {'Omega_m': 0.2950824490263358, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:21,358 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.40730383871465}
2023-07-02 10:33:21,358 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:21,360 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0196075
2023-07-02 10:33:21,360 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:21,360 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:21,380 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.184497
2023-07-02 10:33:21,380 [model] Computed derived parameters: {}
2023-07-02 10:33:21,380 [mcmc] New sample, #36:
Omega_m:0.294482, b1:0.5519221
2023-07-02 10:33:21,380 [model] Posterior to be computed for parameters {'Omega_m': 0.2950824490263358, 'b1': 0.8947225993232409}
2023-07-02 10:33:21,380 [prior] Evaluating prior at array([0.29508245, 0.8947226 ])
2023-07-02 10:33:21,380 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:21,380 [model] Got input parameters: {'Omega_m': 0.2950824490263358, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8947225993232409, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:21,380 [classy] Got parameters {'Omega_m': 0.2950824490263358, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:21,380 [classy] Re-using computed results
2023-07-02 10:33:21,380 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.40730383871465}
2023-07-02 10:33:21,380 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:21,380 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8947225993232409, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:21,380 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:21,401 [fs_likelihood.fslikelihood] Computed log-likelihood = -473.193
2023-07-02 10:33:21,401 [model] Computed derived parameters: {}
2023-07-02 10:33:21,401 [model] Posterior to be computed for parameters {'Omega_m': 0.29273405144912357, 'b1': 0.5519221298133538}
2023-07-02 10:33:21,401 [prior] Evaluating prior at array([0.29273405, 0.55192213])
2023-07-02 10:33:21,401 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:21,401 [model] Got input parameters: {'Omega_m': 0.29273405144912357, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:21,401 [classy] Got parameters {'Omega_m': 0.29273405144912357, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:21,401 [classy] Computing new state
2023-07-02 10:33:21,401 [classy] Setting parameters: {'Omega_m': 0.29273405144912357, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:21,445 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.70551824391174}
2023-07-02 10:33:21,445 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:21,447 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0253503
2023-07-02 10:33:21,447 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:21,447 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:21,468 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.520962
2023-07-02 10:33:21,468 [model] Computed derived parameters: {}
2023-07-02 10:33:21,468 [mcmc] New sample, #37:
Omega_m:0.2950824, b1:0.5519221
2023-07-02 10:33:21,469 [model] Posterior to be computed for parameters {'Omega_m': 0.29273405144912357, 'b1': 1.440711872779902}
2023-07-02 10:33:21,469 [prior] Evaluating prior at array([0.29273405, 1.44071187])
2023-07-02 10:33:21,469 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:21,469 [model] Got input parameters: {'Omega_m': 0.29273405144912357, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.440711872779902, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:21,469 [classy] Got parameters {'Omega_m': 0.29273405144912357, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:21,469 [classy] Re-using computed results
2023-07-02 10:33:21,469 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.70551824391174}
2023-07-02 10:33:21,469 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:21,469 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.440711872779902, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:21,469 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:21,490 [fs_likelihood.fslikelihood] Computed log-likelihood = -4602.06
2023-07-02 10:33:21,490 [model] Computed derived parameters: {}
2023-07-02 10:33:21,490 [model] Posterior to be computed for parameters {'Omega_m': 0.2865468251573651, 'b1': 0.5519221298133538}
2023-07-02 10:33:21,490 [prior] Evaluating prior at array([0.28654683, 0.55192213])
2023-07-02 10:33:21,490 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:21,490 [model] Got input parameters: {'Omega_m': 0.2865468251573651, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:21,490 [classy] Got parameters {'Omega_m': 0.2865468251573651, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:21,490 [classy] Computing new state
2023-07-02 10:33:21,490 [classy] Setting parameters: {'Omega_m': 0.2865468251573651, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:21,534 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.50124421138528}
2023-07-02 10:33:21,534 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:21,536 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0442771
2023-07-02 10:33:21,536 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:21,536 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:21,556 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.27575
2023-07-02 10:33:21,556 [model] Computed derived parameters: {}
2023-07-02 10:33:21,557 [model] Posterior to be computed for parameters {'Omega_m': 0.29273405144912357, 'b1': 0.6144424358556678}
2023-07-02 10:33:21,557 [prior] Evaluating prior at array([0.29273405, 0.61444244])
2023-07-02 10:33:21,557 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:21,557 [model] Got input parameters: {'Omega_m': 0.29273405144912357, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6144424358556678, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:21,557 [classy] Got parameters {'Omega_m': 0.29273405144912357, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:21,557 [classy] Re-using computed results
2023-07-02 10:33:21,557 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.70551824391174}
2023-07-02 10:33:21,557 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:21,557 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6144424358556678, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:21,557 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:21,577 [fs_likelihood.fslikelihood] Computed log-likelihood = -15.5554
2023-07-02 10:33:21,577 [model] Computed derived parameters: {}
2023-07-02 10:33:21,577 [model] Posterior to be computed for parameters {'Omega_m': 0.28360540581866, 'b1': 0.5519221298133538}
2023-07-02 10:33:21,577 [prior] Evaluating prior at array([0.28360541, 0.55192213])
2023-07-02 10:33:21,577 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:21,577 [model] Got input parameters: {'Omega_m': 0.28360540581866, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:21,577 [classy] Got parameters {'Omega_m': 0.28360540581866, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:21,577 [classy] Computing new state
2023-07-02 10:33:21,577 [classy] Setting parameters: {'Omega_m': 0.28360540581866, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:21,621 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.8847915800065}
2023-07-02 10:33:21,621 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:21,623 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0552657
2023-07-02 10:33:21,623 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:21,623 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:21,643 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.55146
2023-07-02 10:33:21,643 [model] Computed derived parameters: {}
2023-07-02 10:33:21,643 [model] Posterior to be computed for parameters {'Omega_m': 0.29273405144912357, 'b1': 0.37530129545493823}
2023-07-02 10:33:21,643 [prior] Evaluating prior at array([0.29273405, 0.3753013 ])
2023-07-02 10:33:21,644 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:21,644 [model] Got input parameters: {'Omega_m': 0.29273405144912357, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.37530129545493823, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:21,644 [classy] Got parameters {'Omega_m': 0.29273405144912357, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:21,644 [classy] Re-using computed results
2023-07-02 10:33:21,644 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.70551824391174}
2023-07-02 10:33:21,644 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:21,644 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.37530129545493823, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:21,644 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:21,665 [fs_likelihood.fslikelihood] Computed log-likelihood = -61.1255
2023-07-02 10:33:21,665 [model] Computed derived parameters: {}
2023-07-02 10:33:21,665 [model] Posterior to be computed for parameters {'Omega_m': 0.28959677171580905, 'b1': 0.5519221298133538}
2023-07-02 10:33:21,665 [prior] Evaluating prior at array([0.28959677, 0.55192213])
2023-07-02 10:33:21,666 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:21,666 [model] Got input parameters: {'Omega_m': 0.28959677171580905, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:21,666 [classy] Got parameters {'Omega_m': 0.28959677171580905, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:21,666 [classy] Computing new state
2023-07-02 10:33:21,666 [classy] Setting parameters: {'Omega_m': 0.28959677171580905, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:21,710 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.10716351986733}
2023-07-02 10:33:21,710 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:21,711 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0342498
2023-07-02 10:33:21,711 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:21,712 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:21,731 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.25342
2023-07-02 10:33:21,732 [model] Computed derived parameters: {}
2023-07-02 10:33:21,732 [model] Posterior to be computed for parameters {'Omega_m': 0.29273405144912357, 'b1': -0.6875621864722891}
2023-07-02 10:33:21,732 [prior] Evaluating prior at array([ 0.29273405, -0.68756219])
2023-07-02 10:33:21,732 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:21,732 [model] Posterior to be computed for parameters {'Omega_m': 0.2990131287426906, 'b1': 0.5519221298133538}
2023-07-02 10:33:21,732 [prior] Evaluating prior at array([0.29901313, 0.55192213])
2023-07-02 10:33:21,732 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:21,732 [model] Got input parameters: {'Omega_m': 0.2990131287426906, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:21,732 [classy] Got parameters {'Omega_m': 0.2990131287426906, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:21,732 [classy] Computing new state
2023-07-02 10:33:21,732 [classy] Setting parameters: {'Omega_m': 0.2990131287426906, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:21,776 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.91273867726886}
2023-07-02 10:33:21,776 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:21,778 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0117139
2023-07-02 10:33:21,778 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:21,778 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:21,798 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.0271319
2023-07-02 10:33:21,798 [model] Computed derived parameters: {}
2023-07-02 10:33:21,798 [mcmc] New sample, #38:
Omega_m:0.2927341, b1:0.5519221
2023-07-02 10:33:21,798 [model] Posterior to be computed for parameters {'Omega_m': 0.2990131287426906, 'b1': 1.1270812526550702}
2023-07-02 10:33:21,798 [prior] Evaluating prior at array([0.29901313, 1.12708125])
2023-07-02 10:33:21,798 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:21,799 [model] Got input parameters: {'Omega_m': 0.2990131287426906, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.1270812526550702, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:21,799 [classy] Got parameters {'Omega_m': 0.2990131287426906, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:21,799 [classy] Re-using computed results
2023-07-02 10:33:21,799 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.91273867726886}
2023-07-02 10:33:21,799 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:21,799 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.1270812526550702, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:21,799 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:21,819 [fs_likelihood.fslikelihood] Computed log-likelihood = -1622.56
2023-07-02 10:33:21,820 [model] Computed derived parameters: {}
2023-07-02 10:33:21,820 [model] Posterior to be computed for parameters {'Omega_m': 0.30444691533565776, 'b1': 0.5519221298133538}
2023-07-02 10:33:21,820 [prior] Evaluating prior at array([0.30444692, 0.55192213])
2023-07-02 10:33:21,820 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:21,820 [model] Got input parameters: {'Omega_m': 0.30444691533565776, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:21,820 [classy] Got parameters {'Omega_m': 0.30444691533565776, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:21,820 [classy] Computing new state
2023-07-02 10:33:21,820 [classy] Setting parameters: {'Omega_m': 0.30444691533565776, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:21,864 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2383900458081}
2023-07-02 10:33:21,865 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:21,866 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00424409
2023-07-02 10:33:21,866 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:21,866 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:21,886 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.646221
2023-07-02 10:33:21,886 [model] Computed derived parameters: {}
2023-07-02 10:33:21,886 [mcmc] New sample, #39:
Omega_m:0.2990131, b1:0.5519221
2023-07-02 10:33:21,886 [model] Posterior to be computed for parameters {'Omega_m': 0.30444691533565776, 'b1': -0.011779091481928128}
2023-07-02 10:33:21,886 [prior] Evaluating prior at array([ 0.30444692, -0.01177909])
2023-07-02 10:33:21,887 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:21,887 [model] Posterior to be computed for parameters {'Omega_m': 0.3108017352823357, 'b1': 0.5519221298133538}
2023-07-02 10:33:21,887 [prior] Evaluating prior at array([0.31080174, 0.55192213])
2023-07-02 10:33:21,887 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:21,887 [model] Got input parameters: {'Omega_m': 0.3108017352823357, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:21,887 [classy] Got parameters {'Omega_m': 0.3108017352823357, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:21,887 [classy] Computing new state
2023-07-02 10:33:21,887 [classy] Setting parameters: {'Omega_m': 0.3108017352823357, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:21,931 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.46303721229393}
2023-07-02 10:33:21,931 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:21,933 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000376649
2023-07-02 10:33:21,933 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:21,933 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:21,953 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.60197
2023-07-02 10:33:21,953 [model] Computed derived parameters: {}
2023-07-02 10:33:21,953 [model] Posterior to be computed for parameters {'Omega_m': 0.30444691533565776, 'b1': 0.7332293952236701}
2023-07-02 10:33:21,953 [prior] Evaluating prior at array([0.30444692, 0.7332294 ])
2023-07-02 10:33:21,954 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:21,954 [model] Got input parameters: {'Omega_m': 0.30444691533565776, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.7332293952236701, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:21,954 [classy] Got parameters {'Omega_m': 0.30444691533565776, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:21,954 [classy] Re-using computed results
2023-07-02 10:33:21,954 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2383900458081}
2023-07-02 10:33:21,954 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:21,954 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.7332293952236701, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:21,954 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:21,974 [fs_likelihood.fslikelihood] Computed log-likelihood = -147.472
2023-07-02 10:33:21,974 [model] Computed derived parameters: {}
2023-07-02 10:33:21,975 [model] Posterior to be computed for parameters {'Omega_m': 0.31362770677515484, 'b1': 0.5519221298133538}
2023-07-02 10:33:21,975 [prior] Evaluating prior at array([0.31362771, 0.55192213])
2023-07-02 10:33:21,975 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:21,975 [model] Got input parameters: {'Omega_m': 0.31362770677515484, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:21,975 [classy] Got parameters {'Omega_m': 0.31362770677515484, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:21,975 [classy] Computing new state
2023-07-02 10:33:21,975 [classy] Setting parameters: {'Omega_m': 0.31362770677515484, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:22,022 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.12272193602996}
2023-07-02 10:33:22,022 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:22,024 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000282393
2023-07-02 10:33:22,024 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:22,024 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:22,045 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.89827
2023-07-02 10:33:22,045 [model] Computed derived parameters: {}
2023-07-02 10:33:22,045 [model] Posterior to be computed for parameters {'Omega_m': 0.30444691533565776, 'b1': -0.6528175061689666}
2023-07-02 10:33:22,045 [prior] Evaluating prior at array([ 0.30444692, -0.65281751])
2023-07-02 10:33:22,045 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:22,045 [model] Posterior to be computed for parameters {'Omega_m': 0.30319807298190116, 'b1': 0.5519221298133538}
2023-07-02 10:33:22,045 [prior] Evaluating prior at array([0.30319807, 0.55192213])
2023-07-02 10:33:22,046 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:22,046 [model] Got input parameters: {'Omega_m': 0.30319807298190116, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:22,046 [classy] Got parameters {'Omega_m': 0.30319807298190116, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:22,046 [classy] Computing new state
2023-07-02 10:33:22,046 [classy] Setting parameters: {'Omega_m': 0.30319807298190116, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:22,090 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.39243020999936}
2023-07-02 10:33:22,090 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:22,092 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00561464
2023-07-02 10:33:22,092 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:22,092 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:22,112 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.418006
2023-07-02 10:33:22,112 [model] Computed derived parameters: {}
2023-07-02 10:33:22,112 [mcmc] New sample, #40:
Omega_m:0.3044469, b1:0.5519221
2023-07-02 10:33:22,112 [model] Posterior to be computed for parameters {'Omega_m': 0.30319807298190116, 'b1': 0.8967733494569461}
2023-07-02 10:33:22,112 [prior] Evaluating prior at array([0.30319807, 0.89677335])
2023-07-02 10:33:22,112 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:22,112 [model] Got input parameters: {'Omega_m': 0.30319807298190116, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8967733494569461, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:22,113 [classy] Got parameters {'Omega_m': 0.30319807298190116, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:22,113 [classy] Re-using computed results
2023-07-02 10:33:22,113 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.39243020999936}
2023-07-02 10:33:22,113 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:22,113 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8967733494569461, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:22,113 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:22,135 [fs_likelihood.fslikelihood] Computed log-likelihood = -530.458
2023-07-02 10:33:22,135 [model] Computed derived parameters: {}
2023-07-02 10:33:22,135 [model] Posterior to be computed for parameters {'Omega_m': 0.30984425966599016, 'b1': 0.5519221298133538}
2023-07-02 10:33:22,135 [prior] Evaluating prior at array([0.30984426, 0.55192213])
2023-07-02 10:33:22,135 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:22,135 [model] Got input parameters: {'Omega_m': 0.30984425966599016, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:22,135 [classy] Got parameters {'Omega_m': 0.30984425966599016, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:22,135 [classy] Computing new state
2023-07-02 10:33:22,136 [classy] Setting parameters: {'Omega_m': 0.30984425966599016, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:22,180 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.57896276336174}
2023-07-02 10:33:22,180 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:22,182 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000632534
2023-07-02 10:33:22,182 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:22,182 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:22,201 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.22233
2023-07-02 10:33:22,201 [model] Computed derived parameters: {}
2023-07-02 10:33:22,202 [model] Posterior to be computed for parameters {'Omega_m': 0.30319807298190116, 'b1': 0.5903604714629186}
2023-07-02 10:33:22,202 [prior] Evaluating prior at array([0.30319807, 0.59036047])
2023-07-02 10:33:22,202 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:22,202 [model] Got input parameters: {'Omega_m': 0.30319807298190116, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5903604714629186, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:22,202 [classy] Got parameters {'Omega_m': 0.30319807298190116, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:22,202 [classy] Re-using computed results
2023-07-02 10:33:22,202 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.39243020999936}
2023-07-02 10:33:22,202 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:22,202 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5903604714629186, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:22,202 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:22,222 [fs_likelihood.fslikelihood] Computed log-likelihood = -11.3314
2023-07-02 10:33:22,222 [model] Computed derived parameters: {}
2023-07-02 10:33:22,222 [model] Posterior to be computed for parameters {'Omega_m': 0.3008435759414654, 'b1': 0.5519221298133538}
2023-07-02 10:33:22,222 [prior] Evaluating prior at array([0.30084358, 0.55192213])
2023-07-02 10:33:22,223 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:22,223 [model] Got input parameters: {'Omega_m': 0.3008435759414654, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:22,223 [classy] Got parameters {'Omega_m': 0.3008435759414654, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:22,223 [classy] Computing new state
2023-07-02 10:33:22,223 [classy] Setting parameters: {'Omega_m': 0.3008435759414654, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:22,267 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.68436678296703}
2023-07-02 10:33:22,267 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:22,269 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00875779
2023-07-02 10:33:22,269 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:22,269 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:22,289 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.127235
2023-07-02 10:33:22,289 [model] Computed derived parameters: {}
2023-07-02 10:33:22,289 [mcmc] New sample, #41:
Omega_m:0.3031981, b1:0.5519221
2023-07-02 10:33:22,289 [model] Posterior to be computed for parameters {'Omega_m': 0.3008435759414654, 'b1': 0.8083227325463126}
2023-07-02 10:33:22,289 [prior] Evaluating prior at array([0.30084358, 0.80832273])
2023-07-02 10:33:22,289 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:22,290 [model] Got input parameters: {'Omega_m': 0.3008435759414654, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8083227325463126, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:22,290 [classy] Got parameters {'Omega_m': 0.3008435759414654, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:22,290 [classy] Re-using computed results
2023-07-02 10:33:22,290 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.68436678296703}
2023-07-02 10:33:22,290 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:22,290 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8083227325463126, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:22,290 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:22,309 [fs_likelihood.fslikelihood] Computed log-likelihood = -275.217
2023-07-02 10:33:22,309 [model] Computed derived parameters: {}
2023-07-02 10:33:22,310 [model] Posterior to be computed for parameters {'Omega_m': 0.3062034503032166, 'b1': 0.5519221298133538}
2023-07-02 10:33:22,310 [prior] Evaluating prior at array([0.30620345, 0.55192213])
2023-07-02 10:33:22,310 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:22,310 [model] Got input parameters: {'Omega_m': 0.3062034503032166, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:22,310 [classy] Got parameters {'Omega_m': 0.3062034503032166, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:22,310 [classy] Computing new state
2023-07-02 10:33:22,310 [classy] Setting parameters: {'Omega_m': 0.3062034503032166, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:22,354 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.02266118955433}
2023-07-02 10:33:22,354 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:22,356 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00265963
2023-07-02 10:33:22,356 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:22,356 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:22,376 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.05401
2023-07-02 10:33:22,376 [model] Computed derived parameters: {}
2023-07-02 10:33:22,376 [mcmc] New sample, #42:
Omega_m:0.3008436, b1:0.5519221
2023-07-02 10:33:22,377 [model] Posterior to be computed for parameters {'Omega_m': 0.3062034503032166, 'b1': 0.37146299220949075}
2023-07-02 10:33:22,377 [prior] Evaluating prior at array([0.30620345, 0.37146299])
2023-07-02 10:33:22,377 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:22,377 [model] Got input parameters: {'Omega_m': 0.3062034503032166, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.37146299220949075, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:22,377 [classy] Got parameters {'Omega_m': 0.3062034503032166, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:22,377 [classy] Re-using computed results
2023-07-02 10:33:22,377 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.02266118955433}
2023-07-02 10:33:22,377 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:22,377 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.37146299220949075, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:22,377 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:22,397 [fs_likelihood.fslikelihood] Computed log-likelihood = -45.919
2023-07-02 10:33:22,397 [model] Computed derived parameters: {}
2023-07-02 10:33:22,397 [model] Posterior to be computed for parameters {'Omega_m': 0.3016247485583303, 'b1': 0.5519221298133538}
2023-07-02 10:33:22,397 [prior] Evaluating prior at array([0.30162475, 0.55192213])
2023-07-02 10:33:22,397 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:22,397 [model] Got input parameters: {'Omega_m': 0.3016247485583303, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:22,397 [classy] Got parameters {'Omega_m': 0.3016247485583303, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:22,397 [classy] Computing new state
2023-07-02 10:33:22,397 [classy] Setting parameters: {'Omega_m': 0.3016247485583303, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:22,442 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.58728920924108}
2023-07-02 10:33:22,442 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:22,443 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00763342
2023-07-02 10:33:22,443 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:22,444 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:22,463 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.203499
2023-07-02 10:33:22,464 [model] Computed derived parameters: {}
2023-07-02 10:33:22,464 [mcmc] New sample, #43:
Omega_m:0.3062035, b1:0.5519221
2023-07-02 10:33:22,464 [model] Posterior to be computed for parameters {'Omega_m': 0.3016247485583303, 'b1': 0.28441299083151156}
2023-07-02 10:33:22,464 [prior] Evaluating prior at array([0.30162475, 0.28441299])
2023-07-02 10:33:22,464 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:22,464 [model] Got input parameters: {'Omega_m': 0.3016247485583303, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.28441299083151156, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:22,464 [classy] Got parameters {'Omega_m': 0.3016247485583303, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:22,464 [classy] Re-using computed results
2023-07-02 10:33:22,464 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.58728920924108}
2023-07-02 10:33:22,464 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:22,464 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.28441299083151156, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:22,464 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:22,485 [fs_likelihood.fslikelihood] Computed log-likelihood = -117.93
2023-07-02 10:33:22,485 [model] Computed derived parameters: {}
2023-07-02 10:33:22,485 [model] Posterior to be computed for parameters {'Omega_m': 0.2984268303190012, 'b1': 0.5519221298133538}
2023-07-02 10:33:22,485 [prior] Evaluating prior at array([0.29842683, 0.55192213])
2023-07-02 10:33:22,485 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:22,485 [model] Got input parameters: {'Omega_m': 0.2984268303190012, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:22,485 [classy] Got parameters {'Omega_m': 0.2984268303190012, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:22,485 [classy] Computing new state
2023-07-02 10:33:22,485 [classy] Setting parameters: {'Omega_m': 0.2984268303190012, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:22,530 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.98614873405336}
2023-07-02 10:33:22,530 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:22,532 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0127568
2023-07-02 10:33:22,532 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:22,532 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:22,551 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.0183653
2023-07-02 10:33:22,552 [model] Computed derived parameters: {}
2023-07-02 10:33:22,552 [mcmc] New sample, #44:
Omega_m:0.3016247, b1:0.5519221
2023-07-02 10:33:22,552 [model] Posterior to be computed for parameters {'Omega_m': 0.2984268303190012, 'b1': 0.7516198877223644}
2023-07-02 10:33:22,552 [prior] Evaluating prior at array([0.29842683, 0.75161989])
2023-07-02 10:33:22,552 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:22,552 [model] Got input parameters: {'Omega_m': 0.2984268303190012, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.7516198877223644, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:22,552 [classy] Got parameters {'Omega_m': 0.2984268303190012, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:22,552 [classy] Re-using computed results
2023-07-02 10:33:22,552 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.98614873405336}
2023-07-02 10:33:22,552 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:22,552 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.7516198877223644, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:22,552 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:22,573 [fs_likelihood.fslikelihood] Computed log-likelihood = -159.064
2023-07-02 10:33:22,573 [model] Computed derived parameters: {}
2023-07-02 10:33:22,573 [model] Posterior to be computed for parameters {'Omega_m': 0.2953615175912442, 'b1': 0.5519221298133538}
2023-07-02 10:33:22,573 [prior] Evaluating prior at array([0.29536152, 0.55192213])
2023-07-02 10:33:22,573 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:22,573 [model] Got input parameters: {'Omega_m': 0.2953615175912442, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:22,573 [classy] Got parameters {'Omega_m': 0.2953615175912442, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:22,574 [classy] Computing new state
2023-07-02 10:33:22,574 [classy] Setting parameters: {'Omega_m': 0.2953615175912442, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:22,617 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.3719982248647}
2023-07-02 10:33:22,617 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:22,619 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0189764
2023-07-02 10:33:22,619 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:22,619 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:22,639 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.156569
2023-07-02 10:33:22,639 [model] Computed derived parameters: {}
2023-07-02 10:33:22,639 [mcmc] New sample, #45:
Omega_m:0.2984268, b1:0.5519221
2023-07-02 10:33:22,640 [model] Posterior to be computed for parameters {'Omega_m': 0.2953615175912442, 'b1': 0.30100388586694227}
2023-07-02 10:33:22,640 [prior] Evaluating prior at array([0.29536152, 0.30100389])
2023-07-02 10:33:22,640 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:22,640 [model] Got input parameters: {'Omega_m': 0.2953615175912442, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.30100388586694227, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:22,640 [classy] Got parameters {'Omega_m': 0.2953615175912442, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:22,640 [classy] Re-using computed results
2023-07-02 10:33:22,640 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.3719982248647}
2023-07-02 10:33:22,640 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:22,640 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.30100388586694227, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:22,640 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:22,660 [fs_likelihood.fslikelihood] Computed log-likelihood = -114.012
2023-07-02 10:33:22,660 [model] Computed derived parameters: {}
2023-07-02 10:33:22,660 [model] Posterior to be computed for parameters {'Omega_m': 0.2937591117363911, 'b1': 0.5519221298133538}
2023-07-02 10:33:22,660 [prior] Evaluating prior at array([0.29375911, 0.55192213])
2023-07-02 10:33:22,660 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:22,660 [model] Got input parameters: {'Omega_m': 0.2937591117363911, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:22,660 [classy] Got parameters {'Omega_m': 0.2937591117363911, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:22,660 [classy] Computing new state
2023-07-02 10:33:22,660 [classy] Setting parameters: {'Omega_m': 0.2937591117363911, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:22,704 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.57509318183054}
2023-07-02 10:33:22,704 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:22,706 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0227478
2023-07-02 10:33:22,706 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:22,706 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:22,727 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.351794
2023-07-02 10:33:22,727 [model] Computed derived parameters: {}
2023-07-02 10:33:22,727 [mcmc] New sample, #46:
Omega_m:0.2953615, b1:0.5519221
2023-07-02 10:33:22,727 [model] Posterior to be computed for parameters {'Omega_m': 0.2937591117363911, 'b1': 0.7986274000650906}
2023-07-02 10:33:22,727 [prior] Evaluating prior at array([0.29375911, 0.7986274 ])
2023-07-02 10:33:22,727 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:22,727 [model] Got input parameters: {'Omega_m': 0.2937591117363911, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.7986274000650906, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:22,727 [classy] Got parameters {'Omega_m': 0.2937591117363911, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:22,727 [classy] Re-using computed results
2023-07-02 10:33:22,727 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.57509318183054}
2023-07-02 10:33:22,727 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:22,727 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.7986274000650906, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:22,728 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:22,747 [fs_likelihood.fslikelihood] Computed log-likelihood = -227.504
2023-07-02 10:33:22,747 [model] Computed derived parameters: {}
2023-07-02 10:33:22,748 [model] Posterior to be computed for parameters {'Omega_m': 0.30625764732277694, 'b1': 0.5519221298133538}
2023-07-02 10:33:22,748 [prior] Evaluating prior at array([0.30625765, 0.55192213])
2023-07-02 10:33:22,748 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:22,748 [model] Got input parameters: {'Omega_m': 0.30625764732277694, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:22,748 [classy] Got parameters {'Omega_m': 0.30625764732277694, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:22,748 [classy] Computing new state
2023-07-02 10:33:22,748 [classy] Setting parameters: {'Omega_m': 0.30625764732277694, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:22,792 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.01602368688003}
2023-07-02 10:33:22,792 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:22,794 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00261709
2023-07-02 10:33:22,794 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:22,794 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:22,814 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.0682
2023-07-02 10:33:22,814 [model] Computed derived parameters: {}
2023-07-02 10:33:22,814 [model] Posterior to be computed for parameters {'Omega_m': 0.2937591117363911, 'b1': 1.2593493996184808}
2023-07-02 10:33:22,814 [prior] Evaluating prior at array([0.29375911, 1.2593494 ])
2023-07-02 10:33:22,814 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:22,814 [model] Got input parameters: {'Omega_m': 0.2937591117363911, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.2593493996184808, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:22,814 [classy] Got parameters {'Omega_m': 0.2937591117363911, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:22,814 [classy] Re-using computed results
2023-07-02 10:33:22,814 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.57509318183054}
2023-07-02 10:33:22,814 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:22,814 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.2593493996184808, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:22,814 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:22,835 [fs_likelihood.fslikelihood] Computed log-likelihood = -2579.76
2023-07-02 10:33:22,835 [model] Computed derived parameters: {}
2023-07-02 10:33:22,835 [model] Posterior to be computed for parameters {'Omega_m': 0.29930387447375584, 'b1': 0.5519221298133538}
2023-07-02 10:33:22,835 [prior] Evaluating prior at array([0.29930387, 0.55192213])
2023-07-02 10:33:22,835 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:22,835 [model] Got input parameters: {'Omega_m': 0.29930387447375584, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:22,836 [classy] Got parameters {'Omega_m': 0.29930387447375584, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:22,836 [classy] Computing new state
2023-07-02 10:33:22,836 [classy] Setting parameters: {'Omega_m': 0.29930387447375584, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:22,880 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.8763825622771}
2023-07-02 10:33:22,880 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:22,882 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0112142
2023-07-02 10:33:22,882 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:22,882 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:22,902 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.0356719
2023-07-02 10:33:22,902 [model] Computed derived parameters: {}
2023-07-02 10:33:22,902 [mcmc] New sample, #47:
Omega_m:0.2937591, b1:0.5519221
2023-07-02 10:33:22,902 [model] Posterior to be computed for parameters {'Omega_m': 0.29930387447375584, 'b1': 0.9170176868694204}
2023-07-02 10:33:22,902 [prior] Evaluating prior at array([0.29930387, 0.91701769])
2023-07-02 10:33:22,902 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:22,902 [model] Got input parameters: {'Omega_m': 0.29930387447375584, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.9170176868694204, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:22,902 [classy] Got parameters {'Omega_m': 0.29930387447375584, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:22,902 [classy] Re-using computed results
2023-07-02 10:33:22,902 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.8763825622771}
2023-07-02 10:33:22,902 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:22,902 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.9170176868694204, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:22,902 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:22,922 [fs_likelihood.fslikelihood] Computed log-likelihood = -572.844
2023-07-02 10:33:22,923 [model] Computed derived parameters: {}
2023-07-02 10:33:22,923 [model] Posterior to be computed for parameters {'Omega_m': 0.28473125848640607, 'b1': 0.5519221298133538}
2023-07-02 10:33:22,923 [prior] Evaluating prior at array([0.28473126, 0.55192213])
2023-07-02 10:33:22,923 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:22,923 [model] Got input parameters: {'Omega_m': 0.28473125848640607, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:22,923 [classy] Got parameters {'Omega_m': 0.28473125848640607, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:22,923 [classy] Computing new state
2023-07-02 10:33:22,923 [classy] Setting parameters: {'Omega_m': 0.28473125848640607, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:22,967 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.7375834964338}
2023-07-02 10:33:22,967 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:22,968 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0509052
2023-07-02 10:33:22,969 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:22,969 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:22,989 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.02957
2023-07-02 10:33:22,990 [model] Computed derived parameters: {}
2023-07-02 10:33:22,990 [model] Posterior to be computed for parameters {'Omega_m': 0.29930387447375584, 'b1': 0.24355068844719835}
2023-07-02 10:33:22,990 [prior] Evaluating prior at array([0.29930387, 0.24355069])
2023-07-02 10:33:22,990 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:22,990 [model] Got input parameters: {'Omega_m': 0.29930387447375584, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.24355068844719835, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:22,990 [classy] Got parameters {'Omega_m': 0.29930387447375584, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:22,990 [classy] Re-using computed results
2023-07-02 10:33:22,990 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.8763825622771}
2023-07-02 10:33:22,990 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:22,990 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.24355068844719835, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:22,990 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:23,010 [fs_likelihood.fslikelihood] Computed log-likelihood = -159.164
2023-07-02 10:33:23,010 [model] Computed derived parameters: {}
2023-07-02 10:33:23,010 [model] Posterior to be computed for parameters {'Omega_m': 0.29991512415667354, 'b1': 0.5519221298133538}
2023-07-02 10:33:23,010 [prior] Evaluating prior at array([0.29991512, 0.55192213])
2023-07-02 10:33:23,010 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:23,011 [model] Got input parameters: {'Omega_m': 0.29991512415667354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:23,011 [classy] Got parameters {'Omega_m': 0.29991512415667354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:23,011 [classy] Computing new state
2023-07-02 10:33:23,011 [classy] Setting parameters: {'Omega_m': 0.29991512415667354, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:23,055 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.80004921847723}
2023-07-02 10:33:23,055 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:23,057 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0102007
2023-07-02 10:33:23,057 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5519221298133538, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:23,057 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:23,078 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.0626909
2023-07-02 10:33:23,078 [model] Computed derived parameters: {}
2023-07-02 10:33:23,078 [mcmc] New sample, #48:
Omega_m:0.2993039, b1:0.5519221
2023-07-02 10:33:23,078 [model] Posterior to be computed for parameters {'Omega_m': 0.29991512415667354, 'b1': 0.5195237182842224}
2023-07-02 10:33:23,078 [prior] Evaluating prior at array([0.29991512, 0.51952372])
2023-07-02 10:33:23,078 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:23,078 [model] Got input parameters: {'Omega_m': 0.29991512415667354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:23,078 [classy] Got parameters {'Omega_m': 0.29991512415667354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:23,078 [classy] Re-using computed results
2023-07-02 10:33:23,078 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.80004921847723}
2023-07-02 10:33:23,078 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:23,078 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:23,079 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:23,099 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.34977
2023-07-02 10:33:23,099 [model] Computed derived parameters: {}
2023-07-02 10:33:23,099 [mcmc] New sample, #49:
Omega_m:0.2999151, b1:0.5519221
2023-07-02 10:33:23,099 [model] Posterior to be computed for parameters {'Omega_m': 0.2983288116046203, 'b1': 0.5195237182842224}
2023-07-02 10:33:23,099 [prior] Evaluating prior at array([0.29832881, 0.51952372])
2023-07-02 10:33:23,099 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:23,099 [model] Got input parameters: {'Omega_m': 0.2983288116046203, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:23,099 [classy] Got parameters {'Omega_m': 0.2983288116046203, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:23,099 [classy] Computing new state
2023-07-02 10:33:23,099 [classy] Setting parameters: {'Omega_m': 0.2983288116046203, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:23,147 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.9984324763864}
2023-07-02 10:33:23,147 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:23,149 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0129356
2023-07-02 10:33:23,149 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:23,149 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:23,169 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.887817
2023-07-02 10:33:23,169 [model] Computed derived parameters: {}
2023-07-02 10:33:23,169 [model] Posterior to be computed for parameters {'Omega_m': 0.29991512415667354, 'b1': 2.5359948169443425}
2023-07-02 10:33:23,169 [prior] Evaluating prior at array([0.29991512, 2.53599482])
2023-07-02 10:33:23,169 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:23,169 [model] Got input parameters: {'Omega_m': 0.29991512415667354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 2.5359948169443425, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:23,169 [classy] Got parameters {'Omega_m': 0.29991512415667354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:23,169 [classy] Re-using computed results
2023-07-02 10:33:23,169 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.80004921847723}
2023-07-02 10:33:23,169 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:23,169 [fs_likelihood.fslikelihood] Got parameters {'b1': 2.5359948169443425, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:23,169 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:23,190 [fs_likelihood.fslikelihood] Computed log-likelihood = -46582.6
2023-07-02 10:33:23,190 [model] Computed derived parameters: {}
2023-07-02 10:33:23,190 [model] Posterior to be computed for parameters {'Omega_m': 0.29122073856488007, 'b1': 0.5195237182842224}
2023-07-02 10:33:23,190 [prior] Evaluating prior at array([0.29122074, 0.51952372])
2023-07-02 10:33:23,191 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:23,191 [model] Got input parameters: {'Omega_m': 0.29122073856488007, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:23,191 [classy] Got parameters {'Omega_m': 0.29122073856488007, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:23,191 [classy] Computing new state
2023-07-02 10:33:23,191 [classy] Setting parameters: {'Omega_m': 0.29122073856488007, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:23,235 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.89879054259472}
2023-07-02 10:33:23,235 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:23,237 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0294661
2023-07-02 10:33:23,237 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:23,237 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:23,257 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.12253
2023-07-02 10:33:23,257 [model] Computed derived parameters: {}
2023-07-02 10:33:23,258 [model] Posterior to be computed for parameters {'Omega_m': 0.29991512415667354, 'b1': 0.6747633984717009}
2023-07-02 10:33:23,258 [prior] Evaluating prior at array([0.29991512, 0.6747634 ])
2023-07-02 10:33:23,258 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:23,258 [model] Got input parameters: {'Omega_m': 0.29991512415667354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6747633984717009, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:23,258 [classy] Got parameters {'Omega_m': 0.29991512415667354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:23,258 [classy] Re-using computed results
2023-07-02 10:33:23,258 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.80004921847723}
2023-07-02 10:33:23,258 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:23,258 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6747633984717009, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:23,258 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:23,280 [fs_likelihood.fslikelihood] Computed log-likelihood = -64.6719
2023-07-02 10:33:23,280 [model] Computed derived parameters: {}
2023-07-02 10:33:23,280 [model] Posterior to be computed for parameters {'Omega_m': 0.3208603102566019, 'b1': 0.5195237182842224}
2023-07-02 10:33:23,280 [prior] Evaluating prior at array([0.32086031, 0.51952372])
2023-07-02 10:33:23,281 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:23,281 [model] Got input parameters: {'Omega_m': 0.3208603102566019, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:23,281 [classy] Got parameters {'Omega_m': 0.3208603102566019, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:23,281 [classy] Computing new state
2023-07-02 10:33:23,281 [classy] Setting parameters: {'Omega_m': 0.3208603102566019, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:23,324 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.26407152024586}
2023-07-02 10:33:23,324 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:23,326 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00441643
2023-07-02 10:33:23,326 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:23,326 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:23,347 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.268184
2023-07-02 10:33:23,347 [model] Computed derived parameters: {}
2023-07-02 10:33:23,347 [model] Posterior to be computed for parameters {'Omega_m': 0.29991512415667354, 'b1': -0.49282733057451356}
2023-07-02 10:33:23,347 [prior] Evaluating prior at array([ 0.29991512, -0.49282733])
2023-07-02 10:33:23,347 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:23,347 [model] Posterior to be computed for parameters {'Omega_m': 0.27955271649559543, 'b1': 0.5195237182842224}
2023-07-02 10:33:23,347 [prior] Evaluating prior at array([0.27955272, 0.51952372])
2023-07-02 10:33:23,348 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:23,348 [model] Got input parameters: {'Omega_m': 0.27955271649559543, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:23,348 [classy] Got parameters {'Omega_m': 0.27955271649559543, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:23,348 [classy] Computing new state
2023-07-02 10:33:23,348 [classy] Setting parameters: {'Omega_m': 0.27955271649559543, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:23,393 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.41887798832215}
2023-07-02 10:33:23,393 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:23,394 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0725779
2023-07-02 10:33:23,394 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:23,395 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:23,415 [fs_likelihood.fslikelihood] Computed log-likelihood = -10.3977
2023-07-02 10:33:23,415 [model] Computed derived parameters: {}
2023-07-02 10:33:23,415 [model] Posterior to be computed for parameters {'Omega_m': 0.29991512415667354, 'b1': 0.15788407551432493}
2023-07-02 10:33:23,415 [prior] Evaluating prior at array([0.29991512, 0.15788408])
2023-07-02 10:33:23,415 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:23,415 [model] Got input parameters: {'Omega_m': 0.29991512415667354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.15788407551432493, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:23,415 [classy] Got parameters {'Omega_m': 0.29991512415667354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:23,415 [classy] Re-using computed results
2023-07-02 10:33:23,415 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.80004921847723}
2023-07-02 10:33:23,415 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:23,415 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.15788407551432493, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:23,415 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:23,436 [fs_likelihood.fslikelihood] Computed log-likelihood = -244.69
2023-07-02 10:33:23,436 [model] Computed derived parameters: {}
2023-07-02 10:33:23,436 [model] Posterior to be computed for parameters {'Omega_m': 0.2993546308450781, 'b1': 0.5195237182842224}
2023-07-02 10:33:23,436 [prior] Evaluating prior at array([0.29935463, 0.51952372])
2023-07-02 10:33:23,436 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:23,436 [model] Got input parameters: {'Omega_m': 0.2993546308450781, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:23,436 [classy] Got parameters {'Omega_m': 0.2993546308450781, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:23,436 [classy] Computing new state
2023-07-02 10:33:23,437 [classy] Setting parameters: {'Omega_m': 0.2993546308450781, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:23,484 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.87003925218033}
2023-07-02 10:33:23,484 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:23,486 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0111281
2023-07-02 10:33:23,486 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:23,486 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:23,506 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.1953
2023-07-02 10:33:23,506 [model] Computed derived parameters: {}
2023-07-02 10:33:23,506 [mcmc] New sample, #50:
Omega_m:0.2999151, b1:0.5195237
2023-07-02 10:33:23,506 [model] Posterior to be computed for parameters {'Omega_m': 0.2993546308450781, 'b1': -0.23787480739684774}
2023-07-02 10:33:23,506 [prior] Evaluating prior at array([ 0.29935463, -0.23787481])
2023-07-02 10:33:23,507 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:23,507 [model] Posterior to be computed for parameters {'Omega_m': 0.3014410956438017, 'b1': 0.5195237182842224}
2023-07-02 10:33:23,507 [prior] Evaluating prior at array([0.3014411 , 0.51952372])
2023-07-02 10:33:23,507 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:23,507 [model] Got input parameters: {'Omega_m': 0.3014410956438017, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:23,507 [classy] Got parameters {'Omega_m': 0.3014410956438017, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:23,507 [classy] Computing new state
2023-07-02 10:33:23,507 [classy] Setting parameters: {'Omega_m': 0.3014410956438017, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:23,552 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.6100921172112}
2023-07-02 10:33:23,552 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:23,554 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00789044
2023-07-02 10:33:23,554 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:23,554 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:23,573 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.72189
2023-07-02 10:33:23,574 [model] Computed derived parameters: {}
2023-07-02 10:33:23,574 [mcmc] New sample, #51:
Omega_m:0.2993546, b1:0.5195237
2023-07-02 10:33:23,574 [model] Posterior to be computed for parameters {'Omega_m': 0.3014410956438017, 'b1': 0.18239292219831027}
2023-07-02 10:33:23,574 [prior] Evaluating prior at array([0.3014411 , 0.18239292])
2023-07-02 10:33:23,574 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:23,574 [model] Got input parameters: {'Omega_m': 0.3014410956438017, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.18239292219831027, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:23,574 [classy] Got parameters {'Omega_m': 0.3014410956438017, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:23,574 [classy] Re-using computed results
2023-07-02 10:33:23,574 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.6100921172112}
2023-07-02 10:33:23,574 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:23,574 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.18239292219831027, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:23,574 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:23,595 [fs_likelihood.fslikelihood] Computed log-likelihood = -216.179
2023-07-02 10:33:23,595 [model] Computed derived parameters: {}
2023-07-02 10:33:23,595 [model] Posterior to be computed for parameters {'Omega_m': 0.3093467198361541, 'b1': 0.5195237182842224}
2023-07-02 10:33:23,595 [prior] Evaluating prior at array([0.30934672, 0.51952372])
2023-07-02 10:33:23,595 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:23,595 [model] Got input parameters: {'Omega_m': 0.3093467198361541, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:23,595 [classy] Got parameters {'Omega_m': 0.3093467198361541, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:23,595 [classy] Computing new state
2023-07-02 10:33:23,595 [classy] Setting parameters: {'Omega_m': 0.3093467198361541, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:23,641 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.63932481434654}
2023-07-02 10:33:23,641 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:23,642 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000810724
2023-07-02 10:33:23,643 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:23,643 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:23,663 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.51512
2023-07-02 10:33:23,663 [model] Computed derived parameters: {}
2023-07-02 10:33:23,663 [mcmc] New sample, #52:
Omega_m:0.3014411, b1:0.5195237
2023-07-02 10:33:23,663 [model] Posterior to be computed for parameters {'Omega_m': 0.3093467198361541, 'b1': 0.9065273821202704}
2023-07-02 10:33:23,663 [prior] Evaluating prior at array([0.30934672, 0.90652738])
2023-07-02 10:33:23,663 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:23,663 [model] Got input parameters: {'Omega_m': 0.3093467198361541, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.9065273821202704, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:23,663 [classy] Got parameters {'Omega_m': 0.3093467198361541, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:23,663 [classy] Re-using computed results
2023-07-02 10:33:23,663 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.63932481434654}
2023-07-02 10:33:23,663 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:23,663 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.9065273821202704, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:23,663 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:23,684 [fs_likelihood.fslikelihood] Computed log-likelihood = -606.71
2023-07-02 10:33:23,684 [model] Computed derived parameters: {}
2023-07-02 10:33:23,684 [model] Posterior to be computed for parameters {'Omega_m': 0.324511395815196, 'b1': 0.5195237182842224}
2023-07-02 10:33:23,684 [prior] Evaluating prior at array([0.3245114 , 0.51952372])
2023-07-02 10:33:23,684 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:23,684 [model] Got input parameters: {'Omega_m': 0.324511395815196, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:23,684 [classy] Got parameters {'Omega_m': 0.324511395815196, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:23,684 [classy] Computing new state
2023-07-02 10:33:23,684 [classy] Setting parameters: {'Omega_m': 0.324511395815196, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:23,728 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.83715652306358}
2023-07-02 10:33:23,728 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:23,730 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00881386
2023-07-02 10:33:23,730 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:23,730 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:23,751 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.28685
2023-07-02 10:33:23,751 [model] Computed derived parameters: {}
2023-07-02 10:33:23,751 [model] Posterior to be computed for parameters {'Omega_m': 0.3093467198361541, 'b1': -0.1496384743576149}
2023-07-02 10:33:23,751 [prior] Evaluating prior at array([ 0.30934672, -0.14963847])
2023-07-02 10:33:23,751 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:23,751 [model] Posterior to be computed for parameters {'Omega_m': 0.2995984350540414, 'b1': 0.5195237182842224}
2023-07-02 10:33:23,751 [prior] Evaluating prior at array([0.29959844, 0.51952372])
2023-07-02 10:33:23,751 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:23,751 [model] Got input parameters: {'Omega_m': 0.2995984350540414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:23,751 [classy] Got parameters {'Omega_m': 0.2995984350540414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:23,751 [classy] Computing new state
2023-07-02 10:33:23,751 [classy] Setting parameters: {'Omega_m': 0.2995984350540414, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:23,796 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.83958023290648}
2023-07-02 10:33:23,796 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:23,798 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0107195
2023-07-02 10:33:23,798 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:23,798 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:23,817 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.26367
2023-07-02 10:33:23,817 [model] Computed derived parameters: {}
2023-07-02 10:33:23,818 [mcmc] New sample, #53:
Omega_m:0.3093467, b1:0.5195237
2023-07-02 10:33:23,818 [model] Posterior to be computed for parameters {'Omega_m': 0.2995984350540414, 'b1': -0.739436344928673}
2023-07-02 10:33:23,818 [prior] Evaluating prior at array([ 0.29959844, -0.73943634])
2023-07-02 10:33:23,818 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:23,818 [model] Posterior to be computed for parameters {'Omega_m': 0.2911141695421805, 'b1': 0.5195237182842224}
2023-07-02 10:33:23,818 [prior] Evaluating prior at array([0.29111417, 0.51952372])
2023-07-02 10:33:23,818 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:23,818 [model] Got input parameters: {'Omega_m': 0.2911141695421805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:23,818 [classy] Got parameters {'Omega_m': 0.2911141695421805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:23,818 [classy] Computing new state
2023-07-02 10:33:23,818 [classy] Setting parameters: {'Omega_m': 0.2911141695421805, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:23,862 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.91243394628125}
2023-07-02 10:33:23,862 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:23,864 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0297683
2023-07-02 10:33:23,864 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:23,864 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:23,884 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.17936
2023-07-02 10:33:23,885 [model] Computed derived parameters: {}
2023-07-02 10:33:23,885 [model] Posterior to be computed for parameters {'Omega_m': 0.2995984350540414, 'b1': -0.20179891593627486}
2023-07-02 10:33:23,885 [prior] Evaluating prior at array([ 0.29959844, -0.20179892])
2023-07-02 10:33:23,885 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:23,885 [model] Posterior to be computed for parameters {'Omega_m': 0.3025261049903241, 'b1': 0.5195237182842224}
2023-07-02 10:33:23,885 [prior] Evaluating prior at array([0.3025261 , 0.51952372])
2023-07-02 10:33:23,885 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:23,885 [model] Got input parameters: {'Omega_m': 0.3025261049903241, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:23,885 [classy] Got parameters {'Omega_m': 0.3025261049903241, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:23,885 [classy] Computing new state
2023-07-02 10:33:23,885 [classy] Setting parameters: {'Omega_m': 0.3025261049903241, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:23,929 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.47554719676702}
2023-07-02 10:33:23,929 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:23,931 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00643685
2023-07-02 10:33:23,931 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:23,931 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:23,951 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.94336
2023-07-02 10:33:23,952 [model] Computed derived parameters: {}
2023-07-02 10:33:23,952 [mcmc] New sample, #54:
Omega_m:0.2995984, b1:0.5195237
2023-07-02 10:33:23,952 [model] Posterior to be computed for parameters {'Omega_m': 0.3025261049903241, 'b1': -0.7969473131310648}
2023-07-02 10:33:23,952 [prior] Evaluating prior at array([ 0.3025261 , -0.79694731])
2023-07-02 10:33:23,952 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:23,952 [model] Posterior to be computed for parameters {'Omega_m': 0.3318560344270412, 'b1': 0.5195237182842224}
2023-07-02 10:33:23,952 [prior] Evaluating prior at array([0.33185603, 0.51952372])
2023-07-02 10:33:23,952 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:23,952 [model] Got input parameters: {'Omega_m': 0.3318560344270412, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:23,952 [classy] Got parameters {'Omega_m': 0.3318560344270412, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:23,952 [classy] Computing new state
2023-07-02 10:33:23,952 [classy] Setting parameters: {'Omega_m': 0.3318560344270412, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:23,997 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.99126308332833}
2023-07-02 10:33:23,997 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:23,999 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0221508
2023-07-02 10:33:23,999 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:23,999 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:24,019 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.64387
2023-07-02 10:33:24,019 [model] Computed derived parameters: {}
2023-07-02 10:33:24,019 [model] Posterior to be computed for parameters {'Omega_m': 0.3025261049903241, 'b1': 0.29461570873738535}
2023-07-02 10:33:24,019 [prior] Evaluating prior at array([0.3025261 , 0.29461571])
2023-07-02 10:33:24,020 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:24,020 [model] Got input parameters: {'Omega_m': 0.3025261049903241, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.29461570873738535, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:24,020 [classy] Got parameters {'Omega_m': 0.3025261049903241, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:24,020 [classy] Re-using computed results
2023-07-02 10:33:24,020 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.47554719676702}
2023-07-02 10:33:24,020 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:24,020 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.29461570873738535, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:24,020 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:24,040 [fs_likelihood.fslikelihood] Computed log-likelihood = -107.743
2023-07-02 10:33:24,040 [model] Computed derived parameters: {}
2023-07-02 10:33:24,040 [model] Posterior to be computed for parameters {'Omega_m': 0.3000975386302018, 'b1': 0.5195237182842224}
2023-07-02 10:33:24,040 [prior] Evaluating prior at array([0.30009754, 0.51952372])
2023-07-02 10:33:24,040 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:24,040 [model] Got input parameters: {'Omega_m': 0.3000975386302018, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:24,040 [classy] Got parameters {'Omega_m': 0.3000975386302018, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:24,040 [classy] Computing new state
2023-07-02 10:33:24,040 [classy] Setting parameters: {'Omega_m': 0.3000975386302018, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:24,084 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.7772941201249}
2023-07-02 10:33:24,084 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:24,086 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00990805
2023-07-02 10:33:24,086 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:24,086 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:24,106 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.39798
2023-07-02 10:33:24,107 [model] Computed derived parameters: {}
2023-07-02 10:33:24,107 [mcmc] New sample, #55:
Omega_m:0.3025261, b1:0.5195237
2023-07-02 10:33:24,107 [model] Posterior to be computed for parameters {'Omega_m': 0.3000975386302018, 'b1': -0.05134008881847618}
2023-07-02 10:33:24,107 [prior] Evaluating prior at array([ 0.30009754, -0.05134009])
2023-07-02 10:33:24,107 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:24,107 [model] Posterior to be computed for parameters {'Omega_m': 0.3138328208814638, 'b1': 0.5195237182842224}
2023-07-02 10:33:24,107 [prior] Evaluating prior at array([0.31383282, 0.51952372])
2023-07-02 10:33:24,107 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:24,107 [model] Got input parameters: {'Omega_m': 0.3138328208814638, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:24,107 [classy] Got parameters {'Omega_m': 0.3138328208814638, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:24,107 [classy] Computing new state
2023-07-02 10:33:24,107 [classy] Setting parameters: {'Omega_m': 0.3138328208814638, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:24,154 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.09812802479559}
2023-07-02 10:33:24,154 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:24,156 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000313603
2023-07-02 10:33:24,156 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:24,156 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:24,176 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.11935
2023-07-02 10:33:24,176 [model] Computed derived parameters: {}
2023-07-02 10:33:24,176 [mcmc] New sample, #56:
Omega_m:0.3000975, b1:0.5195237
2023-07-02 10:33:24,176 [model] Posterior to be computed for parameters {'Omega_m': 0.3138328208814638, 'b1': -1.168791499354323}
2023-07-02 10:33:24,176 [prior] Evaluating prior at array([ 0.31383282, -1.1687915 ])
2023-07-02 10:33:24,176 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:24,176 [model] Posterior to be computed for parameters {'Omega_m': 0.3103570323926313, 'b1': 0.5195237182842224}
2023-07-02 10:33:24,176 [prior] Evaluating prior at array([0.31035703, 0.51952372])
2023-07-02 10:33:24,176 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:24,176 [model] Got input parameters: {'Omega_m': 0.3103570323926313, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:24,176 [classy] Got parameters {'Omega_m': 0.3103570323926313, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:24,176 [classy] Computing new state
2023-07-02 10:33:24,176 [classy] Setting parameters: {'Omega_m': 0.3103570323926313, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:24,220 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.5168402924341}
2023-07-02 10:33:24,220 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:24,222 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000481284
2023-07-02 10:33:24,222 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:24,222 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:24,242 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.47942
2023-07-02 10:33:24,243 [model] Computed derived parameters: {}
2023-07-02 10:33:24,243 [mcmc] New sample, #57:
Omega_m:0.3138328, b1:0.5195237
2023-07-02 10:33:24,243 [model] Posterior to be computed for parameters {'Omega_m': 0.3103570323926313, 'b1': 0.18046939925790145}
2023-07-02 10:33:24,243 [prior] Evaluating prior at array([0.31035703, 0.1804694 ])
2023-07-02 10:33:24,243 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:24,243 [model] Got input parameters: {'Omega_m': 0.3103570323926313, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.18046939925790145, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:24,243 [classy] Got parameters {'Omega_m': 0.3103570323926313, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:24,243 [classy] Re-using computed results
2023-07-02 10:33:24,243 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.5168402924341}
2023-07-02 10:33:24,243 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:24,243 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.18046939925790145, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:24,243 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:24,263 [fs_likelihood.fslikelihood] Computed log-likelihood = -202.222
2023-07-02 10:33:24,263 [model] Computed derived parameters: {}
2023-07-02 10:33:24,264 [model] Posterior to be computed for parameters {'Omega_m': 0.29423264591678533, 'b1': 0.5195237182842224}
2023-07-02 10:33:24,264 [prior] Evaluating prior at array([0.29423265, 0.51952372])
2023-07-02 10:33:24,264 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:24,264 [model] Got input parameters: {'Omega_m': 0.29423264591678533, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:24,264 [classy] Got parameters {'Omega_m': 0.29423264591678533, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:24,264 [classy] Computing new state
2023-07-02 10:33:24,264 [classy] Setting parameters: {'Omega_m': 0.29423264591678533, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:24,308 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.51497698761037}
2023-07-02 10:33:24,308 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:24,310 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0215958
2023-07-02 10:33:24,310 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:24,310 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:24,330 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.659223
2023-07-02 10:33:24,330 [model] Computed derived parameters: {}
2023-07-02 10:33:24,330 [model] Posterior to be computed for parameters {'Omega_m': 0.3103570323926313, 'b1': 0.4499952051144753}
2023-07-02 10:33:24,330 [prior] Evaluating prior at array([0.31035703, 0.44999521])
2023-07-02 10:33:24,330 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:24,330 [model] Got input parameters: {'Omega_m': 0.3103570323926313, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4499952051144753, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:24,330 [classy] Got parameters {'Omega_m': 0.3103570323926313, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:24,330 [classy] Re-using computed results
2023-07-02 10:33:24,330 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.5168402924341}
2023-07-02 10:33:24,330 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:24,330 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4499952051144753, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:24,330 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:24,351 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.94713
2023-07-02 10:33:24,351 [model] Computed derived parameters: {}
2023-07-02 10:33:24,351 [model] Posterior to be computed for parameters {'Omega_m': 0.3195468611781863, 'b1': 0.5195237182842224}
2023-07-02 10:33:24,351 [prior] Evaluating prior at array([0.31954686, 0.51952372])
2023-07-02 10:33:24,351 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:24,351 [model] Got input parameters: {'Omega_m': 0.3195468611781863, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:24,351 [classy] Got parameters {'Omega_m': 0.3195468611781863, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:24,351 [classy] Computing new state
2023-07-02 10:33:24,351 [classy] Setting parameters: {'Omega_m': 0.3195468611781863, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:24,395 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.4187117702353}
2023-07-02 10:33:24,395 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:24,397 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00320815
2023-07-02 10:33:24,397 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:24,397 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:24,417 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.728372
2023-07-02 10:33:24,417 [model] Computed derived parameters: {}
2023-07-02 10:33:24,417 [model] Posterior to be computed for parameters {'Omega_m': 0.3103570323926313, 'b1': 0.46083567127657843}
2023-07-02 10:33:24,417 [prior] Evaluating prior at array([0.31035703, 0.46083567])
2023-07-02 10:33:24,418 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:24,418 [model] Got input parameters: {'Omega_m': 0.3103570323926313, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46083567127657843, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:24,418 [classy] Got parameters {'Omega_m': 0.3103570323926313, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:24,418 [classy] Re-using computed results
2023-07-02 10:33:24,418 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.5168402924341}
2023-07-02 10:33:24,418 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:24,418 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46083567127657843, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:24,418 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:24,438 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.08539
2023-07-02 10:33:24,438 [model] Computed derived parameters: {}
2023-07-02 10:33:24,438 [model] Posterior to be computed for parameters {'Omega_m': 0.3301718701829529, 'b1': 0.5195237182842224}
2023-07-02 10:33:24,438 [prior] Evaluating prior at array([0.33017187, 0.51952372])
2023-07-02 10:33:24,438 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:24,438 [model] Got input parameters: {'Omega_m': 0.3301718701829529, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:24,438 [classy] Got parameters {'Omega_m': 0.3301718701829529, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:24,438 [classy] Computing new state
2023-07-02 10:33:24,438 [classy] Setting parameters: {'Omega_m': 0.3301718701829529, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:24,482 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.1837132550769}
2023-07-02 10:33:24,482 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:24,484 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0185751
2023-07-02 10:33:24,484 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:24,484 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:24,505 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.49972
2023-07-02 10:33:24,505 [model] Computed derived parameters: {}
2023-07-02 10:33:24,505 [model] Posterior to be computed for parameters {'Omega_m': 0.3103570323926313, 'b1': 0.017222164919888927}
2023-07-02 10:33:24,505 [prior] Evaluating prior at array([0.31035703, 0.01722216])
2023-07-02 10:33:24,505 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:24,505 [model] Got input parameters: {'Omega_m': 0.3103570323926313, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.017222164919888927, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:24,505 [classy] Got parameters {'Omega_m': 0.3103570323926313, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:24,505 [classy] Re-using computed results
2023-07-02 10:33:24,505 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.5168402924341}
2023-07-02 10:33:24,505 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:24,505 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.017222164919888927, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:24,505 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:24,526 [fs_likelihood.fslikelihood] Computed log-likelihood = -380.86
2023-07-02 10:33:24,526 [model] Computed derived parameters: {}
2023-07-02 10:33:24,526 [model] Posterior to be computed for parameters {'Omega_m': 0.31830586747927575, 'b1': 0.5195237182842224}
2023-07-02 10:33:24,526 [prior] Evaluating prior at array([0.31830587, 0.51952372])
2023-07-02 10:33:24,526 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:24,526 [model] Got input parameters: {'Omega_m': 0.31830586747927575, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:24,526 [classy] Got parameters {'Omega_m': 0.31830586747927575, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:24,526 [classy] Computing new state
2023-07-02 10:33:24,526 [classy] Setting parameters: {'Omega_m': 0.31830586747927575, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:24,570 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.5653448240577}
2023-07-02 10:33:24,570 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:24,572 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00225092
2023-07-02 10:33:24,572 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:24,572 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:24,592 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.11494
2023-07-02 10:33:24,592 [model] Computed derived parameters: {}
2023-07-02 10:33:24,592 [mcmc] New sample, #58:
Omega_m:0.310357, b1:0.5195237
2023-07-02 10:33:24,592 [model] Posterior to be computed for parameters {'Omega_m': 0.31830586747927575, 'b1': 1.0575120862193421}
2023-07-02 10:33:24,592 [prior] Evaluating prior at array([0.31830587, 1.05751209])
2023-07-02 10:33:24,592 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:24,592 [model] Got input parameters: {'Omega_m': 0.31830586747927575, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.0575120862193421, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:24,592 [classy] Got parameters {'Omega_m': 0.31830586747927575, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:24,592 [classy] Re-using computed results
2023-07-02 10:33:24,592 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.5653448240577}
2023-07-02 10:33:24,592 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:24,592 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.0575120862193421, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:24,592 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:24,613 [fs_likelihood.fslikelihood] Computed log-likelihood = -1436.91
2023-07-02 10:33:24,613 [model] Computed derived parameters: {}
2023-07-02 10:33:24,613 [model] Posterior to be computed for parameters {'Omega_m': 0.3231966957321344, 'b1': 0.5195237182842224}
2023-07-02 10:33:24,613 [prior] Evaluating prior at array([0.3231967 , 0.51952372])
2023-07-02 10:33:24,613 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:24,613 [model] Got input parameters: {'Omega_m': 0.3231966957321344, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:24,613 [classy] Got parameters {'Omega_m': 0.3231966957321344, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:24,613 [classy] Computing new state
2023-07-02 10:33:24,613 [classy] Setting parameters: {'Omega_m': 0.3231966957321344, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:24,657 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.99038509512}
2023-07-02 10:33:24,657 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:24,659 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00705596
2023-07-02 10:33:24,659 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:24,659 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:24,679 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.680164
2023-07-02 10:33:24,679 [model] Computed derived parameters: {}
2023-07-02 10:33:24,679 [model] Posterior to be computed for parameters {'Omega_m': 0.31830586747927575, 'b1': 1.7504185492310702}
2023-07-02 10:33:24,679 [prior] Evaluating prior at array([0.31830587, 1.75041855])
2023-07-02 10:33:24,679 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:24,679 [model] Got input parameters: {'Omega_m': 0.31830586747927575, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.7504185492310702, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:24,679 [classy] Got parameters {'Omega_m': 0.31830586747927575, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:24,679 [classy] Re-using computed results
2023-07-02 10:33:24,679 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.5653448240577}
2023-07-02 10:33:24,679 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:24,679 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.7504185492310702, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:24,679 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:24,699 [fs_likelihood.fslikelihood] Computed log-likelihood = -12038.2
2023-07-02 10:33:24,699 [model] Computed derived parameters: {}
2023-07-02 10:33:24,700 [model] Posterior to be computed for parameters {'Omega_m': 0.32767226246062503, 'b1': 0.5195237182842224}
2023-07-02 10:33:24,700 [prior] Evaluating prior at array([0.32767226, 0.51952372])
2023-07-02 10:33:24,700 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:24,700 [model] Got input parameters: {'Omega_m': 0.32767226246062503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:24,700 [classy] Got parameters {'Omega_m': 0.32767226246062503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:24,700 [classy] Computing new state
2023-07-02 10:33:24,700 [classy] Setting parameters: {'Omega_m': 0.32767226246062503, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:24,743 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.4710135077093}
2023-07-02 10:33:24,743 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:24,745 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0138308
2023-07-02 10:33:24,745 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:24,745 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:24,766 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.96072
2023-07-02 10:33:24,766 [model] Computed derived parameters: {}
2023-07-02 10:33:24,766 [model] Posterior to be computed for parameters {'Omega_m': 0.31830586747927575, 'b1': 2.9027508328963614}
2023-07-02 10:33:24,766 [prior] Evaluating prior at array([0.31830587, 2.90275083])
2023-07-02 10:33:24,766 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:24,766 [model] Got input parameters: {'Omega_m': 0.31830586747927575, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 2.9027508328963614, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:24,766 [classy] Got parameters {'Omega_m': 0.31830586747927575, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:24,766 [classy] Re-using computed results
2023-07-02 10:33:24,766 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.5653448240577}
2023-07-02 10:33:24,766 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:24,766 [fs_likelihood.fslikelihood] Got parameters {'b1': 2.9027508328963614, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:24,766 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:24,786 [fs_likelihood.fslikelihood] Computed log-likelihood = -85915.6
2023-07-02 10:33:24,786 [model] Computed derived parameters: {}
2023-07-02 10:33:24,786 [model] Posterior to be computed for parameters {'Omega_m': 0.2673348157751925, 'b1': 0.5195237182842224}
2023-07-02 10:33:24,786 [prior] Evaluating prior at array([0.26733482, 0.51952372])
2023-07-02 10:33:24,786 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:24,786 [model] Got input parameters: {'Omega_m': 0.2673348157751925, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:24,786 [classy] Got parameters {'Omega_m': 0.2673348157751925, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:24,786 [classy] Computing new state
2023-07-02 10:33:24,786 [classy] Setting parameters: {'Omega_m': 0.2673348157751925, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:24,830 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.06998584706656}
2023-07-02 10:33:24,830 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:24,832 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.140793
2023-07-02 10:33:24,832 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:24,832 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:24,852 [fs_likelihood.fslikelihood] Computed log-likelihood = -23.5036
2023-07-02 10:33:24,852 [model] Computed derived parameters: {}
2023-07-02 10:33:24,852 [model] Posterior to be computed for parameters {'Omega_m': 0.31830586747927575, 'b1': 0.8196620529927041}
2023-07-02 10:33:24,852 [prior] Evaluating prior at array([0.31830587, 0.81966205])
2023-07-02 10:33:24,853 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:24,853 [model] Got input parameters: {'Omega_m': 0.31830586747927575, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8196620529927041, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:24,853 [classy] Got parameters {'Omega_m': 0.31830586747927575, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:24,853 [classy] Re-using computed results
2023-07-02 10:33:24,853 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.5653448240577}
2023-07-02 10:33:24,853 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:24,853 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8196620529927041, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:24,853 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:24,873 [fs_likelihood.fslikelihood] Computed log-likelihood = -387.683
2023-07-02 10:33:24,873 [model] Computed derived parameters: {}
2023-07-02 10:33:24,873 [model] Posterior to be computed for parameters {'Omega_m': 0.31423781033551457, 'b1': 0.5195237182842224}
2023-07-02 10:33:24,873 [prior] Evaluating prior at array([0.31423781, 0.51952372])
2023-07-02 10:33:24,873 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:24,873 [model] Got input parameters: {'Omega_m': 0.31423781033551457, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:24,873 [classy] Got parameters {'Omega_m': 0.31423781033551457, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:24,873 [classy] Computing new state
2023-07-02 10:33:24,873 [classy] Setting parameters: {'Omega_m': 0.31423781033551457, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:24,917 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.04960475911685}
2023-07-02 10:33:24,917 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:24,919 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000390255
2023-07-02 10:33:24,919 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:24,919 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:24,939 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.05348
2023-07-02 10:33:24,939 [model] Computed derived parameters: {}
2023-07-02 10:33:24,939 [mcmc] New sample, #59:
Omega_m:0.3183059, b1:0.5195237
2023-07-02 10:33:24,939 [model] Posterior to be computed for parameters {'Omega_m': 0.31423781033551457, 'b1': 0.8253143886442103}
2023-07-02 10:33:24,939 [prior] Evaluating prior at array([0.31423781, 0.82531439])
2023-07-02 10:33:24,939 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:24,939 [model] Got input parameters: {'Omega_m': 0.31423781033551457, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8253143886442103, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:24,939 [classy] Got parameters {'Omega_m': 0.31423781033551457, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:24,939 [classy] Re-using computed results
2023-07-02 10:33:24,939 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.04960475911685}
2023-07-02 10:33:24,939 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:24,939 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8253143886442103, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:24,939 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:24,959 [fs_likelihood.fslikelihood] Computed log-likelihood = -381.066
2023-07-02 10:33:24,959 [model] Computed derived parameters: {}
2023-07-02 10:33:24,960 [model] Posterior to be computed for parameters {'Omega_m': 0.3051693498916591, 'b1': 0.5195237182842224}
2023-07-02 10:33:24,960 [prior] Evaluating prior at array([0.30516935, 0.51952372])
2023-07-02 10:33:24,960 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:24,960 [model] Got input parameters: {'Omega_m': 0.3051693498916591, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:24,960 [classy] Got parameters {'Omega_m': 0.3051693498916591, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:24,960 [classy] Computing new state
2023-07-02 10:33:24,960 [classy] Setting parameters: {'Omega_m': 0.3051693498916591, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:25,004 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.14953217415507}
2023-07-02 10:33:25,004 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:25,006 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00354408
2023-07-02 10:33:25,006 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:25,006 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:25,026 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.33296
2023-07-02 10:33:25,026 [model] Computed derived parameters: {}
2023-07-02 10:33:25,026 [mcmc] New sample, #60:
Omega_m:0.3142378, b1:0.5195237
2023-07-02 10:33:25,026 [model] Posterior to be computed for parameters {'Omega_m': 0.3051693498916591, 'b1': 2.905029832805368}
2023-07-02 10:33:25,026 [prior] Evaluating prior at array([0.30516935, 2.90502983])
2023-07-02 10:33:25,027 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:25,027 [model] Got input parameters: {'Omega_m': 0.3051693498916591, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 2.905029832805368, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:25,027 [classy] Got parameters {'Omega_m': 0.3051693498916591, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:25,027 [classy] Re-using computed results
2023-07-02 10:33:25,027 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.14953217415507}
2023-07-02 10:33:25,027 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:25,027 [fs_likelihood.fslikelihood] Got parameters {'b1': 2.905029832805368, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:25,027 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:25,046 [fs_likelihood.fslikelihood] Computed log-likelihood = -80952.8
2023-07-02 10:33:25,046 [model] Computed derived parameters: {}
2023-07-02 10:33:25,046 [model] Posterior to be computed for parameters {'Omega_m': 0.3079616920812791, 'b1': 0.5195237182842224}
2023-07-02 10:33:25,047 [prior] Evaluating prior at array([0.30796169, 0.51952372])
2023-07-02 10:33:25,047 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:25,047 [model] Got input parameters: {'Omega_m': 0.3079616920812791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:25,047 [classy] Got parameters {'Omega_m': 0.3079616920812791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:25,047 [classy] Computing new state
2023-07-02 10:33:25,047 [classy] Setting parameters: {'Omega_m': 0.3079616920812791, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:25,091 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.8078110716526}
2023-07-02 10:33:25,091 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:25,092 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00147081
2023-07-02 10:33:25,092 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:25,092 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:25,113 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.51357
2023-07-02 10:33:25,113 [model] Computed derived parameters: {}
2023-07-02 10:33:25,113 [mcmc] New sample, #61:
Omega_m:0.3051693, b1:0.5195237
2023-07-02 10:33:25,113 [model] Posterior to be computed for parameters {'Omega_m': 0.3079616920812791, 'b1': 0.6321737352190662}
2023-07-02 10:33:25,113 [prior] Evaluating prior at array([0.30796169, 0.63217374])
2023-07-02 10:33:25,113 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:25,113 [model] Got input parameters: {'Omega_m': 0.3079616920812791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6321737352190662, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:25,113 [classy] Got parameters {'Omega_m': 0.3079616920812791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:25,113 [classy] Re-using computed results
2023-07-02 10:33:25,113 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.8078110716526}
2023-07-02 10:33:25,113 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:25,113 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6321737352190662, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:25,113 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:25,136 [fs_likelihood.fslikelihood] Computed log-likelihood = -40.0195
2023-07-02 10:33:25,136 [model] Computed derived parameters: {}
2023-07-02 10:33:25,136 [model] Posterior to be computed for parameters {'Omega_m': 0.3361635290202818, 'b1': 0.5195237182842224}
2023-07-02 10:33:25,136 [prior] Evaluating prior at array([0.33616353, 0.51952372])
2023-07-02 10:33:25,136 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:25,136 [model] Got input parameters: {'Omega_m': 0.3361635290202818, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:25,136 [classy] Got parameters {'Omega_m': 0.3361635290202818, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:25,136 [classy] Computing new state
2023-07-02 10:33:25,136 [classy] Setting parameters: {'Omega_m': 0.3361635290202818, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:25,181 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.50301713651234}
2023-07-02 10:33:25,181 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:25,183 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0326601
2023-07-02 10:33:25,183 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:25,183 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:25,203 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.96293
2023-07-02 10:33:25,203 [model] Computed derived parameters: {}
2023-07-02 10:33:25,203 [model] Posterior to be computed for parameters {'Omega_m': 0.3079616920812791, 'b1': 0.23344409875363226}
2023-07-02 10:33:25,203 [prior] Evaluating prior at array([0.30796169, 0.2334441 ])
2023-07-02 10:33:25,203 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:25,203 [model] Got input parameters: {'Omega_m': 0.3079616920812791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.23344409875363226, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:25,203 [classy] Got parameters {'Omega_m': 0.3079616920812791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:25,203 [classy] Re-using computed results
2023-07-02 10:33:25,203 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.8078110716526}
2023-07-02 10:33:25,203 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:25,203 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.23344409875363226, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:25,203 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:25,223 [fs_likelihood.fslikelihood] Computed log-likelihood = -153.895
2023-07-02 10:33:25,223 [model] Computed derived parameters: {}
2023-07-02 10:33:25,224 [model] Posterior to be computed for parameters {'Omega_m': 0.3328194360825727, 'b1': 0.5195237182842224}
2023-07-02 10:33:25,224 [prior] Evaluating prior at array([0.33281944, 0.51952372])
2023-07-02 10:33:25,224 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:25,224 [model] Got input parameters: {'Omega_m': 0.3328194360825727, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:25,224 [classy] Got parameters {'Omega_m': 0.3328194360825727, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:25,224 [classy] Computing new state
2023-07-02 10:33:25,224 [classy] Setting parameters: {'Omega_m': 0.3328194360825727, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:25,268 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.88157058211928}
2023-07-02 10:33:25,268 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:25,269 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.024332
2023-07-02 10:33:25,269 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:25,269 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:25,290 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.33718
2023-07-02 10:33:25,290 [model] Computed derived parameters: {}
2023-07-02 10:33:25,290 [model] Posterior to be computed for parameters {'Omega_m': 0.3079616920812791, 'b1': 1.2195424712990772}
2023-07-02 10:33:25,290 [prior] Evaluating prior at array([0.30796169, 1.21954247])
2023-07-02 10:33:25,290 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:25,290 [model] Got input parameters: {'Omega_m': 0.3079616920812791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.2195424712990772, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:25,290 [classy] Got parameters {'Omega_m': 0.3079616920812791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:25,290 [classy] Re-using computed results
2023-07-02 10:33:25,290 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.8078110716526}
2023-07-02 10:33:25,290 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:25,290 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.2195424712990772, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:25,290 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:25,310 [fs_likelihood.fslikelihood] Computed log-likelihood = -2505.91
2023-07-02 10:33:25,310 [model] Computed derived parameters: {}
2023-07-02 10:33:25,311 [model] Posterior to be computed for parameters {'Omega_m': 0.33238393811256584, 'b1': 0.5195237182842224}
2023-07-02 10:33:25,311 [prior] Evaluating prior at array([0.33238394, 0.51952372])
2023-07-02 10:33:25,311 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:25,311 [model] Got input parameters: {'Omega_m': 0.33238393811256584, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:25,311 [classy] Got parameters {'Omega_m': 0.33238393811256584, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:25,311 [classy] Computing new state
2023-07-02 10:33:25,311 [classy] Setting parameters: {'Omega_m': 0.33238393811256584, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:25,354 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.931122209442}
2023-07-02 10:33:25,355 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:25,356 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0233338
2023-07-02 10:33:25,356 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:25,356 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:25,376 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.02028
2023-07-02 10:33:25,377 [model] Computed derived parameters: {}
2023-07-02 10:33:25,377 [model] Posterior to be computed for parameters {'Omega_m': 0.3079616920812791, 'b1': -0.10194500079011903}
2023-07-02 10:33:25,377 [prior] Evaluating prior at array([ 0.30796169, -0.101945 ])
2023-07-02 10:33:25,377 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:25,377 [model] Posterior to be computed for parameters {'Omega_m': 0.284914693969706, 'b1': 0.5195237182842224}
2023-07-02 10:33:25,377 [prior] Evaluating prior at array([0.28491469, 0.51952372])
2023-07-02 10:33:25,377 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:25,377 [model] Got input parameters: {'Omega_m': 0.284914693969706, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:25,377 [classy] Got parameters {'Omega_m': 0.284914693969706, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:25,377 [classy] Computing new state
2023-07-02 10:33:25,377 [classy] Setting parameters: {'Omega_m': 0.284914693969706, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:25,421 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.71364698532796}
2023-07-02 10:33:25,421 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:25,423 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.050213
2023-07-02 10:33:25,423 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:25,423 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:25,442 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.08037
2023-07-02 10:33:25,443 [model] Computed derived parameters: {}
2023-07-02 10:33:25,443 [model] Posterior to be computed for parameters {'Omega_m': 0.3079616920812791, 'b1': 0.8090922166331185}
2023-07-02 10:33:25,443 [prior] Evaluating prior at array([0.30796169, 0.80909222])
2023-07-02 10:33:25,443 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:25,443 [model] Got input parameters: {'Omega_m': 0.3079616920812791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8090922166331185, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:25,443 [classy] Got parameters {'Omega_m': 0.3079616920812791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:25,443 [classy] Re-using computed results
2023-07-02 10:33:25,443 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.8078110716526}
2023-07-02 10:33:25,443 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:25,443 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8090922166331185, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:25,443 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:25,463 [fs_likelihood.fslikelihood] Computed log-likelihood = -308.342
2023-07-02 10:33:25,463 [model] Computed derived parameters: {}
2023-07-02 10:33:25,463 [model] Posterior to be computed for parameters {'Omega_m': 0.2982008582249032, 'b1': 0.5195237182842224}
2023-07-02 10:33:25,463 [prior] Evaluating prior at array([0.29820086, 0.51952372])
2023-07-02 10:33:25,463 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:25,463 [model] Got input parameters: {'Omega_m': 0.2982008582249032, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:25,463 [classy] Got parameters {'Omega_m': 0.2982008582249032, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:25,464 [classy] Computing new state
2023-07-02 10:33:25,464 [classy] Setting parameters: {'Omega_m': 0.2982008582249032, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:25,507 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.0144729111208}
2023-07-02 10:33:25,508 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:25,509 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0131711
2023-07-02 10:33:25,509 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:25,509 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:25,530 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.847218
2023-07-02 10:33:25,530 [model] Computed derived parameters: {}
2023-07-02 10:33:25,530 [model] Posterior to be computed for parameters {'Omega_m': 0.3079616920812791, 'b1': -1.7628234533603373}
2023-07-02 10:33:25,530 [prior] Evaluating prior at array([ 0.30796169, -1.76282345])
2023-07-02 10:33:25,531 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:25,531 [model] Posterior to be computed for parameters {'Omega_m': 0.30447441477554194, 'b1': 0.5195237182842224}
2023-07-02 10:33:25,531 [prior] Evaluating prior at array([0.30447441, 0.51952372])
2023-07-02 10:33:25,531 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:25,531 [model] Got input parameters: {'Omega_m': 0.30447441477554194, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:25,531 [classy] Got parameters {'Omega_m': 0.30447441477554194, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:25,531 [classy] Computing new state
2023-07-02 10:33:25,531 [classy] Setting parameters: {'Omega_m': 0.30447441477554194, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:25,575 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2350034609921}
2023-07-02 10:33:25,575 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:25,577 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00421619
2023-07-02 10:33:25,577 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:25,577 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:25,597 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.25113
2023-07-02 10:33:25,597 [model] Computed derived parameters: {}
2023-07-02 10:33:25,597 [model] Posterior to be computed for parameters {'Omega_m': 0.3079616920812791, 'b1': 1.235299982626457}
2023-07-02 10:33:25,597 [prior] Evaluating prior at array([0.30796169, 1.23529998])
2023-07-02 10:33:25,597 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:25,597 [model] Got input parameters: {'Omega_m': 0.3079616920812791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.235299982626457, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:25,598 [classy] Got parameters {'Omega_m': 0.3079616920812791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:25,598 [classy] Re-using computed results
2023-07-02 10:33:25,598 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.8078110716526}
2023-07-02 10:33:25,598 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:25,598 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.235299982626457, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:25,598 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:25,619 [fs_likelihood.fslikelihood] Computed log-likelihood = -2651.87
2023-07-02 10:33:25,619 [model] Computed derived parameters: {}
2023-07-02 10:33:25,619 [model] Posterior to be computed for parameters {'Omega_m': 0.3194329461577319, 'b1': 0.5195237182842224}
2023-07-02 10:33:25,619 [prior] Evaluating prior at array([0.31943295, 0.51952372])
2023-07-02 10:33:25,619 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:25,619 [model] Got input parameters: {'Omega_m': 0.3194329461577319, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:25,619 [classy] Got parameters {'Omega_m': 0.3194329461577319, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:25,619 [classy] Computing new state
2023-07-02 10:33:25,619 [classy] Setting parameters: {'Omega_m': 0.3194329461577319, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:25,664 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.43215211073266}
2023-07-02 10:33:25,664 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:25,666 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00311276
2023-07-02 10:33:25,666 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:25,666 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:25,687 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.765809
2023-07-02 10:33:25,687 [model] Computed derived parameters: {}
2023-07-02 10:33:25,687 [model] Posterior to be computed for parameters {'Omega_m': 0.3079616920812791, 'b1': 0.13569190346342513}
2023-07-02 10:33:25,688 [prior] Evaluating prior at array([0.30796169, 0.1356919 ])
2023-07-02 10:33:25,688 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:25,688 [model] Got input parameters: {'Omega_m': 0.3079616920812791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.13569190346342513, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:25,688 [classy] Got parameters {'Omega_m': 0.3079616920812791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:25,688 [classy] Re-using computed results
2023-07-02 10:33:25,688 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.8078110716526}
2023-07-02 10:33:25,688 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:25,688 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.13569190346342513, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:25,688 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:25,709 [fs_likelihood.fslikelihood] Computed log-likelihood = -253.573
2023-07-02 10:33:25,709 [model] Computed derived parameters: {}
2023-07-02 10:33:25,709 [model] Posterior to be computed for parameters {'Omega_m': 0.2995079138545972, 'b1': 0.5195237182842224}
2023-07-02 10:33:25,709 [prior] Evaluating prior at array([0.29950791, 0.51952372])
2023-07-02 10:33:25,709 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:25,709 [model] Got input parameters: {'Omega_m': 0.2995079138545972, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:25,709 [classy] Got parameters {'Omega_m': 0.2995079138545972, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:25,709 [classy] Computing new state
2023-07-02 10:33:25,709 [classy] Setting parameters: {'Omega_m': 0.2995079138545972, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:25,755 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.85088614150735}
2023-07-02 10:33:25,755 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:25,756 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0108702
2023-07-02 10:33:25,756 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:25,756 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:25,778 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.23849
2023-07-02 10:33:25,778 [model] Computed derived parameters: {}
2023-07-02 10:33:25,779 [model] Posterior to be computed for parameters {'Omega_m': 0.3079616920812791, 'b1': 0.5969587301513756}
2023-07-02 10:33:25,779 [prior] Evaluating prior at array([0.30796169, 0.59695873])
2023-07-02 10:33:25,779 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:25,779 [model] Got input parameters: {'Omega_m': 0.3079616920812791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5969587301513756, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:25,779 [classy] Got parameters {'Omega_m': 0.3079616920812791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:25,779 [classy] Re-using computed results
2023-07-02 10:33:25,779 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.8078110716526}
2023-07-02 10:33:25,779 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:25,779 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5969587301513756, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:25,779 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:25,799 [fs_likelihood.fslikelihood] Computed log-likelihood = -17.8137
2023-07-02 10:33:25,799 [model] Computed derived parameters: {}
2023-07-02 10:33:25,799 [model] Posterior to be computed for parameters {'Omega_m': 0.2940096597205522, 'b1': 0.5195237182842224}
2023-07-02 10:33:25,799 [prior] Evaluating prior at array([0.29400966, 0.51952372])
2023-07-02 10:33:25,799 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:25,799 [model] Got input parameters: {'Omega_m': 0.2940096597205522, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:25,799 [classy] Got parameters {'Omega_m': 0.2940096597205522, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:25,799 [classy] Computing new state
2023-07-02 10:33:25,799 [classy] Setting parameters: {'Omega_m': 0.2940096597205522, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:25,843 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.5432744987018}
2023-07-02 10:33:25,844 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:25,845 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0221343
2023-07-02 10:33:25,845 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:25,845 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:25,865 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.758095
2023-07-02 10:33:25,865 [model] Computed derived parameters: {}
2023-07-02 10:33:25,865 [model] Posterior to be computed for parameters {'Omega_m': 0.3079616920812791, 'b1': 0.46873955981859783}
2023-07-02 10:33:25,865 [prior] Evaluating prior at array([0.30796169, 0.46873956])
2023-07-02 10:33:25,866 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:25,866 [model] Got input parameters: {'Omega_m': 0.3079616920812791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46873955981859783, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:25,866 [classy] Got parameters {'Omega_m': 0.3079616920812791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:25,866 [classy] Re-using computed results
2023-07-02 10:33:25,866 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.8078110716526}
2023-07-02 10:33:25,866 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:25,866 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46873955981859783, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:25,866 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:25,886 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.42157
2023-07-02 10:33:25,887 [model] Computed derived parameters: {}
2023-07-02 10:33:25,887 [model] Posterior to be computed for parameters {'Omega_m': 0.3072416390385678, 'b1': 0.5195237182842224}
2023-07-02 10:33:25,887 [prior] Evaluating prior at array([0.30724164, 0.51952372])
2023-07-02 10:33:25,887 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:25,887 [model] Got input parameters: {'Omega_m': 0.3072416390385678, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:25,887 [classy] Got parameters {'Omega_m': 0.3072416390385678, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:25,887 [classy] Computing new state
2023-07-02 10:33:25,887 [classy] Setting parameters: {'Omega_m': 0.3072416390385678, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:25,931 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.89566992917867}
2023-07-02 10:33:25,931 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:25,933 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00190998
2023-07-02 10:33:25,933 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:25,933 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:25,952 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.4897
2023-07-02 10:33:25,953 [model] Computed derived parameters: {}
2023-07-02 10:33:25,953 [mcmc] New sample, #62:
Omega_m:0.3079617, b1:0.5195237
2023-07-02 10:33:25,953 [model] Posterior to be computed for parameters {'Omega_m': 0.3072416390385678, 'b1': 1.1647778911305142}
2023-07-02 10:33:25,953 [prior] Evaluating prior at array([0.30724164, 1.16477789])
2023-07-02 10:33:25,953 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:25,953 [model] Got input parameters: {'Omega_m': 0.3072416390385678, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.1647778911305142, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:25,953 [classy] Got parameters {'Omega_m': 0.3072416390385678, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:25,953 [classy] Re-using computed results
2023-07-02 10:33:25,953 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.89566992917867}
2023-07-02 10:33:25,953 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:25,953 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.1647778911305142, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:25,953 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:25,973 [fs_likelihood.fslikelihood] Computed log-likelihood = -2028.34
2023-07-02 10:33:25,973 [model] Computed derived parameters: {}
2023-07-02 10:33:25,973 [model] Posterior to be computed for parameters {'Omega_m': 0.30133973011809095, 'b1': 0.5195237182842224}
2023-07-02 10:33:25,973 [prior] Evaluating prior at array([0.30133973, 0.51952372])
2023-07-02 10:33:25,973 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:25,973 [model] Got input parameters: {'Omega_m': 0.30133973011809095, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:25,973 [classy] Got parameters {'Omega_m': 0.30133973011809095, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:25,973 [classy] Computing new state
2023-07-02 10:33:25,974 [classy] Setting parameters: {'Omega_m': 0.30133973011809095, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:26,017 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.6226818769937}
2023-07-02 10:33:26,017 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:26,019 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0080342
2023-07-02 10:33:26,019 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:26,019 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:26,039 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.69936
2023-07-02 10:33:26,039 [model] Computed derived parameters: {}
2023-07-02 10:33:26,040 [model] Posterior to be computed for parameters {'Omega_m': 0.3072416390385678, 'b1': 0.39802286175431345}
2023-07-02 10:33:26,040 [prior] Evaluating prior at array([0.30724164, 0.39802286])
2023-07-02 10:33:26,040 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:26,040 [model] Got input parameters: {'Omega_m': 0.3072416390385678, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.39802286175431345, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:26,040 [classy] Got parameters {'Omega_m': 0.3072416390385678, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:26,040 [classy] Re-using computed results
2023-07-02 10:33:26,040 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.89566992917867}
2023-07-02 10:33:26,040 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:26,040 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.39802286175431345, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:26,040 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:26,060 [fs_likelihood.fslikelihood] Computed log-likelihood = -29.651
2023-07-02 10:33:26,061 [model] Computed derived parameters: {}
2023-07-02 10:33:26,061 [model] Posterior to be computed for parameters {'Omega_m': 0.31703966455068633, 'b1': 0.5195237182842224}
2023-07-02 10:33:26,061 [prior] Evaluating prior at array([0.31703966, 0.51952372])
2023-07-02 10:33:26,061 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:26,061 [model] Got input parameters: {'Omega_m': 0.31703966455068633, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:26,061 [classy] Got parameters {'Omega_m': 0.31703966455068633, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:26,061 [classy] Computing new state
2023-07-02 10:33:26,061 [classy] Setting parameters: {'Omega_m': 0.31703966455068633, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:26,105 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.71547649536305}
2023-07-02 10:33:26,105 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:26,107 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00146075
2023-07-02 10:33:26,107 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:26,107 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:26,129 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.46105
2023-07-02 10:33:26,129 [model] Computed derived parameters: {}
2023-07-02 10:33:26,129 [model] Posterior to be computed for parameters {'Omega_m': 0.3072416390385678, 'b1': 0.8757405683545079}
2023-07-02 10:33:26,129 [prior] Evaluating prior at array([0.30724164, 0.87574057])
2023-07-02 10:33:26,129 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:26,129 [model] Got input parameters: {'Omega_m': 0.3072416390385678, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8757405683545079, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:26,129 [classy] Got parameters {'Omega_m': 0.3072416390385678, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:26,129 [classy] Re-using computed results
2023-07-02 10:33:26,129 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.89566992917867}
2023-07-02 10:33:26,129 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:26,129 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8757405683545079, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:26,130 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:26,150 [fs_likelihood.fslikelihood] Computed log-likelihood = -488.406
2023-07-02 10:33:26,150 [model] Computed derived parameters: {}
2023-07-02 10:33:26,150 [model] Posterior to be computed for parameters {'Omega_m': 0.28906961564474176, 'b1': 0.5195237182842224}
2023-07-02 10:33:26,150 [prior] Evaluating prior at array([0.28906962, 0.51952372])
2023-07-02 10:33:26,150 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:26,150 [model] Got input parameters: {'Omega_m': 0.28906961564474176, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:26,150 [classy] Got parameters {'Omega_m': 0.28906961564474176, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:26,150 [classy] Computing new state
2023-07-02 10:33:26,151 [classy] Setting parameters: {'Omega_m': 0.28906961564474176, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:26,194 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.17502106524663}
2023-07-02 10:33:26,194 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:26,196 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0358851
2023-07-02 10:33:26,196 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:26,196 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:26,216 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.33663
2023-07-02 10:33:26,216 [model] Computed derived parameters: {}
2023-07-02 10:33:26,216 [model] Posterior to be computed for parameters {'Omega_m': 0.3072416390385678, 'b1': 0.22734163785337874}
2023-07-02 10:33:26,216 [prior] Evaluating prior at array([0.30724164, 0.22734164])
2023-07-02 10:33:26,216 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:26,216 [model] Got input parameters: {'Omega_m': 0.3072416390385678, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.22734163785337874, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:26,216 [classy] Got parameters {'Omega_m': 0.3072416390385678, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:26,216 [classy] Re-using computed results
2023-07-02 10:33:26,216 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.89566992917867}
2023-07-02 10:33:26,216 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:26,216 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.22734163785337874, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:26,216 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:26,237 [fs_likelihood.fslikelihood] Computed log-likelihood = -160.941
2023-07-02 10:33:26,237 [model] Computed derived parameters: {}
2023-07-02 10:33:26,237 [model] Posterior to be computed for parameters {'Omega_m': 0.31079882662289215, 'b1': 0.5195237182842224}
2023-07-02 10:33:26,237 [prior] Evaluating prior at array([0.31079883, 0.51952372])
2023-07-02 10:33:26,237 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:26,237 [model] Got input parameters: {'Omega_m': 0.31079882662289215, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:26,237 [classy] Got parameters {'Omega_m': 0.31079882662289215, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:26,237 [classy] Computing new state
2023-07-02 10:33:26,237 [classy] Setting parameters: {'Omega_m': 0.31079882662289215, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:26,281 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.46338818545397}
2023-07-02 10:33:26,281 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:26,283 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000377253
2023-07-02 10:33:26,283 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:26,283 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:26,303 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.45405
2023-07-02 10:33:26,303 [model] Computed derived parameters: {}
2023-07-02 10:33:26,303 [mcmc] New sample, #63:
Omega_m:0.3072416, b1:0.5195237
2023-07-02 10:33:26,303 [model] Posterior to be computed for parameters {'Omega_m': 0.31079882662289215, 'b1': 0.48447863243664985}
2023-07-02 10:33:26,303 [prior] Evaluating prior at array([0.31079883, 0.48447863])
2023-07-02 10:33:26,303 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:26,303 [model] Got input parameters: {'Omega_m': 0.31079882662289215, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48447863243664985, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:26,303 [classy] Got parameters {'Omega_m': 0.31079882662289215, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:26,303 [classy] Re-using computed results
2023-07-02 10:33:26,303 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.46338818545397}
2023-07-02 10:33:26,303 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:26,303 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48447863243664985, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:26,304 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:26,324 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.36821
2023-07-02 10:33:26,324 [model] Computed derived parameters: {}
2023-07-02 10:33:26,324 [model] Posterior to be computed for parameters {'Omega_m': 0.30491062563358523, 'b1': 0.5195237182842224}
2023-07-02 10:33:26,324 [prior] Evaluating prior at array([0.30491063, 0.51952372])
2023-07-02 10:33:26,324 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:26,324 [model] Got input parameters: {'Omega_m': 0.30491062563358523, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:26,324 [classy] Got parameters {'Omega_m': 0.30491062563358523, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:26,324 [classy] Computing new state
2023-07-02 10:33:26,324 [classy] Setting parameters: {'Omega_m': 0.30491062563358523, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:26,368 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.18133469907934}
2023-07-02 10:33:26,368 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:26,370 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.003787
2023-07-02 10:33:26,370 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:26,370 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:26,390 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.30421
2023-07-02 10:33:26,390 [model] Computed derived parameters: {}
2023-07-02 10:33:26,390 [mcmc] New sample, #64:
Omega_m:0.3107988, b1:0.5195237
2023-07-02 10:33:26,390 [model] Posterior to be computed for parameters {'Omega_m': 0.30491062563358523, 'b1': 1.7018034328713654}
2023-07-02 10:33:26,390 [prior] Evaluating prior at array([0.30491063, 1.70180343])
2023-07-02 10:33:26,391 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:26,391 [model] Got input parameters: {'Omega_m': 0.30491062563358523, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.7018034328713654, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:26,391 [classy] Got parameters {'Omega_m': 0.30491062563358523, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:26,391 [classy] Re-using computed results
2023-07-02 10:33:26,391 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.18133469907934}
2023-07-02 10:33:26,391 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:26,391 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.7018034328713654, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:26,391 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:26,411 [fs_likelihood.fslikelihood] Computed log-likelihood = -9924.67
2023-07-02 10:33:26,411 [model] Computed derived parameters: {}
2023-07-02 10:33:26,411 [model] Posterior to be computed for parameters {'Omega_m': 0.30689077278800003, 'b1': 0.5195237182842224}
2023-07-02 10:33:26,411 [prior] Evaluating prior at array([0.30689077, 0.51952372])
2023-07-02 10:33:26,411 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:26,411 [model] Got input parameters: {'Omega_m': 0.30689077278800003, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:26,411 [classy] Got parameters {'Omega_m': 0.30689077278800003, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:26,411 [classy] Computing new state
2023-07-02 10:33:26,411 [classy] Setting parameters: {'Omega_m': 0.30689077278800003, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:26,459 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.93854525778107}
2023-07-02 10:33:26,460 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:26,461 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0021479
2023-07-02 10:33:26,461 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:26,462 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:26,483 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.47235
2023-07-02 10:33:26,483 [model] Computed derived parameters: {}
2023-07-02 10:33:26,483 [mcmc] New sample, #65:
Omega_m:0.3049106, b1:0.5195237
2023-07-02 10:33:26,483 [model] Posterior to be computed for parameters {'Omega_m': 0.30689077278800003, 'b1': -0.7242928519955681}
2023-07-02 10:33:26,483 [prior] Evaluating prior at array([ 0.30689077, -0.72429285])
2023-07-02 10:33:26,483 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:26,483 [model] Posterior to be computed for parameters {'Omega_m': 0.32024040330016973, 'b1': 0.5195237182842224}
2023-07-02 10:33:26,483 [prior] Evaluating prior at array([0.3202404 , 0.51952372])
2023-07-02 10:33:26,483 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:26,483 [model] Got input parameters: {'Omega_m': 0.32024040330016973, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:26,483 [classy] Got parameters {'Omega_m': 0.32024040330016973, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:26,484 [classy] Computing new state
2023-07-02 10:33:26,484 [classy] Setting parameters: {'Omega_m': 0.32024040330016973, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:26,528 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.3369878768257}
2023-07-02 10:33:26,528 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:26,530 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00382124
2023-07-02 10:33:26,530 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:26,530 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:26,550 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.49192
2023-07-02 10:33:26,550 [model] Computed derived parameters: {}
2023-07-02 10:33:26,550 [model] Posterior to be computed for parameters {'Omega_m': 0.30689077278800003, 'b1': 1.4737475672089861}
2023-07-02 10:33:26,550 [prior] Evaluating prior at array([0.30689077, 1.47374757])
2023-07-02 10:33:26,550 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:26,550 [model] Got input parameters: {'Omega_m': 0.30689077278800003, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.4737475672089861, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:26,550 [classy] Got parameters {'Omega_m': 0.30689077278800003, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:26,550 [classy] Re-using computed results
2023-07-02 10:33:26,550 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.93854525778107}
2023-07-02 10:33:26,550 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:26,550 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.4737475672089861, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:26,550 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:26,570 [fs_likelihood.fslikelihood] Computed log-likelihood = -5582.97
2023-07-02 10:33:26,570 [model] Computed derived parameters: {}
2023-07-02 10:33:26,570 [model] Posterior to be computed for parameters {'Omega_m': 0.33343142329749453, 'b1': 0.5195237182842224}
2023-07-02 10:33:26,570 [prior] Evaluating prior at array([0.33343142, 0.51952372])
2023-07-02 10:33:26,570 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:26,570 [model] Got input parameters: {'Omega_m': 0.33343142329749453, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:26,570 [classy] Got parameters {'Omega_m': 0.33343142329749453, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:26,570 [classy] Computing new state
2023-07-02 10:33:26,570 [classy] Setting parameters: {'Omega_m': 0.33343142329749453, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:26,614 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.8120359681545}
2023-07-02 10:33:26,614 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:26,615 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0257687
2023-07-02 10:33:26,616 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:26,616 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:26,636 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.79227
2023-07-02 10:33:26,636 [model] Computed derived parameters: {}
2023-07-02 10:33:26,636 [model] Posterior to be computed for parameters {'Omega_m': 0.30689077278800003, 'b1': -0.5045437248776469}
2023-07-02 10:33:26,636 [prior] Evaluating prior at array([ 0.30689077, -0.50454372])
2023-07-02 10:33:26,637 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:26,637 [model] Posterior to be computed for parameters {'Omega_m': 0.2989405460357108, 'b1': 0.5195237182842224}
2023-07-02 10:33:26,637 [prior] Evaluating prior at array([0.29894055, 0.51952372])
2023-07-02 10:33:26,637 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:26,637 [model] Got input parameters: {'Omega_m': 0.2989405460357108, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:26,637 [classy] Got parameters {'Omega_m': 0.2989405460357108, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:26,637 [classy] Computing new state
2023-07-02 10:33:26,637 [classy] Setting parameters: {'Omega_m': 0.2989405460357108, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:26,681 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.92181981975565}
2023-07-02 10:33:26,681 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:26,683 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0118405
2023-07-02 10:33:26,683 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:26,683 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:26,703 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.07503
2023-07-02 10:33:26,703 [model] Computed derived parameters: {}
2023-07-02 10:33:26,703 [mcmc] New sample, #66:
Omega_m:0.3068908, b1:0.5195237
2023-07-02 10:33:26,703 [model] Posterior to be computed for parameters {'Omega_m': 0.2989405460357108, 'b1': -0.08300294939514119}
2023-07-02 10:33:26,703 [prior] Evaluating prior at array([ 0.29894055, -0.08300295])
2023-07-02 10:33:26,703 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:26,704 [model] Posterior to be computed for parameters {'Omega_m': 0.29822350627657324, 'b1': 0.5195237182842224}
2023-07-02 10:33:26,704 [prior] Evaluating prior at array([0.29822351, 0.51952372])
2023-07-02 10:33:26,704 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:26,704 [model] Got input parameters: {'Omega_m': 0.29822350627657324, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:26,704 [classy] Got parameters {'Omega_m': 0.29822350627657324, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:26,704 [classy] Computing new state
2023-07-02 10:33:26,704 [classy] Setting parameters: {'Omega_m': 0.29822350627657324, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:26,748 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.0116352036433}
2023-07-02 10:33:26,749 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:26,750 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0131293
2023-07-02 10:33:26,750 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:26,750 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:26,770 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.85444
2023-07-02 10:33:26,770 [model] Computed derived parameters: {}
2023-07-02 10:33:26,770 [model] Posterior to be computed for parameters {'Omega_m': 0.2989405460357108, 'b1': -0.6037498143502248}
2023-07-02 10:33:26,770 [prior] Evaluating prior at array([ 0.29894055, -0.60374981])
2023-07-02 10:33:26,770 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:26,770 [model] Posterior to be computed for parameters {'Omega_m': 0.29710768172004637, 'b1': 0.5195237182842224}
2023-07-02 10:33:26,770 [prior] Evaluating prior at array([0.29710768, 0.51952372])
2023-07-02 10:33:26,771 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:26,771 [model] Got input parameters: {'Omega_m': 0.29710768172004637, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:26,771 [classy] Got parameters {'Omega_m': 0.29710768172004637, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:26,771 [classy] Computing new state
2023-07-02 10:33:26,771 [classy] Setting parameters: {'Omega_m': 0.29710768172004637, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:26,814 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.15177282220907}
2023-07-02 10:33:26,815 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:26,816 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0152746
2023-07-02 10:33:26,816 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:26,816 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:26,836 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.480043
2023-07-02 10:33:26,836 [model] Computed derived parameters: {}
2023-07-02 10:33:26,837 [model] Posterior to be computed for parameters {'Omega_m': 0.2989405460357108, 'b1': 0.4768268561713}
2023-07-02 10:33:26,837 [prior] Evaluating prior at array([0.29894055, 0.47682686])
2023-07-02 10:33:26,837 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:26,837 [model] Got input parameters: {'Omega_m': 0.2989405460357108, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4768268561713, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:26,837 [classy] Got parameters {'Omega_m': 0.2989405460357108, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:26,837 [classy] Re-using computed results
2023-07-02 10:33:26,837 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.92181981975565}
2023-07-02 10:33:26,837 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:26,837 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4768268561713, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:26,837 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:26,857 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.64516
2023-07-02 10:33:26,857 [model] Computed derived parameters: {}
2023-07-02 10:33:26,857 [model] Posterior to be computed for parameters {'Omega_m': 0.31546003866230893, 'b1': 0.5195237182842224}
2023-07-02 10:33:26,857 [prior] Evaluating prior at array([0.31546004, 0.51952372])
2023-07-02 10:33:26,857 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:26,857 [model] Got input parameters: {'Omega_m': 0.31546003866230893, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:26,857 [classy] Got parameters {'Omega_m': 0.31546003866230893, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:26,857 [classy] Computing new state
2023-07-02 10:33:26,857 [classy] Setting parameters: {'Omega_m': 0.31546003866230893, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:26,901 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.9035219753674}
2023-07-02 10:33:26,901 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:26,903 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000741594
2023-07-02 10:33:26,903 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:26,903 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:26,923 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.82443
2023-07-02 10:33:26,923 [model] Computed derived parameters: {}
2023-07-02 10:33:26,923 [mcmc] New sample, #67:
Omega_m:0.2989405, b1:0.5195237
2023-07-02 10:33:26,923 [model] Posterior to be computed for parameters {'Omega_m': 0.31546003866230893, 'b1': 0.933315576959987}
2023-07-02 10:33:26,923 [prior] Evaluating prior at array([0.31546004, 0.93331558])
2023-07-02 10:33:26,923 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:26,923 [model] Got input parameters: {'Omega_m': 0.31546003866230893, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.933315576959987, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:26,923 [classy] Got parameters {'Omega_m': 0.31546003866230893, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:26,923 [classy] Re-using computed results
2023-07-02 10:33:26,923 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.9035219753674}
2023-07-02 10:33:26,923 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:26,923 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.933315576959987, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:26,923 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:26,944 [fs_likelihood.fslikelihood] Computed log-likelihood = -759.238
2023-07-02 10:33:26,944 [model] Computed derived parameters: {}
2023-07-02 10:33:26,944 [model] Posterior to be computed for parameters {'Omega_m': 0.3983003739067321, 'b1': 0.5195237182842224}
2023-07-02 10:33:26,944 [prior] Evaluating prior at array([0.39830037, 0.51952372])
2023-07-02 10:33:26,944 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:26,944 [model] Got input parameters: {'Omega_m': 0.3983003739067321, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:26,944 [classy] Got parameters {'Omega_m': 0.3983003739067321, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:26,944 [classy] Computing new state
2023-07-02 10:33:26,944 [classy] Setting parameters: {'Omega_m': 0.3983003739067321, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:26,988 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 138.03501347492517}
2023-07-02 10:33:26,988 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:26,990 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.370792
2023-07-02 10:33:26,990 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:26,990 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:27,010 [fs_likelihood.fslikelihood] Computed log-likelihood = -119.665
2023-07-02 10:33:27,010 [model] Computed derived parameters: {}
2023-07-02 10:33:27,010 [model] Posterior to be computed for parameters {'Omega_m': 0.31546003866230893, 'b1': -0.02033975695346002}
2023-07-02 10:33:27,010 [prior] Evaluating prior at array([ 0.31546004, -0.02033976])
2023-07-02 10:33:27,010 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:27,011 [model] Posterior to be computed for parameters {'Omega_m': 0.31072027943400077, 'b1': 0.5195237182842224}
2023-07-02 10:33:27,011 [prior] Evaluating prior at array([0.31072028, 0.51952372])
2023-07-02 10:33:27,011 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:27,011 [model] Got input parameters: {'Omega_m': 0.31072027943400077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:27,011 [classy] Got parameters {'Omega_m': 0.31072027943400077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:27,011 [classy] Computing new state
2023-07-02 10:33:27,011 [classy] Setting parameters: {'Omega_m': 0.31072027943400077, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:27,056 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.47288774333185}
2023-07-02 10:33:27,056 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:27,058 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000393976
2023-07-02 10:33:27,058 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:27,058 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:27,078 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.459
2023-07-02 10:33:27,078 [model] Computed derived parameters: {}
2023-07-02 10:33:27,078 [mcmc] New sample, #68:
Omega_m:0.31546, b1:0.5195237
2023-07-02 10:33:27,078 [model] Posterior to be computed for parameters {'Omega_m': 0.31072027943400077, 'b1': 0.07579848278236362}
2023-07-02 10:33:27,078 [prior] Evaluating prior at array([0.31072028, 0.07579848])
2023-07-02 10:33:27,078 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:27,078 [model] Got input parameters: {'Omega_m': 0.31072027943400077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.07579848278236362, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:27,078 [classy] Got parameters {'Omega_m': 0.31072027943400077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:27,078 [classy] Re-using computed results
2023-07-02 10:33:27,078 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.47288774333185}
2023-07-02 10:33:27,078 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:27,078 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.07579848278236362, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:27,078 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:27,099 [fs_likelihood.fslikelihood] Computed log-likelihood = -314.293
2023-07-02 10:33:27,099 [model] Computed derived parameters: {}
2023-07-02 10:33:27,099 [model] Posterior to be computed for parameters {'Omega_m': 0.3109607727905804, 'b1': 0.5195237182842224}
2023-07-02 10:33:27,099 [prior] Evaluating prior at array([0.31096077, 0.51952372])
2023-07-02 10:33:27,099 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:27,099 [model] Got input parameters: {'Omega_m': 0.3109607727905804, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:27,099 [classy] Got parameters {'Omega_m': 0.3109607727905804, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:27,099 [classy] Computing new state
2023-07-02 10:33:27,099 [classy] Setting parameters: {'Omega_m': 0.3109607727905804, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:27,146 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.44381506408098}
2023-07-02 10:33:27,147 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:27,148 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000345198
2023-07-02 10:33:27,148 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:27,148 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:27,168 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.44326
2023-07-02 10:33:27,168 [model] Computed derived parameters: {}
2023-07-02 10:33:27,168 [mcmc] New sample, #69:
Omega_m:0.3107203, b1:0.5195237
2023-07-02 10:33:27,168 [model] Posterior to be computed for parameters {'Omega_m': 0.3109607727905804, 'b1': 0.7717843124248623}
2023-07-02 10:33:27,168 [prior] Evaluating prior at array([0.31096077, 0.77178431])
2023-07-02 10:33:27,168 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:27,168 [model] Got input parameters: {'Omega_m': 0.3109607727905804, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.7717843124248623, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:27,168 [classy] Got parameters {'Omega_m': 0.3109607727905804, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:27,169 [classy] Re-using computed results
2023-07-02 10:33:27,169 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.44381506408098}
2023-07-02 10:33:27,169 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:27,169 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.7717843124248623, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:27,169 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:27,188 [fs_likelihood.fslikelihood] Computed log-likelihood = -238.549
2023-07-02 10:33:27,188 [model] Computed derived parameters: {}
2023-07-02 10:33:27,189 [model] Posterior to be computed for parameters {'Omega_m': 0.30801945684944393, 'b1': 0.5195237182842224}
2023-07-02 10:33:27,189 [prior] Evaluating prior at array([0.30801946, 0.51952372])
2023-07-02 10:33:27,189 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:27,189 [model] Got input parameters: {'Omega_m': 0.30801945684944393, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:27,189 [classy] Got parameters {'Omega_m': 0.30801945684944393, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:27,189 [classy] Computing new state
2023-07-02 10:33:27,189 [classy] Setting parameters: {'Omega_m': 0.30801945684944393, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:27,233 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.80076778195385}
2023-07-02 10:33:27,233 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:27,235 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00143842
2023-07-02 10:33:27,235 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:27,235 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:27,255 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.5148
2023-07-02 10:33:27,255 [model] Computed derived parameters: {}
2023-07-02 10:33:27,255 [mcmc] New sample, #70:
Omega_m:0.3109608, b1:0.5195237
2023-07-02 10:33:27,255 [model] Posterior to be computed for parameters {'Omega_m': 0.30801945684944393, 'b1': 0.3044095565219965}
2023-07-02 10:33:27,255 [prior] Evaluating prior at array([0.30801946, 0.30440956])
2023-07-02 10:33:27,255 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:27,255 [model] Got input parameters: {'Omega_m': 0.30801945684944393, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.3044095565219965, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:27,255 [classy] Got parameters {'Omega_m': 0.30801945684944393, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:27,255 [classy] Re-using computed results
2023-07-02 10:33:27,255 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.80076778195385}
2023-07-02 10:33:27,255 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:27,255 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.3044095565219965, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:27,255 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:27,275 [fs_likelihood.fslikelihood] Computed log-likelihood = -91.3448
2023-07-02 10:33:27,275 [model] Computed derived parameters: {}
2023-07-02 10:33:27,275 [model] Posterior to be computed for parameters {'Omega_m': 0.3141222451954286, 'b1': 0.5195237182842224}
2023-07-02 10:33:27,275 [prior] Evaluating prior at array([0.31412225, 0.51952372])
2023-07-02 10:33:27,275 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:27,275 [model] Got input parameters: {'Omega_m': 0.3141222451954286, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:27,275 [classy] Got parameters {'Omega_m': 0.3141222451954286, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:27,275 [classy] Computing new state
2023-07-02 10:33:27,275 [classy] Setting parameters: {'Omega_m': 0.3141222451954286, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:27,320 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.06344811477638}
2023-07-02 10:33:27,320 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:27,321 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000366337
2023-07-02 10:33:27,321 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195237182842224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:27,322 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:27,341 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.07279
2023-07-02 10:33:27,342 [model] Computed derived parameters: {}
2023-07-02 10:33:27,342 [mcmc] New sample, #71:
Omega_m:0.3080195, b1:0.5195237
2023-07-02 10:33:27,342 [model] Posterior to be computed for parameters {'Omega_m': 0.3141222451954286, 'b1': 0.510511879507605}
2023-07-02 10:33:27,342 [prior] Evaluating prior at array([0.31412225, 0.51051188])
2023-07-02 10:33:27,342 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:27,342 [model] Got input parameters: {'Omega_m': 0.3141222451954286, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:27,342 [classy] Got parameters {'Omega_m': 0.3141222451954286, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:27,342 [classy] Re-using computed results
2023-07-02 10:33:27,342 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.06344811477638}
2023-07-02 10:33:27,342 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:27,342 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:27,342 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:27,362 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.72072
2023-07-02 10:33:27,362 [model] Computed derived parameters: {}
2023-07-02 10:33:27,362 [mcmc] New sample, #72:
Omega_m:0.3141222, b1:0.5195237
2023-07-02 10:33:27,362 [model] Posterior to be computed for parameters {'Omega_m': 0.3116662689735015, 'b1': 0.510511879507605}
2023-07-02 10:33:27,362 [prior] Evaluating prior at array([0.31166627, 0.51051188])
2023-07-02 10:33:27,362 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:27,362 [model] Got input parameters: {'Omega_m': 0.3116662689735015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:27,362 [classy] Got parameters {'Omega_m': 0.3116662689735015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:27,362 [classy] Computing new state
2023-07-02 10:33:27,362 [classy] Setting parameters: {'Omega_m': 0.3116662689735015, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:27,406 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.35863904393676}
2023-07-02 10:33:27,407 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:27,408 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000243456
2023-07-02 10:33:27,408 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:27,408 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:27,428 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.81022
2023-07-02 10:33:27,428 [model] Computed derived parameters: {}
2023-07-02 10:33:27,428 [mcmc] New sample, #73:
Omega_m:0.3141222, b1:0.5105119
2023-07-02 10:33:27,428 [model] Posterior to be computed for parameters {'Omega_m': 0.3116662689735015, 'b1': 0.5423869192078473}
2023-07-02 10:33:27,428 [prior] Evaluating prior at array([0.31166627, 0.54238692])
2023-07-02 10:33:27,428 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:27,428 [model] Got input parameters: {'Omega_m': 0.3116662689735015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5423869192078473, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:27,428 [classy] Got parameters {'Omega_m': 0.3116662689735015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:27,428 [classy] Re-using computed results
2023-07-02 10:33:27,428 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.35863904393676}
2023-07-02 10:33:27,428 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:27,428 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5423869192078473, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:27,429 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:27,448 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.751192
2023-07-02 10:33:27,449 [model] Computed derived parameters: {}
2023-07-02 10:33:27,449 [model] Posterior to be computed for parameters {'Omega_m': 0.29542114913282985, 'b1': 0.510511879507605}
2023-07-02 10:33:27,449 [prior] Evaluating prior at array([0.29542115, 0.51051188])
2023-07-02 10:33:27,449 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:27,449 [model] Got input parameters: {'Omega_m': 0.29542114913282985, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:27,449 [classy] Got parameters {'Omega_m': 0.29542114913282985, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:27,449 [classy] Computing new state
2023-07-02 10:33:27,449 [classy] Setting parameters: {'Omega_m': 0.29542114913282985, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:27,493 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.36446017207876}
2023-07-02 10:33:27,493 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:27,495 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.018843
2023-07-02 10:33:27,495 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:27,495 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:27,514 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.12068
2023-07-02 10:33:27,514 [model] Computed derived parameters: {}
2023-07-02 10:33:27,515 [model] Posterior to be computed for parameters {'Omega_m': 0.3116662689735015, 'b1': 2.0233898161996606}
2023-07-02 10:33:27,515 [prior] Evaluating prior at array([0.31166627, 2.02338982])
2023-07-02 10:33:27,515 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:27,515 [model] Got input parameters: {'Omega_m': 0.3116662689735015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 2.0233898161996606, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:27,515 [classy] Got parameters {'Omega_m': 0.3116662689735015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:27,515 [classy] Re-using computed results
2023-07-02 10:33:27,515 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.35863904393676}
2023-07-02 10:33:27,515 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:27,515 [fs_likelihood.fslikelihood] Got parameters {'b1': 2.0233898161996606, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:27,515 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:27,535 [fs_likelihood.fslikelihood] Computed log-likelihood = -20522
2023-07-02 10:33:27,535 [model] Computed derived parameters: {}
2023-07-02 10:33:27,535 [model] Posterior to be computed for parameters {'Omega_m': 0.3070391180491007, 'b1': 0.510511879507605}
2023-07-02 10:33:27,535 [prior] Evaluating prior at array([0.30703912, 0.51051188])
2023-07-02 10:33:27,535 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:27,535 [model] Got input parameters: {'Omega_m': 0.3070391180491007, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:27,535 [classy] Got parameters {'Omega_m': 0.3070391180491007, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:27,535 [classy] Computing new state
2023-07-02 10:33:27,535 [classy] Setting parameters: {'Omega_m': 0.3070391180491007, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:27,579 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.92041204173233}
2023-07-02 10:33:27,579 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:27,581 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00204539
2023-07-02 10:33:27,581 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:27,581 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:27,601 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.4909
2023-07-02 10:33:27,602 [model] Computed derived parameters: {}
2023-07-02 10:33:27,602 [mcmc] New sample, #74:
Omega_m:0.3116663, b1:0.5105119
2023-07-02 10:33:27,602 [model] Posterior to be computed for parameters {'Omega_m': 0.3070391180491007, 'b1': 0.8918573916496058}
2023-07-02 10:33:27,602 [prior] Evaluating prior at array([0.30703912, 0.89185739])
2023-07-02 10:33:27,602 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:27,602 [model] Got input parameters: {'Omega_m': 0.3070391180491007, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8918573916496058, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:27,602 [classy] Got parameters {'Omega_m': 0.3070391180491007, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:27,602 [classy] Re-using computed results
2023-07-02 10:33:27,602 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.92041204173233}
2023-07-02 10:33:27,602 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:27,602 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8918573916496058, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:27,602 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:27,622 [fs_likelihood.fslikelihood] Computed log-likelihood = -539.521
2023-07-02 10:33:27,622 [model] Computed derived parameters: {}
2023-07-02 10:33:27,622 [model] Posterior to be computed for parameters {'Omega_m': 0.31096422110619903, 'b1': 0.510511879507605}
2023-07-02 10:33:27,622 [prior] Evaluating prior at array([0.31096422, 0.51051188])
2023-07-02 10:33:27,622 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:27,622 [model] Got input parameters: {'Omega_m': 0.31096422110619903, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:27,622 [classy] Got parameters {'Omega_m': 0.31096422110619903, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:27,622 [classy] Computing new state
2023-07-02 10:33:27,622 [classy] Setting parameters: {'Omega_m': 0.31096422110619903, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:27,666 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.44339732401312}
2023-07-02 10:33:27,666 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:27,668 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000344551
2023-07-02 10:33:27,668 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:27,668 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:27,687 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.8028
2023-07-02 10:33:27,687 [model] Computed derived parameters: {}
2023-07-02 10:33:27,687 [mcmc] New sample, #75:
Omega_m:0.3070391, b1:0.5105119
2023-07-02 10:33:27,688 [model] Posterior to be computed for parameters {'Omega_m': 0.31096422110619903, 'b1': 0.09098674359463482}
2023-07-02 10:33:27,688 [prior] Evaluating prior at array([0.31096422, 0.09098674])
2023-07-02 10:33:27,688 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:27,688 [model] Got input parameters: {'Omega_m': 0.31096422110619903, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.09098674359463482, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:27,688 [classy] Got parameters {'Omega_m': 0.31096422110619903, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:27,688 [classy] Re-using computed results
2023-07-02 10:33:27,688 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.44339732401312}
2023-07-02 10:33:27,688 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:27,688 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.09098674359463482, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:27,688 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:27,708 [fs_likelihood.fslikelihood] Computed log-likelihood = -296.982
2023-07-02 10:33:27,708 [model] Computed derived parameters: {}
2023-07-02 10:33:27,708 [model] Posterior to be computed for parameters {'Omega_m': 0.3213311636378495, 'b1': 0.510511879507605}
2023-07-02 10:33:27,708 [prior] Evaluating prior at array([0.32133116, 0.51051188])
2023-07-02 10:33:27,708 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:27,708 [model] Got input parameters: {'Omega_m': 0.3213311636378495, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:27,708 [classy] Got parameters {'Omega_m': 0.3213311636378495, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:27,708 [classy] Computing new state
2023-07-02 10:33:27,709 [classy] Setting parameters: {'Omega_m': 0.3213311636378495, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:27,752 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.20877374326957}
2023-07-02 10:33:27,752 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:27,754 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00489807
2023-07-02 10:33:27,754 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:27,754 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:27,773 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.42075
2023-07-02 10:33:27,774 [model] Computed derived parameters: {}
2023-07-02 10:33:27,774 [model] Posterior to be computed for parameters {'Omega_m': 0.31096422110619903, 'b1': -0.073027341525574}
2023-07-02 10:33:27,774 [prior] Evaluating prior at array([ 0.31096422, -0.07302734])
2023-07-02 10:33:27,774 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:27,774 [model] Posterior to be computed for parameters {'Omega_m': 0.28965314656470253, 'b1': 0.510511879507605}
2023-07-02 10:33:27,774 [prior] Evaluating prior at array([0.28965315, 0.51051188])
2023-07-02 10:33:27,774 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:27,774 [model] Got input parameters: {'Omega_m': 0.28965314656470253, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:27,774 [classy] Got parameters {'Omega_m': 0.28965314656470253, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:27,774 [classy] Computing new state
2023-07-02 10:33:27,774 [classy] Setting parameters: {'Omega_m': 0.28965314656470253, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:27,818 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.09991312850602}
2023-07-02 10:33:27,818 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:27,819 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0340774
2023-07-02 10:33:27,820 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:27,820 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:27,839 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.40669
2023-07-02 10:33:27,839 [model] Computed derived parameters: {}
2023-07-02 10:33:27,839 [model] Posterior to be computed for parameters {'Omega_m': 0.31096422110619903, 'b1': 1.3245926363231155}
2023-07-02 10:33:27,839 [prior] Evaluating prior at array([0.31096422, 1.32459264])
2023-07-02 10:33:27,839 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:27,840 [model] Got input parameters: {'Omega_m': 0.31096422110619903, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.3245926363231155, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:27,840 [classy] Got parameters {'Omega_m': 0.31096422110619903, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:27,840 [classy] Re-using computed results
2023-07-02 10:33:27,840 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.44339732401312}
2023-07-02 10:33:27,840 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:27,840 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.3245926363231155, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:27,840 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:27,860 [fs_likelihood.fslikelihood] Computed log-likelihood = -3669.83
2023-07-02 10:33:27,860 [model] Computed derived parameters: {}
2023-07-02 10:33:27,860 [model] Posterior to be computed for parameters {'Omega_m': 0.3189529864464342, 'b1': 0.510511879507605}
2023-07-02 10:33:27,860 [prior] Evaluating prior at array([0.31895299, 0.51051188])
2023-07-02 10:33:27,860 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:27,860 [model] Got input parameters: {'Omega_m': 0.3189529864464342, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:27,860 [classy] Got parameters {'Omega_m': 0.3189529864464342, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:27,860 [classy] Computing new state
2023-07-02 10:33:27,860 [classy] Setting parameters: {'Omega_m': 0.3189529864464342, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:27,904 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.48882050480427}
2023-07-02 10:33:27,904 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:27,906 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00272759
2023-07-02 10:33:27,906 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:27,906 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:27,925 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.02063
2023-07-02 10:33:27,925 [model] Computed derived parameters: {}
2023-07-02 10:33:27,925 [mcmc] New sample, #76:
Omega_m:0.3109642, b1:0.5105119
2023-07-02 10:33:27,926 [model] Posterior to be computed for parameters {'Omega_m': 0.3189529864464342, 'b1': 1.5609618453469905}
2023-07-02 10:33:27,926 [prior] Evaluating prior at array([0.31895299, 1.56096185])
2023-07-02 10:33:27,926 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:27,926 [model] Got input parameters: {'Omega_m': 0.3189529864464342, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.5609618453469905, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:27,926 [classy] Got parameters {'Omega_m': 0.3189529864464342, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:27,926 [classy] Re-using computed results
2023-07-02 10:33:27,926 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.48882050480427}
2023-07-02 10:33:27,926 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:27,926 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.5609618453469905, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:27,926 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:27,945 [fs_likelihood.fslikelihood] Computed log-likelihood = -7645.23
2023-07-02 10:33:27,945 [model] Computed derived parameters: {}
2023-07-02 10:33:27,946 [model] Posterior to be computed for parameters {'Omega_m': 0.3118621656882154, 'b1': 0.510511879507605}
2023-07-02 10:33:27,946 [prior] Evaluating prior at array([0.31186217, 0.51051188])
2023-07-02 10:33:27,946 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:27,946 [model] Got input parameters: {'Omega_m': 0.3118621656882154, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:27,946 [classy] Got parameters {'Omega_m': 0.3118621656882154, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:27,946 [classy] Computing new state
2023-07-02 10:33:27,946 [classy] Setting parameters: {'Omega_m': 0.3118621656882154, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:27,990 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.33501645858092}
2023-07-02 10:33:27,990 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:27,991 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000226117
2023-07-02 10:33:27,991 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:27,991 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:28,012 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.80967
2023-07-02 10:33:28,012 [model] Computed derived parameters: {}
2023-07-02 10:33:28,012 [mcmc] New sample, #77:
Omega_m:0.318953, b1:0.5105119
2023-07-02 10:33:28,012 [model] Posterior to be computed for parameters {'Omega_m': 0.3118621656882154, 'b1': -1.2001337573775275}
2023-07-02 10:33:28,012 [prior] Evaluating prior at array([ 0.31186217, -1.20013376])
2023-07-02 10:33:28,012 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:28,012 [model] Posterior to be computed for parameters {'Omega_m': 0.2933876432486707, 'b1': 0.510511879507605}
2023-07-02 10:33:28,012 [prior] Evaluating prior at array([0.29338764, 0.51051188])
2023-07-02 10:33:28,012 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:28,012 [model] Got input parameters: {'Omega_m': 0.2933876432486707, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:28,013 [classy] Got parameters {'Omega_m': 0.2933876432486707, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:28,013 [classy] Computing new state
2023-07-02 10:33:28,013 [classy] Setting parameters: {'Omega_m': 0.2933876432486707, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:28,056 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.6223130855612}
2023-07-02 10:33:28,056 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:28,058 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0236737
2023-07-02 10:33:28,058 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:28,058 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:28,078 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.1661
2023-07-02 10:33:28,078 [model] Computed derived parameters: {}
2023-07-02 10:33:28,078 [model] Posterior to be computed for parameters {'Omega_m': 0.3118621656882154, 'b1': 0.23307091655401746}
2023-07-02 10:33:28,078 [prior] Evaluating prior at array([0.31186217, 0.23307092])
2023-07-02 10:33:28,078 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:28,078 [model] Got input parameters: {'Omega_m': 0.3118621656882154, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.23307091655401746, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:28,078 [classy] Got parameters {'Omega_m': 0.3118621656882154, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:28,078 [classy] Re-using computed results
2023-07-02 10:33:28,078 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.33501645858092}
2023-07-02 10:33:28,078 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:28,078 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.23307091655401746, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:28,078 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:28,098 [fs_likelihood.fslikelihood] Computed log-likelihood = -147.841
2023-07-02 10:33:28,098 [model] Computed derived parameters: {}
2023-07-02 10:33:28,098 [model] Posterior to be computed for parameters {'Omega_m': 0.29471412471260805, 'b1': 0.510511879507605}
2023-07-02 10:33:28,099 [prior] Evaluating prior at array([0.29471412, 0.51051188])
2023-07-02 10:33:28,099 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:28,099 [model] Got input parameters: {'Omega_m': 0.29471412471260805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:28,099 [classy] Got parameters {'Omega_m': 0.29471412471260805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:28,099 [classy] Computing new state
2023-07-02 10:33:28,099 [classy] Setting parameters: {'Omega_m': 0.29471412471260805, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:28,144 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.45393759543168}
2023-07-02 10:33:28,144 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:28,146 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0204568
2023-07-02 10:33:28,146 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:28,146 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:28,166 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.4702
2023-07-02 10:33:28,166 [model] Computed derived parameters: {}
2023-07-02 10:33:28,167 [model] Posterior to be computed for parameters {'Omega_m': 0.3118621656882154, 'b1': 0.15900443294048716}
2023-07-02 10:33:28,167 [prior] Evaluating prior at array([0.31186217, 0.15900443])
2023-07-02 10:33:28,167 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:28,167 [model] Got input parameters: {'Omega_m': 0.3118621656882154, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.15900443294048716, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:28,167 [classy] Got parameters {'Omega_m': 0.3118621656882154, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:28,167 [classy] Re-using computed results
2023-07-02 10:33:28,167 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.33501645858092}
2023-07-02 10:33:28,167 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:28,167 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.15900443294048716, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:28,167 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:28,187 [fs_likelihood.fslikelihood] Computed log-likelihood = -221.865
2023-07-02 10:33:28,187 [model] Computed derived parameters: {}
2023-07-02 10:33:28,187 [model] Posterior to be computed for parameters {'Omega_m': 0.3040747775646616, 'b1': 0.510511879507605}
2023-07-02 10:33:28,187 [prior] Evaluating prior at array([0.30407478, 0.51051188])
2023-07-02 10:33:28,187 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:28,187 [model] Got input parameters: {'Omega_m': 0.3040747775646616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:28,187 [classy] Got parameters {'Omega_m': 0.3040747775646616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:28,187 [classy] Computing new state
2023-07-02 10:33:28,187 [classy] Setting parameters: {'Omega_m': 0.3040747775646616, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:28,231 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.28423482709456}
2023-07-02 10:33:28,231 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:28,233 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00463118
2023-07-02 10:33:28,233 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:28,233 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:28,253 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.9513
2023-07-02 10:33:28,253 [model] Computed derived parameters: {}
2023-07-02 10:33:28,253 [model] Posterior to be computed for parameters {'Omega_m': 0.3118621656882154, 'b1': 0.6148850997181499}
2023-07-02 10:33:28,253 [prior] Evaluating prior at array([0.31186217, 0.6148851 ])
2023-07-02 10:33:28,253 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:28,253 [model] Got input parameters: {'Omega_m': 0.3118621656882154, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6148850997181499, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:28,254 [classy] Got parameters {'Omega_m': 0.3118621656882154, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:28,254 [classy] Re-using computed results
2023-07-02 10:33:28,254 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.33501645858092}
2023-07-02 10:33:28,254 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:28,254 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6148850997181499, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:28,254 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:28,274 [fs_likelihood.fslikelihood] Computed log-likelihood = -32.5798
2023-07-02 10:33:28,274 [model] Computed derived parameters: {}
2023-07-02 10:33:28,274 [model] Posterior to be computed for parameters {'Omega_m': 0.3100697665230034, 'b1': 0.510511879507605}
2023-07-02 10:33:28,274 [prior] Evaluating prior at array([0.31006977, 0.51051188])
2023-07-02 10:33:28,274 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:28,274 [model] Got input parameters: {'Omega_m': 0.3100697665230034, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:28,274 [classy] Got parameters {'Omega_m': 0.3100697665230034, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:28,274 [classy] Computing new state
2023-07-02 10:33:28,274 [classy] Setting parameters: {'Omega_m': 0.3100697665230034, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:28,318 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.55162911848896}
2023-07-02 10:33:28,318 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:28,320 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000561967
2023-07-02 10:33:28,320 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:28,320 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:28,340 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.77208
2023-07-02 10:33:28,340 [model] Computed derived parameters: {}
2023-07-02 10:33:28,340 [mcmc] New sample, #78:
Omega_m:0.3118622, b1:0.5105119
2023-07-02 10:33:28,340 [model] Posterior to be computed for parameters {'Omega_m': 0.3100697665230034, 'b1': 1.107578690141842}
2023-07-02 10:33:28,340 [prior] Evaluating prior at array([0.31006977, 1.10757869])
2023-07-02 10:33:28,340 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:28,340 [model] Got input parameters: {'Omega_m': 0.3100697665230034, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.107578690141842, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:28,340 [classy] Got parameters {'Omega_m': 0.3100697665230034, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:28,340 [classy] Re-using computed results
2023-07-02 10:33:28,340 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.55162911848896}
2023-07-02 10:33:28,341 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:28,341 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.107578690141842, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:28,341 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:28,361 [fs_likelihood.fslikelihood] Computed log-likelihood = -1651.46
2023-07-02 10:33:28,361 [model] Computed derived parameters: {}
2023-07-02 10:33:28,361 [model] Posterior to be computed for parameters {'Omega_m': 0.3170673338430472, 'b1': 0.510511879507605}
2023-07-02 10:33:28,361 [prior] Evaluating prior at array([0.31706733, 0.51051188])
2023-07-02 10:33:28,361 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:28,361 [model] Got input parameters: {'Omega_m': 0.3170673338430472, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:28,361 [classy] Got parameters {'Omega_m': 0.3170673338430472, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:28,361 [classy] Computing new state
2023-07-02 10:33:28,361 [classy] Setting parameters: {'Omega_m': 0.3170673338430472, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:28,407 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.7121932359088}
2023-07-02 10:33:28,408 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:28,409 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00147596
2023-07-02 10:33:28,410 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:28,410 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:28,430 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.37659
2023-07-02 10:33:28,430 [model] Computed derived parameters: {}
2023-07-02 10:33:28,430 [mcmc] New sample, #79:
Omega_m:0.3100698, b1:0.5105119
2023-07-02 10:33:28,430 [model] Posterior to be computed for parameters {'Omega_m': 0.3170673338430472, 'b1': 1.1871695168601222}
2023-07-02 10:33:28,430 [prior] Evaluating prior at array([0.31706733, 1.18716952])
2023-07-02 10:33:28,430 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:28,431 [model] Got input parameters: {'Omega_m': 0.3170673338430472, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.1871695168601222, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:28,431 [classy] Got parameters {'Omega_m': 0.3170673338430472, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:28,431 [classy] Re-using computed results
2023-07-02 10:33:28,431 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.7121932359088}
2023-07-02 10:33:28,431 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:28,431 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.1871695168601222, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:28,431 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:28,450 [fs_likelihood.fslikelihood] Computed log-likelihood = -2396.06
2023-07-02 10:33:28,450 [model] Computed derived parameters: {}
2023-07-02 10:33:28,450 [model] Posterior to be computed for parameters {'Omega_m': 0.31293505739663435, 'b1': 0.510511879507605}
2023-07-02 10:33:28,450 [prior] Evaluating prior at array([0.31293506, 0.51051188])
2023-07-02 10:33:28,451 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:28,451 [model] Got input parameters: {'Omega_m': 0.31293505739663435, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:28,451 [classy] Got parameters {'Omega_m': 0.31293505739663435, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:28,451 [classy] Computing new state
2023-07-02 10:33:28,451 [classy] Setting parameters: {'Omega_m': 0.31293505739663435, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:28,494 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.20588163404494}
2023-07-02 10:33:28,494 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:28,496 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000214845
2023-07-02 10:33:28,496 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:28,496 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:28,517 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.78641
2023-07-02 10:33:28,517 [model] Computed derived parameters: {}
2023-07-02 10:33:28,517 [mcmc] New sample, #80:
Omega_m:0.3170673, b1:0.5105119
2023-07-02 10:33:28,517 [mcmc] Learn + convergence test @ 80 samples accepted.
2023-07-02 10:33:28,517 [mcmc] Ready to check convergence and learn a new proposal covmat
2023-07-02 10:33:28,522 [mcmc] - Acceptance rate: 0.263
2023-07-02 10:33:28,523 [mcmc] - Condition number = 5172.46
2023-07-02 10:33:28,523 [mcmc] - Eigenvalues = array([7.78223671e-03, 4.02532716e+01])
2023-07-02 10:33:28,523 [mcmc] - Convergence of means: R-1 = 40.253272 after 64 accepted steps
2023-07-02 10:33:28,523 [mcmc] Convergence less than requested for updates: waiting until the next convergence check.
2023-07-02 10:33:28,523 [model] Posterior to be computed for parameters {'Omega_m': 0.31293505739663435, 'b1': 1.3699776482394408}
2023-07-02 10:33:28,523 [prior] Evaluating prior at array([0.31293506, 1.36997765])
2023-07-02 10:33:28,523 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:28,523 [model] Got input parameters: {'Omega_m': 0.31293505739663435, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.3699776482394408, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:28,523 [classy] Got parameters {'Omega_m': 0.31293505739663435, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:28,523 [classy] Re-using computed results
2023-07-02 10:33:28,523 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.20588163404494}
2023-07-02 10:33:28,523 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:28,523 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.3699776482394408, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:28,523 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:28,544 [fs_likelihood.fslikelihood] Computed log-likelihood = -4292.78
2023-07-02 10:33:28,544 [model] Computed derived parameters: {}
2023-07-02 10:33:28,544 [model] Posterior to be computed for parameters {'Omega_m': 0.30322111404638574, 'b1': 0.510511879507605}
2023-07-02 10:33:28,544 [prior] Evaluating prior at array([0.30322111, 0.51051188])
2023-07-02 10:33:28,544 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:28,544 [model] Got input parameters: {'Omega_m': 0.30322111404638574, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:28,544 [classy] Got parameters {'Omega_m': 0.30322111404638574, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:28,544 [classy] Computing new state
2023-07-02 10:33:28,544 [classy] Setting parameters: {'Omega_m': 0.30322111404638574, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:28,589 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.38958432026266}
2023-07-02 10:33:28,589 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:28,591 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00558753
2023-07-02 10:33:28,591 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:28,591 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:28,611 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.74739
2023-07-02 10:33:28,611 [model] Computed derived parameters: {}
2023-07-02 10:33:28,612 [model] Posterior to be computed for parameters {'Omega_m': 0.31293505739663435, 'b1': 1.6986006887478249}
2023-07-02 10:33:28,612 [prior] Evaluating prior at array([0.31293506, 1.69860069])
2023-07-02 10:33:28,612 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:28,612 [model] Got input parameters: {'Omega_m': 0.31293505739663435, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.6986006887478249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:28,612 [classy] Got parameters {'Omega_m': 0.31293505739663435, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:28,612 [classy] Re-using computed results
2023-07-02 10:33:28,612 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.20588163404494}
2023-07-02 10:33:28,612 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:28,612 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.6986006887478249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:28,612 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:28,632 [fs_likelihood.fslikelihood] Computed log-likelihood = -10343.2
2023-07-02 10:33:28,632 [model] Computed derived parameters: {}
2023-07-02 10:33:28,632 [model] Posterior to be computed for parameters {'Omega_m': 0.31979737595941976, 'b1': 0.510511879507605}
2023-07-02 10:33:28,632 [prior] Evaluating prior at array([0.31979738, 0.51051188])
2023-07-02 10:33:28,632 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:28,632 [model] Got input parameters: {'Omega_m': 0.31979737595941976, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:28,632 [classy] Got parameters {'Omega_m': 0.31979737595941976, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:28,632 [classy] Computing new state
2023-07-02 10:33:28,632 [classy] Setting parameters: {'Omega_m': 0.31979737595941976, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:28,676 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.38917564309028}
2023-07-02 10:33:28,676 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:28,678 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00342313
2023-07-02 10:33:28,678 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:28,678 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:28,697 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.82692
2023-07-02 10:33:28,697 [model] Computed derived parameters: {}
2023-07-02 10:33:28,697 [model] Posterior to be computed for parameters {'Omega_m': 0.31293505739663435, 'b1': 0.6866664092026913}
2023-07-02 10:33:28,698 [prior] Evaluating prior at array([0.31293506, 0.68666641])
2023-07-02 10:33:28,698 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:28,698 [model] Got input parameters: {'Omega_m': 0.31293505739663435, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6866664092026913, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:28,698 [classy] Got parameters {'Omega_m': 0.31293505739663435, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:28,698 [classy] Re-using computed results
2023-07-02 10:33:28,698 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.20588163404494}
2023-07-02 10:33:28,698 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:28,698 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6866664092026913, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:28,698 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:28,719 [fs_likelihood.fslikelihood] Computed log-likelihood = -104.242
2023-07-02 10:33:28,719 [model] Computed derived parameters: {}
2023-07-02 10:33:28,719 [model] Posterior to be computed for parameters {'Omega_m': 0.3027454002839479, 'b1': 0.510511879507605}
2023-07-02 10:33:28,719 [prior] Evaluating prior at array([0.3027454 , 0.51051188])
2023-07-02 10:33:28,719 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:28,719 [model] Got input parameters: {'Omega_m': 0.3027454002839479, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:28,719 [classy] Got parameters {'Omega_m': 0.3027454002839479, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:28,719 [classy] Computing new state
2023-07-02 10:33:28,719 [classy] Setting parameters: {'Omega_m': 0.3027454002839479, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:28,763 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.44840353356787}
2023-07-02 10:33:28,764 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:28,765 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00616197
2023-07-02 10:33:28,765 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:28,765 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:28,785 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.62434
2023-07-02 10:33:28,785 [model] Computed derived parameters: {}
2023-07-02 10:33:28,785 [model] Posterior to be computed for parameters {'Omega_m': 0.31293505739663435, 'b1': 0.6899836820973305}
2023-07-02 10:33:28,785 [prior] Evaluating prior at array([0.31293506, 0.68998368])
2023-07-02 10:33:28,785 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:28,785 [model] Got input parameters: {'Omega_m': 0.31293505739663435, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6899836820973305, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:28,785 [classy] Got parameters {'Omega_m': 0.31293505739663435, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:28,785 [classy] Re-using computed results
2023-07-02 10:33:28,785 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.20588163404494}
2023-07-02 10:33:28,785 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:28,785 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6899836820973305, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:28,785 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:28,805 [fs_likelihood.fslikelihood] Computed log-likelihood = -108.519
2023-07-02 10:33:28,805 [model] Computed derived parameters: {}
2023-07-02 10:33:28,805 [model] Posterior to be computed for parameters {'Omega_m': 0.32287791562147955, 'b1': 0.510511879507605}
2023-07-02 10:33:28,805 [prior] Evaluating prior at array([0.32287792, 0.51051188])
2023-07-02 10:33:28,805 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:28,805 [model] Got input parameters: {'Omega_m': 0.32287791562147955, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:28,805 [classy] Got parameters {'Omega_m': 0.32287791562147955, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:28,805 [classy] Computing new state
2023-07-02 10:33:28,805 [classy] Setting parameters: {'Omega_m': 0.32287791562147955, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:28,849 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.02762402388845}
2023-07-02 10:33:28,849 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:28,851 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00665912
2023-07-02 10:33:28,851 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:28,851 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:28,871 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.940201
2023-07-02 10:33:28,871 [model] Computed derived parameters: {}
2023-07-02 10:33:28,871 [model] Posterior to be computed for parameters {'Omega_m': 0.31293505739663435, 'b1': 1.377510723496425}
2023-07-02 10:33:28,872 [prior] Evaluating prior at array([0.31293506, 1.37751072])
2023-07-02 10:33:28,872 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:28,872 [model] Got input parameters: {'Omega_m': 0.31293505739663435, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.377510723496425, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:28,872 [classy] Got parameters {'Omega_m': 0.31293505739663435, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:28,872 [classy] Re-using computed results
2023-07-02 10:33:28,872 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.20588163404494}
2023-07-02 10:33:28,872 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:28,872 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.377510723496425, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:28,872 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:28,891 [fs_likelihood.fslikelihood] Computed log-likelihood = -4392.73
2023-07-02 10:33:28,891 [model] Computed derived parameters: {}
2023-07-02 10:33:28,891 [model] Posterior to be computed for parameters {'Omega_m': 0.31540071922536833, 'b1': 0.510511879507605}
2023-07-02 10:33:28,891 [prior] Evaluating prior at array([0.31540072, 0.51051188])
2023-07-02 10:33:28,892 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:28,892 [model] Got input parameters: {'Omega_m': 0.31540071922536833, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:28,892 [classy] Got parameters {'Omega_m': 0.31540071922536833, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:28,892 [classy] Computing new state
2023-07-02 10:33:28,892 [classy] Setting parameters: {'Omega_m': 0.31540071922536833, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:28,936 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.91059953499882}
2023-07-02 10:33:28,936 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:28,937 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000720398
2023-07-02 10:33:28,937 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:28,937 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:28,957 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.60305
2023-07-02 10:33:28,957 [model] Computed derived parameters: {}
2023-07-02 10:33:28,957 [mcmc] New sample, #81:
Omega_m:0.3129351, b1:0.5105119
2023-07-02 10:33:28,957 [model] Posterior to be computed for parameters {'Omega_m': 0.31540071922536833, 'b1': -0.5041712964231465}
2023-07-02 10:33:28,957 [prior] Evaluating prior at array([ 0.31540072, -0.5041713 ])
2023-07-02 10:33:28,957 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:28,957 [model] Posterior to be computed for parameters {'Omega_m': 0.3132009262188758, 'b1': 0.510511879507605}
2023-07-02 10:33:28,957 [prior] Evaluating prior at array([0.31320093, 0.51051188])
2023-07-02 10:33:28,958 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:28,958 [model] Got input parameters: {'Omega_m': 0.3132009262188758, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:28,958 [classy] Got parameters {'Omega_m': 0.3132009262188758, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:28,958 [classy] Computing new state
2023-07-02 10:33:28,958 [classy] Setting parameters: {'Omega_m': 0.3132009262188758, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:29,002 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.17394355394978}
2023-07-02 10:33:29,002 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:29,003 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000233847
2023-07-02 10:33:29,003 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:29,003 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:29,024 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.77534
2023-07-02 10:33:29,024 [model] Computed derived parameters: {}
2023-07-02 10:33:29,024 [mcmc] New sample, #82:
Omega_m:0.3154007, b1:0.5105119
2023-07-02 10:33:29,024 [model] Posterior to be computed for parameters {'Omega_m': 0.3132009262188758, 'b1': 1.3084035322932421}
2023-07-02 10:33:29,024 [prior] Evaluating prior at array([0.31320093, 1.30840353])
2023-07-02 10:33:29,024 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:29,024 [model] Got input parameters: {'Omega_m': 0.3132009262188758, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.3084035322932421, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:29,024 [classy] Got parameters {'Omega_m': 0.3132009262188758, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:29,024 [classy] Re-using computed results
2023-07-02 10:33:29,024 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.17394355394978}
2023-07-02 10:33:29,024 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:29,024 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.3084035322932421, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:29,024 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:29,044 [fs_likelihood.fslikelihood] Computed log-likelihood = -3540.7
2023-07-02 10:33:29,044 [model] Computed derived parameters: {}
2023-07-02 10:33:29,044 [model] Posterior to be computed for parameters {'Omega_m': 0.29814529229457815, 'b1': 0.510511879507605}
2023-07-02 10:33:29,044 [prior] Evaluating prior at array([0.29814529, 0.51051188])
2023-07-02 10:33:29,044 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:29,044 [model] Got input parameters: {'Omega_m': 0.29814529229457815, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:29,044 [classy] Got parameters {'Omega_m': 0.29814529229457815, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:29,044 [classy] Computing new state
2023-07-02 10:33:29,044 [classy] Setting parameters: {'Omega_m': 0.29814529229457815, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:29,088 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.0214418274543}
2023-07-02 10:33:29,088 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:29,090 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0132741
2023-07-02 10:33:29,090 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:29,090 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:29,111 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.0868517
2023-07-02 10:33:29,111 [model] Computed derived parameters: {}
2023-07-02 10:33:29,111 [model] Posterior to be computed for parameters {'Omega_m': 0.3132009262188758, 'b1': -0.0817462090169998}
2023-07-02 10:33:29,111 [prior] Evaluating prior at array([ 0.31320093, -0.08174621])
2023-07-02 10:33:29,111 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:29,111 [model] Posterior to be computed for parameters {'Omega_m': 0.30867714026610565, 'b1': 0.510511879507605}
2023-07-02 10:33:29,111 [prior] Evaluating prior at array([0.30867714, 0.51051188])
2023-07-02 10:33:29,111 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:29,111 [model] Got input parameters: {'Omega_m': 0.30867714026610565, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:29,112 [classy] Got parameters {'Omega_m': 0.30867714026610565, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:29,112 [classy] Computing new state
2023-07-02 10:33:29,112 [classy] Setting parameters: {'Omega_m': 0.30867714026610565, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:29,157 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.72069560690463}
2023-07-02 10:33:29,157 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:29,158 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00109962
2023-07-02 10:33:29,158 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:29,158 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:29,178 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.67683
2023-07-02 10:33:29,179 [model] Computed derived parameters: {}
2023-07-02 10:33:29,179 [mcmc] New sample, #83:
Omega_m:0.3132009, b1:0.5105119
2023-07-02 10:33:29,179 [model] Posterior to be computed for parameters {'Omega_m': 0.30867714026610565, 'b1': -0.9958898332894498}
2023-07-02 10:33:29,179 [prior] Evaluating prior at array([ 0.30867714, -0.99588983])
2023-07-02 10:33:29,179 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:29,179 [model] Posterior to be computed for parameters {'Omega_m': 0.29791442119222267, 'b1': 0.510511879507605}
2023-07-02 10:33:29,179 [prior] Evaluating prior at array([0.29791442, 0.51051188])
2023-07-02 10:33:29,179 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:29,179 [model] Got input parameters: {'Omega_m': 0.29791442119222267, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:29,179 [classy] Got parameters {'Omega_m': 0.29791442119222267, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:29,179 [classy] Computing new state
2023-07-02 10:33:29,179 [classy] Setting parameters: {'Omega_m': 0.29791442119222267, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:29,223 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.05040754777798}
2023-07-02 10:33:29,223 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:29,225 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0137065
2023-07-02 10:33:29,225 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:29,225 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:29,245 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.00691669
2023-07-02 10:33:29,245 [model] Computed derived parameters: {}
2023-07-02 10:33:29,245 [model] Posterior to be computed for parameters {'Omega_m': 0.30867714026610565, 'b1': 0.027527553050551823}
2023-07-02 10:33:29,245 [prior] Evaluating prior at array([0.30867714, 0.02752755])
2023-07-02 10:33:29,245 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:29,245 [model] Got input parameters: {'Omega_m': 0.30867714026610565, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.027527553050551823, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:29,245 [classy] Got parameters {'Omega_m': 0.30867714026610565, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:29,245 [classy] Re-using computed results
2023-07-02 10:33:29,245 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.72069560690463}
2023-07-02 10:33:29,245 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:29,245 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.027527553050551823, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:29,245 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:29,265 [fs_likelihood.fslikelihood] Computed log-likelihood = -372.168
2023-07-02 10:33:29,265 [model] Computed derived parameters: {}
2023-07-02 10:33:29,265 [model] Posterior to be computed for parameters {'Omega_m': 0.28025403658981685, 'b1': 0.510511879507605}
2023-07-02 10:33:29,265 [prior] Evaluating prior at array([0.28025404, 0.51051188])
2023-07-02 10:33:29,265 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:29,265 [model] Got input parameters: {'Omega_m': 0.28025403658981685, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:29,265 [classy] Got parameters {'Omega_m': 0.28025403658981685, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:29,265 [classy] Computing new state
2023-07-02 10:33:29,265 [classy] Setting parameters: {'Omega_m': 0.28025403658981685, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:29,309 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.3259796827307}
2023-07-02 10:33:29,310 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:29,311 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0693989
2023-07-02 10:33:29,311 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:29,311 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:29,331 [fs_likelihood.fslikelihood] Computed log-likelihood = -11.8837
2023-07-02 10:33:29,331 [model] Computed derived parameters: {}
2023-07-02 10:33:29,331 [model] Posterior to be computed for parameters {'Omega_m': 0.30867714026610565, 'b1': -0.5741004210734669}
2023-07-02 10:33:29,331 [prior] Evaluating prior at array([ 0.30867714, -0.57410042])
2023-07-02 10:33:29,332 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:29,332 [model] Posterior to be computed for parameters {'Omega_m': 0.2948895775575782, 'b1': 0.510511879507605}
2023-07-02 10:33:29,332 [prior] Evaluating prior at array([0.29488958, 0.51051188])
2023-07-02 10:33:29,332 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:29,332 [model] Got input parameters: {'Omega_m': 0.2948895775575782, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:29,332 [classy] Got parameters {'Omega_m': 0.2948895775575782, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:29,332 [classy] Computing new state
2023-07-02 10:33:29,332 [classy] Setting parameters: {'Omega_m': 0.2948895775575782, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:29,376 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.4317179768111}
2023-07-02 10:33:29,376 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:29,377 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0200499
2023-07-02 10:33:29,377 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:29,378 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:29,397 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.38207
2023-07-02 10:33:29,397 [model] Computed derived parameters: {}
2023-07-02 10:33:29,397 [model] Posterior to be computed for parameters {'Omega_m': 0.30867714026610565, 'b1': -2.6635045533376887}
2023-07-02 10:33:29,397 [prior] Evaluating prior at array([ 0.30867714, -2.66350455])
2023-07-02 10:33:29,397 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:29,397 [model] Posterior to be computed for parameters {'Omega_m': 0.2594474917032065, 'b1': 0.510511879507605}
2023-07-02 10:33:29,397 [prior] Evaluating prior at array([0.25944749, 0.51051188])
2023-07-02 10:33:29,397 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:29,397 [model] Got input parameters: {'Omega_m': 0.2594474917032065, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:29,398 [classy] Got parameters {'Omega_m': 0.2594474917032065, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:29,398 [classy] Computing new state
2023-07-02 10:33:29,398 [classy] Setting parameters: {'Omega_m': 0.2594474917032065, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:29,442 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 154.1700608232798}
2023-07-02 10:33:29,442 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:29,443 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.198455
2023-07-02 10:33:29,443 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:29,444 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:29,463 [fs_likelihood.fslikelihood] Computed log-likelihood = -37.7918
2023-07-02 10:33:29,463 [model] Computed derived parameters: {}
2023-07-02 10:33:29,463 [model] Posterior to be computed for parameters {'Omega_m': 0.30867714026610565, 'b1': 1.441465329770376}
2023-07-02 10:33:29,463 [prior] Evaluating prior at array([0.30867714, 1.44146533])
2023-07-02 10:33:29,463 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:29,463 [model] Got input parameters: {'Omega_m': 0.30867714026610565, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.441465329770376, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:29,463 [classy] Got parameters {'Omega_m': 0.30867714026610565, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:29,463 [classy] Computing new state
2023-07-02 10:33:29,463 [classy] Setting parameters: {'Omega_m': 0.30867714026610565, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:29,508 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.72069560690463}
2023-07-02 10:33:29,508 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:29,510 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00109962
2023-07-02 10:33:29,510 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.441465329770376, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:29,510 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:29,531 [fs_likelihood.fslikelihood] Computed log-likelihood = -5154.35
2023-07-02 10:33:29,531 [model] Computed derived parameters: {}
2023-07-02 10:33:29,531 [model] Posterior to be computed for parameters {'Omega_m': 0.29310762835174614, 'b1': 0.510511879507605}
2023-07-02 10:33:29,531 [prior] Evaluating prior at array([0.29310763, 0.51051188])
2023-07-02 10:33:29,531 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:29,531 [model] Got input parameters: {'Omega_m': 0.29310762835174614, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:29,531 [classy] Got parameters {'Omega_m': 0.29310762835174614, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:29,531 [classy] Computing new state
2023-07-02 10:33:29,531 [classy] Setting parameters: {'Omega_m': 0.29310762835174614, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:29,575 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.65793890097405}
2023-07-02 10:33:29,576 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:29,577 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0243845
2023-07-02 10:33:29,577 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:29,577 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:29,597 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.3197
2023-07-02 10:33:29,597 [model] Computed derived parameters: {}
2023-07-02 10:33:29,597 [model] Posterior to be computed for parameters {'Omega_m': 0.30867714026610565, 'b1': 0.8170313498069216}
2023-07-02 10:33:29,597 [prior] Evaluating prior at array([0.30867714, 0.81703135])
2023-07-02 10:33:29,598 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:29,598 [model] Got input parameters: {'Omega_m': 0.30867714026610565, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8170313498069216, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:29,598 [classy] Got parameters {'Omega_m': 0.30867714026610565, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:29,598 [classy] Re-using computed results
2023-07-02 10:33:29,598 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.72069560690463}
2023-07-02 10:33:29,598 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:29,598 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8170313498069216, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:29,598 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:29,618 [fs_likelihood.fslikelihood] Computed log-likelihood = -331.069
2023-07-02 10:33:29,618 [model] Computed derived parameters: {}
2023-07-02 10:33:29,618 [model] Posterior to be computed for parameters {'Omega_m': 0.3201995467766069, 'b1': 0.510511879507605}
2023-07-02 10:33:29,618 [prior] Evaluating prior at array([0.32019955, 0.51051188])
2023-07-02 10:33:29,618 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:29,618 [model] Got input parameters: {'Omega_m': 0.3201995467766069, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:29,618 [classy] Got parameters {'Omega_m': 0.3201995467766069, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:29,618 [classy] Computing new state
2023-07-02 10:33:29,618 [classy] Setting parameters: {'Omega_m': 0.3201995467766069, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:29,662 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.34179800892252}
2023-07-02 10:33:29,662 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:29,664 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00378357
2023-07-02 10:33:29,664 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:29,664 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:29,684 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.72719
2023-07-02 10:33:29,684 [model] Computed derived parameters: {}
2023-07-02 10:33:29,684 [model] Posterior to be computed for parameters {'Omega_m': 0.30867714026610565, 'b1': 1.5288595821896807}
2023-07-02 10:33:29,684 [prior] Evaluating prior at array([0.30867714, 1.52885958])
2023-07-02 10:33:29,684 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:29,684 [model] Got input parameters: {'Omega_m': 0.30867714026610565, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.5288595821896807, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:29,684 [classy] Got parameters {'Omega_m': 0.30867714026610565, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:29,684 [classy] Re-using computed results
2023-07-02 10:33:29,684 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.72069560690463}
2023-07-02 10:33:29,684 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:29,684 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.5288595821896807, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:29,685 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:29,705 [fs_likelihood.fslikelihood] Computed log-likelihood = -6574.06
2023-07-02 10:33:29,705 [model] Computed derived parameters: {}
2023-07-02 10:33:29,705 [model] Posterior to be computed for parameters {'Omega_m': 0.29296069272429687, 'b1': 0.510511879507605}
2023-07-02 10:33:29,705 [prior] Evaluating prior at array([0.29296069, 0.51051188])
2023-07-02 10:33:29,705 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:29,706 [model] Got input parameters: {'Omega_m': 0.29296069272429687, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:29,706 [classy] Got parameters {'Omega_m': 0.29296069272429687, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:29,706 [classy] Computing new state
2023-07-02 10:33:29,706 [classy] Setting parameters: {'Omega_m': 0.29296069272429687, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:29,751 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.67664911227692}
2023-07-02 10:33:29,751 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:29,753 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0247621
2023-07-02 10:33:29,753 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:29,753 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:29,773 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.40124
2023-07-02 10:33:29,773 [model] Computed derived parameters: {}
2023-07-02 10:33:29,773 [model] Posterior to be computed for parameters {'Omega_m': 0.30867714026610565, 'b1': -0.2206187555957263}
2023-07-02 10:33:29,773 [prior] Evaluating prior at array([ 0.30867714, -0.22061876])
2023-07-02 10:33:29,773 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:29,773 [model] Posterior to be computed for parameters {'Omega_m': 0.3318034490223313, 'b1': 0.510511879507605}
2023-07-02 10:33:29,773 [prior] Evaluating prior at array([0.33180345, 0.51051188])
2023-07-02 10:33:29,774 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:29,774 [model] Got input parameters: {'Omega_m': 0.3318034490223313, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:29,774 [classy] Got parameters {'Omega_m': 0.3318034490223313, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:29,774 [classy] Computing new state
2023-07-02 10:33:29,774 [classy] Setting parameters: {'Omega_m': 0.3318034490223313, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:29,818 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.99725917221437}
2023-07-02 10:33:29,818 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:29,820 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0220345
2023-07-02 10:33:29,820 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:29,820 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:29,840 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.22434
2023-07-02 10:33:29,840 [model] Computed derived parameters: {}
2023-07-02 10:33:29,840 [model] Posterior to be computed for parameters {'Omega_m': 0.30867714026610565, 'b1': 1.3195996238429446}
2023-07-02 10:33:29,840 [prior] Evaluating prior at array([0.30867714, 1.31959962])
2023-07-02 10:33:29,840 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:29,840 [model] Got input parameters: {'Omega_m': 0.30867714026610565, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.3195996238429446, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:29,840 [classy] Got parameters {'Omega_m': 0.30867714026610565, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:29,840 [classy] Re-using computed results
2023-07-02 10:33:29,841 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.72069560690463}
2023-07-02 10:33:29,841 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:29,841 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.3195996238429446, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:29,841 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:29,860 [fs_likelihood.fslikelihood] Computed log-likelihood = -3550.43
2023-07-02 10:33:29,860 [model] Computed derived parameters: {}
2023-07-02 10:33:29,860 [model] Posterior to be computed for parameters {'Omega_m': 0.3106045478832062, 'b1': 0.510511879507605}
2023-07-02 10:33:29,861 [prior] Evaluating prior at array([0.31060455, 0.51051188])
2023-07-02 10:33:29,861 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:29,861 [model] Got input parameters: {'Omega_m': 0.3106045478832062, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:29,861 [classy] Got parameters {'Omega_m': 0.3106045478832062, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:29,861 [classy] Computing new state
2023-07-02 10:33:29,861 [classy] Setting parameters: {'Omega_m': 0.3106045478832062, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:29,905 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.48688575085552}
2023-07-02 10:33:29,905 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:29,907 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000420009
2023-07-02 10:33:29,907 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:29,908 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:29,928 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.79331
2023-07-02 10:33:29,928 [model] Computed derived parameters: {}
2023-07-02 10:33:29,928 [mcmc] New sample, #84:
Omega_m:0.3086771, b1:0.5105119
2023-07-02 10:33:29,928 [model] Posterior to be computed for parameters {'Omega_m': 0.3106045478832062, 'b1': 0.21400178716454288}
2023-07-02 10:33:29,928 [prior] Evaluating prior at array([0.31060455, 0.21400179])
2023-07-02 10:33:29,929 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:29,929 [model] Got input parameters: {'Omega_m': 0.3106045478832062, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.21400178716454288, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:29,929 [classy] Got parameters {'Omega_m': 0.3106045478832062, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:29,929 [classy] Re-using computed results
2023-07-02 10:33:29,929 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.48688575085552}
2023-07-02 10:33:29,929 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:29,929 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.21400178716454288, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:29,929 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:29,949 [fs_likelihood.fslikelihood] Computed log-likelihood = -168.208
2023-07-02 10:33:29,949 [model] Computed derived parameters: {}
2023-07-02 10:33:29,949 [model] Posterior to be computed for parameters {'Omega_m': 0.3162603393052345, 'b1': 0.510511879507605}
2023-07-02 10:33:29,949 [prior] Evaluating prior at array([0.31626034, 0.51051188])
2023-07-02 10:33:29,949 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:29,949 [model] Got input parameters: {'Omega_m': 0.3162603393052345, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:29,949 [classy] Got parameters {'Omega_m': 0.3162603393052345, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:29,949 [classy] Computing new state
2023-07-02 10:33:29,949 [classy] Setting parameters: {'Omega_m': 0.3162603393052345, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:29,993 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.80814397077353}
2023-07-02 10:33:29,994 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:29,995 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0010688
2023-07-02 10:33:29,995 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:29,995 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:30,015 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.49657
2023-07-02 10:33:30,015 [model] Computed derived parameters: {}
2023-07-02 10:33:30,015 [model] Posterior to be computed for parameters {'Omega_m': 0.3106045478832062, 'b1': -0.541302597363798}
2023-07-02 10:33:30,015 [prior] Evaluating prior at array([ 0.31060455, -0.5413026 ])
2023-07-02 10:33:30,016 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:30,016 [model] Posterior to be computed for parameters {'Omega_m': 0.31964494874295624, 'b1': 0.510511879507605}
2023-07-02 10:33:30,016 [prior] Evaluating prior at array([0.31964495, 0.51051188])
2023-07-02 10:33:30,016 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:30,016 [model] Got input parameters: {'Omega_m': 0.31964494874295624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:30,016 [classy] Got parameters {'Omega_m': 0.31964494874295624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:30,016 [classy] Computing new state
2023-07-02 10:33:30,016 [classy] Setting parameters: {'Omega_m': 0.31964494874295624, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:30,060 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.40714501773252}
2023-07-02 10:33:30,060 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:30,062 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00329145
2023-07-02 10:33:30,062 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:30,062 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:30,083 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.86346
2023-07-02 10:33:30,083 [model] Computed derived parameters: {}
2023-07-02 10:33:30,083 [model] Posterior to be computed for parameters {'Omega_m': 0.3106045478832062, 'b1': 3.5107304685957548}
2023-07-02 10:33:30,083 [prior] Evaluating prior at array([0.31060455, 3.51073047])
2023-07-02 10:33:30,083 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:30,083 [model] Got input parameters: {'Omega_m': 0.3106045478832062, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 3.5107304685957548, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:30,083 [classy] Got parameters {'Omega_m': 0.3106045478832062, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:30,083 [classy] Re-using computed results
2023-07-02 10:33:30,083 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.48688575085552}
2023-07-02 10:33:30,083 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:30,083 [fs_likelihood.fslikelihood] Got parameters {'b1': 3.5107304685957548, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:30,083 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:30,103 [fs_likelihood.fslikelihood] Computed log-likelihood = -172463
2023-07-02 10:33:30,103 [model] Computed derived parameters: {}
2023-07-02 10:33:30,103 [model] Posterior to be computed for parameters {'Omega_m': 0.30456567764696935, 'b1': 0.510511879507605}
2023-07-02 10:33:30,103 [prior] Evaluating prior at array([0.30456568, 0.51051188])
2023-07-02 10:33:30,103 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:30,103 [model] Got input parameters: {'Omega_m': 0.30456567764696935, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:30,103 [classy] Got parameters {'Omega_m': 0.30456567764696935, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:30,104 [classy] Computing new state
2023-07-02 10:33:30,104 [classy] Setting parameters: {'Omega_m': 0.30456567764696935, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:30,158 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2237685652061}
2023-07-02 10:33:30,158 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:30,160 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00412433
2023-07-02 10:33:30,160 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:30,160 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:30,180 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.05874
2023-07-02 10:33:30,180 [model] Computed derived parameters: {}
2023-07-02 10:33:30,180 [mcmc] New sample, #85:
Omega_m:0.3106045, b1:0.5105119
2023-07-02 10:33:30,180 [model] Posterior to be computed for parameters {'Omega_m': 0.30456567764696935, 'b1': 1.146721970671471}
2023-07-02 10:33:30,180 [prior] Evaluating prior at array([0.30456568, 1.14672197])
2023-07-02 10:33:30,181 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:30,181 [model] Got input parameters: {'Omega_m': 0.30456567764696935, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.146721970671471, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:30,181 [classy] Got parameters {'Omega_m': 0.30456567764696935, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:30,181 [classy] Re-using computed results
2023-07-02 10:33:30,181 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2237685652061}
2023-07-02 10:33:30,181 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:30,181 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.146721970671471, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:30,181 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:30,201 [fs_likelihood.fslikelihood] Computed log-likelihood = -1846.08
2023-07-02 10:33:30,201 [model] Computed derived parameters: {}
2023-07-02 10:33:30,201 [model] Posterior to be computed for parameters {'Omega_m': 0.28747699989957104, 'b1': 0.510511879507605}
2023-07-02 10:33:30,201 [prior] Evaluating prior at array([0.287477 , 0.51051188])
2023-07-02 10:33:30,201 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:30,201 [model] Got input parameters: {'Omega_m': 0.28747699989957104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:30,201 [classy] Got parameters {'Omega_m': 0.28747699989957104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:30,201 [classy] Computing new state
2023-07-02 10:33:30,201 [classy] Setting parameters: {'Omega_m': 0.28747699989957104, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:30,245 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.38067460101394}
2023-07-02 10:33:30,245 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:30,247 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0410732
2023-07-02 10:33:30,247 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:30,247 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:30,267 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.90381
2023-07-02 10:33:30,267 [model] Computed derived parameters: {}
2023-07-02 10:33:30,267 [model] Posterior to be computed for parameters {'Omega_m': 0.30456567764696935, 'b1': 1.5801913557241027}
2023-07-02 10:33:30,267 [prior] Evaluating prior at array([0.30456568, 1.58019136])
2023-07-02 10:33:30,267 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:30,267 [model] Got input parameters: {'Omega_m': 0.30456567764696935, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.5801913557241027, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:30,267 [classy] Got parameters {'Omega_m': 0.30456567764696935, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:30,267 [classy] Re-using computed results
2023-07-02 10:33:30,267 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2237685652061}
2023-07-02 10:33:30,267 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:30,267 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.5801913557241027, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:30,267 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:30,287 [fs_likelihood.fslikelihood] Computed log-likelihood = -7328.07
2023-07-02 10:33:30,288 [model] Computed derived parameters: {}
2023-07-02 10:33:30,288 [model] Posterior to be computed for parameters {'Omega_m': 0.30513132895419104, 'b1': 0.510511879507605}
2023-07-02 10:33:30,288 [prior] Evaluating prior at array([0.30513133, 0.51051188])
2023-07-02 10:33:30,288 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:30,288 [model] Got input parameters: {'Omega_m': 0.30513132895419104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:30,288 [classy] Got parameters {'Omega_m': 0.30513132895419104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:30,288 [classy] Computing new state
2023-07-02 10:33:30,288 [classy] Setting parameters: {'Omega_m': 0.30513132895419104, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:30,333 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.15420420376265}
2023-07-02 10:33:30,333 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:30,335 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00357923
2023-07-02 10:33:30,335 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:30,335 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:30,355 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.17364
2023-07-02 10:33:30,356 [model] Computed derived parameters: {}
2023-07-02 10:33:30,356 [mcmc] New sample, #86:
Omega_m:0.3045657, b1:0.5105119
2023-07-02 10:33:30,356 [model] Posterior to be computed for parameters {'Omega_m': 0.30513132895419104, 'b1': -0.1255377975072438}
2023-07-02 10:33:30,356 [prior] Evaluating prior at array([ 0.30513133, -0.1255378 ])
2023-07-02 10:33:30,356 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:30,356 [model] Posterior to be computed for parameters {'Omega_m': 0.2982486691649924, 'b1': 0.510511879507605}
2023-07-02 10:33:30,356 [prior] Evaluating prior at array([0.29824867, 0.51051188])
2023-07-02 10:33:30,356 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:30,356 [model] Got input parameters: {'Omega_m': 0.2982486691649924, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:30,356 [classy] Got parameters {'Omega_m': 0.2982486691649924, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:30,356 [classy] Computing new state
2023-07-02 10:33:30,356 [classy] Setting parameters: {'Omega_m': 0.2982486691649924, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:30,402 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.0084779442951}
2023-07-02 10:33:30,402 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:30,404 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0130828
2023-07-02 10:33:30,404 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:30,404 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:30,424 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.128324
2023-07-02 10:33:30,424 [model] Computed derived parameters: {}
2023-07-02 10:33:30,424 [model] Posterior to be computed for parameters {'Omega_m': 0.30513132895419104, 'b1': 1.4045761218467945}
2023-07-02 10:33:30,424 [prior] Evaluating prior at array([0.30513133, 1.40457612])
2023-07-02 10:33:30,425 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:30,425 [model] Got input parameters: {'Omega_m': 0.30513132895419104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.4045761218467945, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:30,425 [classy] Got parameters {'Omega_m': 0.30513132895419104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:30,425 [classy] Re-using computed results
2023-07-02 10:33:30,425 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.15420420376265}
2023-07-02 10:33:30,425 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:30,425 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.4045761218467945, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:30,425 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:30,445 [fs_likelihood.fslikelihood] Computed log-likelihood = -4510.75
2023-07-02 10:33:30,445 [model] Computed derived parameters: {}
2023-07-02 10:33:30,445 [model] Posterior to be computed for parameters {'Omega_m': 0.2934181760088821, 'b1': 0.510511879507605}
2023-07-02 10:33:30,445 [prior] Evaluating prior at array([0.29341818, 0.51051188])
2023-07-02 10:33:30,445 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:30,445 [model] Got input parameters: {'Omega_m': 0.2934181760088821, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:30,445 [classy] Got parameters {'Omega_m': 0.2934181760088821, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:30,445 [classy] Computing new state
2023-07-02 10:33:30,445 [classy] Setting parameters: {'Omega_m': 0.2934181760088821, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:30,489 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.61842936385415}
2023-07-02 10:33:30,489 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:30,491 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0235968
2023-07-02 10:33:30,491 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:30,491 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:30,511 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.1495
2023-07-02 10:33:30,511 [model] Computed derived parameters: {}
2023-07-02 10:33:30,511 [model] Posterior to be computed for parameters {'Omega_m': 0.30513132895419104, 'b1': -0.4060076221101059}
2023-07-02 10:33:30,511 [prior] Evaluating prior at array([ 0.30513133, -0.40600762])
2023-07-02 10:33:30,511 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:30,511 [model] Posterior to be computed for parameters {'Omega_m': 0.32889537577222305, 'b1': 0.510511879507605}
2023-07-02 10:33:30,511 [prior] Evaluating prior at array([0.32889538, 0.51051188])
2023-07-02 10:33:30,511 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:30,511 [model] Got input parameters: {'Omega_m': 0.32889537577222305, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:30,511 [classy] Got parameters {'Omega_m': 0.32889537577222305, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:30,511 [classy] Computing new state
2023-07-02 10:33:30,511 [classy] Setting parameters: {'Omega_m': 0.32889537577222305, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:30,555 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.33018195655924}
2023-07-02 10:33:30,555 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:30,557 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0160676
2023-07-02 10:33:30,557 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:30,557 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:30,576 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.60695
2023-07-02 10:33:30,577 [model] Computed derived parameters: {}
2023-07-02 10:33:30,577 [model] Posterior to be computed for parameters {'Omega_m': 0.30513132895419104, 'b1': 0.8638417869564398}
2023-07-02 10:33:30,577 [prior] Evaluating prior at array([0.30513133, 0.86384179])
2023-07-02 10:33:30,577 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:30,577 [model] Got input parameters: {'Omega_m': 0.30513132895419104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8638417869564398, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:30,577 [classy] Got parameters {'Omega_m': 0.30513132895419104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:30,577 [classy] Re-using computed results
2023-07-02 10:33:30,577 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.15420420376265}
2023-07-02 10:33:30,577 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:30,577 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8638417869564398, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:30,577 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:30,597 [fs_likelihood.fslikelihood] Computed log-likelihood = -439.393
2023-07-02 10:33:30,597 [model] Computed derived parameters: {}
2023-07-02 10:33:30,597 [model] Posterior to be computed for parameters {'Omega_m': 0.30286665987814726, 'b1': 0.510511879507605}
2023-07-02 10:33:30,597 [prior] Evaluating prior at array([0.30286666, 0.51051188])
2023-07-02 10:33:30,597 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:30,597 [model] Got input parameters: {'Omega_m': 0.30286665987814726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:30,597 [classy] Got parameters {'Omega_m': 0.30286665987814726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:30,597 [classy] Computing new state
2023-07-02 10:33:30,597 [classy] Setting parameters: {'Omega_m': 0.30286665987814726, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:30,641 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.4334017783611}
2023-07-02 10:33:30,641 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:30,643 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00601269
2023-07-02 10:33:30,643 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:30,643 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:30,662 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.65634
2023-07-02 10:33:30,662 [model] Computed derived parameters: {}
2023-07-02 10:33:30,662 [mcmc] New sample, #87:
Omega_m:0.3051313, b1:0.5105119
2023-07-02 10:33:30,662 [model] Posterior to be computed for parameters {'Omega_m': 0.30286665987814726, 'b1': 3.340819491012145}
2023-07-02 10:33:30,662 [prior] Evaluating prior at array([0.30286666, 3.34081949])
2023-07-02 10:33:30,662 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:30,662 [model] Got input parameters: {'Omega_m': 0.30286665987814726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 3.340819491012145, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:30,662 [classy] Got parameters {'Omega_m': 0.30286665987814726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:30,662 [classy] Re-using computed results
2023-07-02 10:33:30,663 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.4334017783611}
2023-07-02 10:33:30,663 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:30,663 [fs_likelihood.fslikelihood] Got parameters {'b1': 3.340819491012145, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:30,663 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:30,682 [fs_likelihood.fslikelihood] Computed log-likelihood = -137440
2023-07-02 10:33:30,682 [model] Computed derived parameters: {}
2023-07-02 10:33:30,682 [model] Posterior to be computed for parameters {'Omega_m': 0.314983268365396, 'b1': 0.510511879507605}
2023-07-02 10:33:30,682 [prior] Evaluating prior at array([0.31498327, 0.51051188])
2023-07-02 10:33:30,682 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:30,682 [model] Got input parameters: {'Omega_m': 0.314983268365396, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:30,682 [classy] Got parameters {'Omega_m': 0.314983268365396, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:30,682 [classy] Computing new state
2023-07-02 10:33:30,682 [classy] Setting parameters: {'Omega_m': 0.314983268365396, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:30,726 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.96044280105662}
2023-07-02 10:33:30,726 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:30,728 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000583166
2023-07-02 10:33:30,728 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:30,728 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:30,748 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.64682
2023-07-02 10:33:30,748 [model] Computed derived parameters: {}
2023-07-02 10:33:30,748 [mcmc] New sample, #88:
Omega_m:0.3028667, b1:0.5105119
2023-07-02 10:33:30,748 [model] Posterior to be computed for parameters {'Omega_m': 0.314983268365396, 'b1': -0.0034649455522184347}
2023-07-02 10:33:30,748 [prior] Evaluating prior at array([ 0.31498327, -0.00346495])
2023-07-02 10:33:30,748 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:30,749 [model] Posterior to be computed for parameters {'Omega_m': 0.30020534454799486, 'b1': 0.510511879507605}
2023-07-02 10:33:30,749 [prior] Evaluating prior at array([0.30020534, 0.51051188])
2023-07-02 10:33:30,749 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:30,749 [model] Got input parameters: {'Omega_m': 0.30020534454799486, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:30,749 [classy] Got parameters {'Omega_m': 0.30020534454799486, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:30,749 [classy] Computing new state
2023-07-02 10:33:30,749 [classy] Setting parameters: {'Omega_m': 0.30020534454799486, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:30,793 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.76385339293995}
2023-07-02 10:33:30,793 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:30,794 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00973721
2023-07-02 10:33:30,794 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:30,794 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:30,814 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.853282
2023-07-02 10:33:30,814 [model] Computed derived parameters: {}
2023-07-02 10:33:30,814 [model] Posterior to be computed for parameters {'Omega_m': 0.314983268365396, 'b1': 0.13609352219110488}
2023-07-02 10:33:30,814 [prior] Evaluating prior at array([0.31498327, 0.13609352])
2023-07-02 10:33:30,814 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:30,814 [model] Got input parameters: {'Omega_m': 0.314983268365396, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.13609352219110488, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:30,814 [classy] Got parameters {'Omega_m': 0.314983268365396, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:30,814 [classy] Re-using computed results
2023-07-02 10:33:30,814 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.96044280105662}
2023-07-02 10:33:30,815 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:30,815 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.13609352219110488, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:30,815 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:30,834 [fs_likelihood.fslikelihood] Computed log-likelihood = -240.707
2023-07-02 10:33:30,834 [model] Computed derived parameters: {}
2023-07-02 10:33:30,834 [model] Posterior to be computed for parameters {'Omega_m': 0.27339348975141387, 'b1': 0.510511879507605}
2023-07-02 10:33:30,834 [prior] Evaluating prior at array([0.27339349, 0.51051188])
2023-07-02 10:33:30,834 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:30,834 [model] Got input parameters: {'Omega_m': 0.27339348975141387, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:30,835 [classy] Got parameters {'Omega_m': 0.27339348975141387, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:30,835 [classy] Computing new state
2023-07-02 10:33:30,835 [classy] Setting parameters: {'Omega_m': 0.27339348975141387, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:30,878 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.2433553636712}
2023-07-02 10:33:30,878 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:30,880 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.103874
2023-07-02 10:33:30,880 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:30,880 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:30,900 [fs_likelihood.fslikelihood] Computed log-likelihood = -19.002
2023-07-02 10:33:30,900 [model] Computed derived parameters: {}
2023-07-02 10:33:30,900 [model] Posterior to be computed for parameters {'Omega_m': 0.314983268365396, 'b1': 1.0454258679711703}
2023-07-02 10:33:30,900 [prior] Evaluating prior at array([0.31498327, 1.04542587])
2023-07-02 10:33:30,901 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:30,901 [model] Got input parameters: {'Omega_m': 0.314983268365396, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.0454258679711703, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:30,901 [classy] Got parameters {'Omega_m': 0.314983268365396, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:30,901 [classy] Re-using computed results
2023-07-02 10:33:30,901 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.96044280105662}
2023-07-02 10:33:30,901 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:30,901 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.0454258679711703, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:30,901 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:30,922 [fs_likelihood.fslikelihood] Computed log-likelihood = -1319.56
2023-07-02 10:33:30,922 [model] Computed derived parameters: {}
2023-07-02 10:33:30,922 [model] Posterior to be computed for parameters {'Omega_m': 0.29452615129947335, 'b1': 0.510511879507605}
2023-07-02 10:33:30,922 [prior] Evaluating prior at array([0.29452615, 0.51051188])
2023-07-02 10:33:30,922 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:30,922 [model] Got input parameters: {'Omega_m': 0.29452615129947335, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:30,922 [classy] Got parameters {'Omega_m': 0.29452615129947335, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:30,922 [classy] Computing new state
2023-07-02 10:33:30,922 [classy] Setting parameters: {'Omega_m': 0.29452615129947335, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:30,966 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.47775750773326}
2023-07-02 10:33:30,966 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:30,968 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0208976
2023-07-02 10:33:30,968 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:30,968 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:30,988 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.56563
2023-07-02 10:33:30,988 [model] Computed derived parameters: {}
2023-07-02 10:33:30,988 [model] Posterior to be computed for parameters {'Omega_m': 0.314983268365396, 'b1': -0.24265851412123307}
2023-07-02 10:33:30,988 [prior] Evaluating prior at array([ 0.31498327, -0.24265851])
2023-07-02 10:33:30,988 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:30,988 [model] Posterior to be computed for parameters {'Omega_m': 0.3040363147599663, 'b1': 0.510511879507605}
2023-07-02 10:33:30,988 [prior] Evaluating prior at array([0.30403631, 0.51051188])
2023-07-02 10:33:30,988 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:30,988 [model] Got input parameters: {'Omega_m': 0.3040363147599663, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:30,988 [classy] Got parameters {'Omega_m': 0.3040363147599663, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:30,988 [classy] Computing new state
2023-07-02 10:33:30,988 [classy] Setting parameters: {'Omega_m': 0.3040363147599663, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:31,033 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.28897360630606}
2023-07-02 10:33:31,033 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:31,034 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00467218
2023-07-02 10:33:31,034 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:31,034 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:31,054 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.94258
2023-07-02 10:33:31,055 [model] Computed derived parameters: {}
2023-07-02 10:33:31,055 [mcmc] New sample, #89:
Omega_m:0.3149833, b1:0.5105119
2023-07-02 10:33:31,055 [model] Posterior to be computed for parameters {'Omega_m': 0.3040363147599663, 'b1': -0.8481631845335226}
2023-07-02 10:33:31,055 [prior] Evaluating prior at array([ 0.30403631, -0.84816318])
2023-07-02 10:33:31,055 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:31,055 [model] Posterior to be computed for parameters {'Omega_m': 0.33597264887436257, 'b1': 0.510511879507605}
2023-07-02 10:33:31,055 [prior] Evaluating prior at array([0.33597265, 0.51051188])
2023-07-02 10:33:31,055 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:31,055 [model] Got input parameters: {'Omega_m': 0.33597264887436257, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:31,055 [classy] Got parameters {'Omega_m': 0.33597264887436257, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:31,055 [classy] Computing new state
2023-07-02 10:33:31,055 [classy] Setting parameters: {'Omega_m': 0.33597264887436257, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:31,099 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.5245344783747}
2023-07-02 10:33:31,100 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:31,101 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0321534
2023-07-02 10:33:31,101 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:31,101 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:31,124 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.98242
2023-07-02 10:33:31,124 [model] Computed derived parameters: {}
2023-07-02 10:33:31,124 [model] Posterior to be computed for parameters {'Omega_m': 0.3040363147599663, 'b1': 0.4223719764271592}
2023-07-02 10:33:31,124 [prior] Evaluating prior at array([0.30403631, 0.42237198])
2023-07-02 10:33:31,124 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:31,124 [model] Got input parameters: {'Omega_m': 0.3040363147599663, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4223719764271592, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:31,124 [classy] Got parameters {'Omega_m': 0.3040363147599663, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:31,124 [classy] Re-using computed results
2023-07-02 10:33:31,124 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.28897360630606}
2023-07-02 10:33:31,124 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:31,124 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4223719764271592, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:31,124 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:31,146 [fs_likelihood.fslikelihood] Computed log-likelihood = -20.9466
2023-07-02 10:33:31,146 [model] Computed derived parameters: {}
2023-07-02 10:33:31,146 [model] Posterior to be computed for parameters {'Omega_m': 0.3073216159437114, 'b1': 0.510511879507605}
2023-07-02 10:33:31,146 [prior] Evaluating prior at array([0.30732162, 0.51051188])
2023-07-02 10:33:31,146 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:31,146 [model] Got input parameters: {'Omega_m': 0.3073216159437114, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:31,146 [classy] Got parameters {'Omega_m': 0.3073216159437114, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:31,146 [classy] Computing new state
2023-07-02 10:33:31,146 [classy] Setting parameters: {'Omega_m': 0.3073216159437114, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:31,190 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.8859019013764}
2023-07-02 10:33:31,190 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:31,192 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00185794
2023-07-02 10:33:31,192 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:31,192 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:31,212 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.52867
2023-07-02 10:33:31,212 [model] Computed derived parameters: {}
2023-07-02 10:33:31,212 [mcmc] New sample, #90:
Omega_m:0.3040363, b1:0.5105119
2023-07-02 10:33:31,212 [model] Posterior to be computed for parameters {'Omega_m': 0.3073216159437114, 'b1': 1.4644300837696178}
2023-07-02 10:33:31,212 [prior] Evaluating prior at array([0.30732162, 1.46443008])
2023-07-02 10:33:31,212 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:31,212 [model] Got input parameters: {'Omega_m': 0.3073216159437114, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.4644300837696178, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:31,212 [classy] Got parameters {'Omega_m': 0.3073216159437114, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:31,212 [classy] Re-using computed results
2023-07-02 10:33:31,212 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.8859019013764}
2023-07-02 10:33:31,212 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:31,212 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.4644300837696178, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:31,212 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:31,232 [fs_likelihood.fslikelihood] Computed log-likelihood = -5453.8
2023-07-02 10:33:31,232 [model] Computed derived parameters: {}
2023-07-02 10:33:31,232 [model] Posterior to be computed for parameters {'Omega_m': 0.30511359508866737, 'b1': 0.510511879507605}
2023-07-02 10:33:31,232 [prior] Evaluating prior at array([0.3051136 , 0.51051188])
2023-07-02 10:33:31,233 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:31,233 [model] Got input parameters: {'Omega_m': 0.30511359508866737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:31,233 [classy] Got parameters {'Omega_m': 0.30511359508866737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:31,233 [classy] Computing new state
2023-07-02 10:33:31,233 [classy] Setting parameters: {'Omega_m': 0.30511359508866737, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:31,276 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.1563815789092}
2023-07-02 10:33:31,277 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:31,278 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00359567
2023-07-02 10:33:31,278 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:31,278 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:31,299 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.17018
2023-07-02 10:33:31,299 [model] Computed derived parameters: {}
2023-07-02 10:33:31,299 [mcmc] New sample, #91:
Omega_m:0.3073216, b1:0.5105119
2023-07-02 10:33:31,299 [model] Posterior to be computed for parameters {'Omega_m': 0.30511359508866737, 'b1': -0.29015794151644647}
2023-07-02 10:33:31,299 [prior] Evaluating prior at array([ 0.3051136 , -0.29015794])
2023-07-02 10:33:31,299 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:31,299 [model] Posterior to be computed for parameters {'Omega_m': 0.2946663252175768, 'b1': 0.510511879507605}
2023-07-02 10:33:31,299 [prior] Evaluating prior at array([0.29466633, 0.51051188])
2023-07-02 10:33:31,299 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:31,299 [model] Got input parameters: {'Omega_m': 0.2946663252175768, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:31,299 [classy] Got parameters {'Omega_m': 0.2946663252175768, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:31,299 [classy] Computing new state
2023-07-02 10:33:31,299 [classy] Setting parameters: {'Omega_m': 0.2946663252175768, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:31,345 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.45999214764888}
2023-07-02 10:33:31,345 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:31,347 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0205683
2023-07-02 10:33:31,347 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:31,347 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:31,367 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.49436
2023-07-02 10:33:31,367 [model] Computed derived parameters: {}
2023-07-02 10:33:31,367 [model] Posterior to be computed for parameters {'Omega_m': 0.30511359508866737, 'b1': 0.7263119954371279}
2023-07-02 10:33:31,367 [prior] Evaluating prior at array([0.3051136, 0.726312 ])
2023-07-02 10:33:31,367 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:31,367 [model] Got input parameters: {'Omega_m': 0.30511359508866737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.7263119954371279, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:31,367 [classy] Got parameters {'Omega_m': 0.30511359508866737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:31,367 [classy] Re-using computed results
2023-07-02 10:33:31,367 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.1563815789092}
2023-07-02 10:33:31,367 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:31,367 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.7263119954371279, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:31,367 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:31,386 [fs_likelihood.fslikelihood] Computed log-likelihood = -138.859
2023-07-02 10:33:31,387 [model] Computed derived parameters: {}
2023-07-02 10:33:31,387 [model] Posterior to be computed for parameters {'Omega_m': 0.2952596373400552, 'b1': 0.510511879507605}
2023-07-02 10:33:31,387 [prior] Evaluating prior at array([0.29525964, 0.51051188])
2023-07-02 10:33:31,387 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:31,387 [model] Got input parameters: {'Omega_m': 0.2952596373400552, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:31,387 [classy] Got parameters {'Omega_m': 0.2952596373400552, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:31,387 [classy] Computing new state
2023-07-02 10:33:31,387 [classy] Setting parameters: {'Omega_m': 0.2952596373400552, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:31,431 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.38488513167317}
2023-07-02 10:33:31,431 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:31,433 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0192056
2023-07-02 10:33:31,433 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:31,433 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:31,453 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.19921
2023-07-02 10:33:31,454 [model] Computed derived parameters: {}
2023-07-02 10:33:31,454 [model] Posterior to be computed for parameters {'Omega_m': 0.30511359508866737, 'b1': 0.010467230522064441}
2023-07-02 10:33:31,454 [prior] Evaluating prior at array([0.3051136 , 0.01046723])
2023-07-02 10:33:31,454 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:31,454 [model] Got input parameters: {'Omega_m': 0.30511359508866737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.010467230522064441, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:31,454 [classy] Got parameters {'Omega_m': 0.30511359508866737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:31,454 [classy] Re-using computed results
2023-07-02 10:33:31,454 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.1563815789092}
2023-07-02 10:33:31,454 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:31,454 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.010467230522064441, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:31,454 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:31,474 [fs_likelihood.fslikelihood] Computed log-likelihood = -397.744
2023-07-02 10:33:31,474 [model] Computed derived parameters: {}
2023-07-02 10:33:31,474 [model] Posterior to be computed for parameters {'Omega_m': 0.28736112308624284, 'b1': 0.510511879507605}
2023-07-02 10:33:31,474 [prior] Evaluating prior at array([0.28736112, 0.51051188])
2023-07-02 10:33:31,474 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:31,474 [model] Got input parameters: {'Omega_m': 0.28736112308624284, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:31,474 [classy] Got parameters {'Omega_m': 0.28736112308624284, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:31,474 [classy] Computing new state
2023-07-02 10:33:31,474 [classy] Setting parameters: {'Omega_m': 0.28736112308624284, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:31,519 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.39567769730567}
2023-07-02 10:33:31,519 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:31,521 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0414654
2023-07-02 10:33:31,521 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:31,521 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:31,541 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.98749
2023-07-02 10:33:31,541 [model] Computed derived parameters: {}
2023-07-02 10:33:31,541 [model] Posterior to be computed for parameters {'Omega_m': 0.30511359508866737, 'b1': 1.5258068269156086}
2023-07-02 10:33:31,541 [prior] Evaluating prior at array([0.3051136 , 1.52580683])
2023-07-02 10:33:31,541 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:31,541 [model] Got input parameters: {'Omega_m': 0.30511359508866737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.5258068269156086, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:31,541 [classy] Got parameters {'Omega_m': 0.30511359508866737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:31,541 [classy] Re-using computed results
2023-07-02 10:33:31,541 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.1563815789092}
2023-07-02 10:33:31,541 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:31,541 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.5258068269156086, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:31,541 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:31,561 [fs_likelihood.fslikelihood] Computed log-likelihood = -6368.86
2023-07-02 10:33:31,561 [model] Computed derived parameters: {}
2023-07-02 10:33:31,562 [model] Posterior to be computed for parameters {'Omega_m': 0.28921320678237655, 'b1': 0.510511879507605}
2023-07-02 10:33:31,562 [prior] Evaluating prior at array([0.28921321, 0.51051188])
2023-07-02 10:33:31,562 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:31,562 [model] Got input parameters: {'Omega_m': 0.28921320678237655, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:31,562 [classy] Got parameters {'Omega_m': 0.28921320678237655, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:31,562 [classy] Computing new state
2023-07-02 10:33:31,562 [classy] Setting parameters: {'Omega_m': 0.28921320678237655, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:31,606 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.15652620457902}
2023-07-02 10:33:31,606 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:31,607 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0354356
2023-07-02 10:33:31,607 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:31,607 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:31,627 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.69799
2023-07-02 10:33:31,627 [model] Computed derived parameters: {}
2023-07-02 10:33:31,627 [model] Posterior to be computed for parameters {'Omega_m': 0.30511359508866737, 'b1': 0.14939700929281846}
2023-07-02 10:33:31,627 [prior] Evaluating prior at array([0.3051136 , 0.14939701])
2023-07-02 10:33:31,628 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:31,628 [model] Got input parameters: {'Omega_m': 0.30511359508866737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.14939700929281846, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:31,628 [classy] Got parameters {'Omega_m': 0.30511359508866737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:31,628 [classy] Re-using computed results
2023-07-02 10:33:31,628 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.1563815789092}
2023-07-02 10:33:31,628 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:31,628 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.14939700929281846, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:31,628 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:31,647 [fs_likelihood.fslikelihood] Computed log-likelihood = -244.082
2023-07-02 10:33:31,647 [model] Computed derived parameters: {}
2023-07-02 10:33:31,648 [model] Posterior to be computed for parameters {'Omega_m': 0.30053191871268436, 'b1': 0.510511879507605}
2023-07-02 10:33:31,648 [prior] Evaluating prior at array([0.30053192, 0.51051188])
2023-07-02 10:33:31,648 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:31,648 [model] Got input parameters: {'Omega_m': 0.30053191871268436, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:31,648 [classy] Got parameters {'Omega_m': 0.30053191871268436, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:31,648 [classy] Computing new state
2023-07-02 10:33:31,648 [classy] Setting parameters: {'Omega_m': 0.30053191871268436, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:31,692 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.7231580211562}
2023-07-02 10:33:31,692 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:31,693 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00922912
2023-07-02 10:33:31,693 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:31,693 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:31,713 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.963178
2023-07-02 10:33:31,713 [model] Computed derived parameters: {}
2023-07-02 10:33:31,713 [model] Posterior to be computed for parameters {'Omega_m': 0.30511359508866737, 'b1': 0.41480488255373427}
2023-07-02 10:33:31,714 [prior] Evaluating prior at array([0.3051136 , 0.41480488])
2023-07-02 10:33:31,714 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:31,714 [model] Got input parameters: {'Omega_m': 0.30511359508866737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.41480488255373427, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:31,714 [classy] Got parameters {'Omega_m': 0.30511359508866737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:31,714 [classy] Re-using computed results
2023-07-02 10:33:31,714 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.1563815789092}
2023-07-02 10:33:31,714 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:31,714 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.41480488255373427, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:31,714 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:31,734 [fs_likelihood.fslikelihood] Computed log-likelihood = -23.4164
2023-07-02 10:33:31,734 [model] Computed derived parameters: {}
2023-07-02 10:33:31,734 [model] Posterior to be computed for parameters {'Omega_m': 0.3341128418266844, 'b1': 0.510511879507605}
2023-07-02 10:33:31,734 [prior] Evaluating prior at array([0.33411284, 0.51051188])
2023-07-02 10:33:31,734 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:31,734 [model] Got input parameters: {'Omega_m': 0.3341128418266844, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:31,734 [classy] Got parameters {'Omega_m': 0.3341128418266844, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:31,734 [classy] Computing new state
2023-07-02 10:33:31,734 [classy] Setting parameters: {'Omega_m': 0.3341128418266844, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:31,778 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.73474985200932}
2023-07-02 10:33:31,778 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:31,780 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0274146
2023-07-02 10:33:31,780 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:31,780 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:31,799 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.68815
2023-07-02 10:33:31,799 [model] Computed derived parameters: {}
2023-07-02 10:33:31,799 [model] Posterior to be computed for parameters {'Omega_m': 0.30511359508866737, 'b1': 2.7510528102294525}
2023-07-02 10:33:31,799 [prior] Evaluating prior at array([0.3051136 , 2.75105281])
2023-07-02 10:33:31,799 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:31,799 [model] Got input parameters: {'Omega_m': 0.30511359508866737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 2.7510528102294525, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:31,799 [classy] Got parameters {'Omega_m': 0.30511359508866737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:31,800 [classy] Re-using computed results
2023-07-02 10:33:31,800 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.1563815789092}
2023-07-02 10:33:31,800 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:31,800 [fs_likelihood.fslikelihood] Got parameters {'b1': 2.7510528102294525, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:31,800 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:31,820 [fs_likelihood.fslikelihood] Computed log-likelihood = -65556.1
2023-07-02 10:33:31,820 [model] Computed derived parameters: {}
2023-07-02 10:33:31,820 [model] Posterior to be computed for parameters {'Omega_m': 0.32283816543868477, 'b1': 0.510511879507605}
2023-07-02 10:33:31,820 [prior] Evaluating prior at array([0.32283817, 0.51051188])
2023-07-02 10:33:31,820 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:31,820 [model] Got input parameters: {'Omega_m': 0.32283816543868477, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:31,820 [classy] Got parameters {'Omega_m': 0.32283816543868477, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:31,820 [classy] Computing new state
2023-07-02 10:33:31,820 [classy] Setting parameters: {'Omega_m': 0.32283816543868477, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:31,864 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.03226954824564}
2023-07-02 10:33:31,864 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:31,866 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00661045
2023-07-02 10:33:31,866 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:31,866 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:31,886 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.953443
2023-07-02 10:33:31,886 [model] Computed derived parameters: {}
2023-07-02 10:33:31,886 [model] Posterior to be computed for parameters {'Omega_m': 0.30511359508866737, 'b1': 0.002146526028987905}
2023-07-02 10:33:31,886 [prior] Evaluating prior at array([0.3051136 , 0.00214653])
2023-07-02 10:33:31,886 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:31,886 [model] Got input parameters: {'Omega_m': 0.30511359508866737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.002146526028987905, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:31,886 [classy] Got parameters {'Omega_m': 0.30511359508866737, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:31,886 [classy] Re-using computed results
2023-07-02 10:33:31,886 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.1563815789092}
2023-07-02 10:33:31,886 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:31,886 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.002146526028987905, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:31,886 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:31,906 [fs_likelihood.fslikelihood] Computed log-likelihood = -407.121
2023-07-02 10:33:31,906 [model] Computed derived parameters: {}
2023-07-02 10:33:31,906 [model] Posterior to be computed for parameters {'Omega_m': 0.3078560551897329, 'b1': 0.510511879507605}
2023-07-02 10:33:31,906 [prior] Evaluating prior at array([0.30785606, 0.51051188])
2023-07-02 10:33:31,906 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:31,906 [model] Got input parameters: {'Omega_m': 0.3078560551897329, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:31,906 [classy] Got parameters {'Omega_m': 0.3078560551897329, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:31,906 [classy] Computing new state
2023-07-02 10:33:31,906 [classy] Setting parameters: {'Omega_m': 0.3078560551897329, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:31,950 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.82068910756414}
2023-07-02 10:33:31,950 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:31,952 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00153111
2023-07-02 10:33:31,952 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:31,952 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:31,972 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.59362
2023-07-02 10:33:31,972 [model] Computed derived parameters: {}
2023-07-02 10:33:31,972 [mcmc] New sample, #92:
Omega_m:0.3051136, b1:0.5105119
2023-07-02 10:33:31,972 [model] Posterior to be computed for parameters {'Omega_m': 0.3078560551897329, 'b1': -0.5454829397011657}
2023-07-02 10:33:31,972 [prior] Evaluating prior at array([ 0.30785606, -0.54548294])
2023-07-02 10:33:31,972 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:31,972 [model] Posterior to be computed for parameters {'Omega_m': 0.3098111876524504, 'b1': 0.510511879507605}
2023-07-02 10:33:31,972 [prior] Evaluating prior at array([0.30981119, 0.51051188])
2023-07-02 10:33:31,972 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:31,973 [model] Got input parameters: {'Omega_m': 0.3098111876524504, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:31,973 [classy] Got parameters {'Omega_m': 0.3098111876524504, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:31,973 [classy] Computing new state
2023-07-02 10:33:31,973 [classy] Setting parameters: {'Omega_m': 0.3098111876524504, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:32,017 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.58297050751267}
2023-07-02 10:33:32,018 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:32,020 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00064341
2023-07-02 10:33:32,020 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:32,020 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:32,042 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.75876
2023-07-02 10:33:32,042 [model] Computed derived parameters: {}
2023-07-02 10:33:32,042 [mcmc] New sample, #93:
Omega_m:0.3078561, b1:0.5105119
2023-07-02 10:33:32,042 [model] Posterior to be computed for parameters {'Omega_m': 0.3098111876524504, 'b1': -1.1655607977874505}
2023-07-02 10:33:32,042 [prior] Evaluating prior at array([ 0.30981119, -1.1655608 ])
2023-07-02 10:33:32,042 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:32,042 [model] Posterior to be computed for parameters {'Omega_m': 0.31779364668864063, 'b1': 0.510511879507605}
2023-07-02 10:33:32,042 [prior] Evaluating prior at array([0.31779365, 0.51051188])
2023-07-02 10:33:32,042 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:32,042 [model] Got input parameters: {'Omega_m': 0.31779364668864063, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:32,042 [classy] Got parameters {'Omega_m': 0.31779364668864063, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:32,042 [classy] Computing new state
2023-07-02 10:33:32,042 [classy] Setting parameters: {'Omega_m': 0.31779364668864063, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:32,087 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.6260148063591}
2023-07-02 10:33:32,087 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:32,088 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00190849
2023-07-02 10:33:32,088 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:32,088 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:32,108 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.25202
2023-07-02 10:33:32,108 [model] Computed derived parameters: {}
2023-07-02 10:33:32,108 [mcmc] New sample, #94:
Omega_m:0.3098112, b1:0.5105119
2023-07-02 10:33:32,109 [model] Posterior to be computed for parameters {'Omega_m': 0.31779364668864063, 'b1': 0.35034600656704085}
2023-07-02 10:33:32,109 [prior] Evaluating prior at array([0.31779365, 0.35034601])
2023-07-02 10:33:32,109 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:32,109 [model] Got input parameters: {'Omega_m': 0.31779364668864063, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.35034600656704085, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:32,109 [classy] Got parameters {'Omega_m': 0.31779364668864063, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:32,109 [classy] Re-using computed results
2023-07-02 10:33:32,109 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.6260148063591}
2023-07-02 10:33:32,109 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:32,109 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.35034600656704085, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:32,109 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:32,131 [fs_likelihood.fslikelihood] Computed log-likelihood = -46.0412
2023-07-02 10:33:32,131 [model] Computed derived parameters: {}
2023-07-02 10:33:32,131 [model] Posterior to be computed for parameters {'Omega_m': 0.3098717700283572, 'b1': 0.510511879507605}
2023-07-02 10:33:32,131 [prior] Evaluating prior at array([0.30987177, 0.51051188])
2023-07-02 10:33:32,131 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:32,131 [model] Got input parameters: {'Omega_m': 0.3098717700283572, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:32,131 [classy] Got parameters {'Omega_m': 0.3098717700283572, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:32,131 [classy] Computing new state
2023-07-02 10:33:32,131 [classy] Setting parameters: {'Omega_m': 0.3098717700283572, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:32,176 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.57562556356942}
2023-07-02 10:33:32,176 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:32,178 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000623579
2023-07-02 10:33:32,178 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:32,178 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:32,197 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.76206
2023-07-02 10:33:32,197 [model] Computed derived parameters: {}
2023-07-02 10:33:32,197 [mcmc] New sample, #95:
Omega_m:0.3177936, b1:0.5105119
2023-07-02 10:33:32,198 [model] Posterior to be computed for parameters {'Omega_m': 0.3098717700283572, 'b1': 0.4739781878054233}
2023-07-02 10:33:32,198 [prior] Evaluating prior at array([0.30987177, 0.47397819])
2023-07-02 10:33:32,198 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:32,198 [model] Got input parameters: {'Omega_m': 0.3098717700283572, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4739781878054233, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:32,198 [classy] Got parameters {'Omega_m': 0.3098717700283572, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:32,198 [classy] Re-using computed results
2023-07-02 10:33:32,198 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.57562556356942}
2023-07-02 10:33:32,198 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:32,198 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4739781878054233, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:32,198 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:32,218 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.531097
2023-07-02 10:33:32,218 [model] Computed derived parameters: {}
2023-07-02 10:33:32,218 [model] Posterior to be computed for parameters {'Omega_m': 0.3176712685694544, 'b1': 0.510511879507605}
2023-07-02 10:33:32,218 [prior] Evaluating prior at array([0.31767127, 0.51051188])
2023-07-02 10:33:32,219 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:32,219 [model] Got input parameters: {'Omega_m': 0.3176712685694544, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:32,219 [classy] Got parameters {'Omega_m': 0.3176712685694544, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:32,219 [classy] Computing new state
2023-07-02 10:33:32,219 [classy] Setting parameters: {'Omega_m': 0.3176712685694544, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:32,263 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.64052256841083}
2023-07-02 10:33:32,263 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:32,264 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00183125
2023-07-02 10:33:32,264 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:32,264 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:32,284 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.27411
2023-07-02 10:33:32,284 [model] Computed derived parameters: {}
2023-07-02 10:33:32,284 [model] Posterior to be computed for parameters {'Omega_m': 0.3098717700283572, 'b1': 2.2254855235159896}
2023-07-02 10:33:32,284 [prior] Evaluating prior at array([0.30987177, 2.22548552])
2023-07-02 10:33:32,284 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:32,284 [model] Got input parameters: {'Omega_m': 0.3098717700283572, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 2.2254855235159896, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:32,284 [classy] Got parameters {'Omega_m': 0.3098717700283572, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:32,284 [classy] Re-using computed results
2023-07-02 10:33:32,284 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.57562556356942}
2023-07-02 10:33:32,284 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:32,284 [fs_likelihood.fslikelihood] Got parameters {'b1': 2.2254855235159896, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:32,284 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:32,304 [fs_likelihood.fslikelihood] Computed log-likelihood = -29487.7
2023-07-02 10:33:32,304 [model] Computed derived parameters: {}
2023-07-02 10:33:32,304 [model] Posterior to be computed for parameters {'Omega_m': 0.30227722602460516, 'b1': 0.510511879507605}
2023-07-02 10:33:32,304 [prior] Evaluating prior at array([0.30227723, 0.51051188])
2023-07-02 10:33:32,304 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:32,304 [model] Got input parameters: {'Omega_m': 0.30227722602460516, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:32,304 [classy] Got parameters {'Omega_m': 0.30227722602460516, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:32,304 [classy] Computing new state
2023-07-02 10:33:32,304 [classy] Setting parameters: {'Omega_m': 0.30227722602460516, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:32,348 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.50637125042036}
2023-07-02 10:33:32,349 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:32,350 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00675648
2023-07-02 10:33:32,350 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:32,350 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:32,371 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.49666
2023-07-02 10:33:32,371 [model] Computed derived parameters: {}
2023-07-02 10:33:32,371 [model] Posterior to be computed for parameters {'Omega_m': 0.3098717700283572, 'b1': -0.5690400495012625}
2023-07-02 10:33:32,371 [prior] Evaluating prior at array([ 0.30987177, -0.56904005])
2023-07-02 10:33:32,371 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:32,371 [model] Posterior to be computed for parameters {'Omega_m': 0.31816045863227715, 'b1': 0.510511879507605}
2023-07-02 10:33:32,371 [prior] Evaluating prior at array([0.31816046, 0.51051188])
2023-07-02 10:33:32,371 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:32,371 [model] Got input parameters: {'Omega_m': 0.31816045863227715, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:32,371 [classy] Got parameters {'Omega_m': 0.31816045863227715, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:32,371 [classy] Computing new state
2023-07-02 10:33:32,371 [classy] Setting parameters: {'Omega_m': 0.31816045863227715, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:32,415 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.58255803642194}
2023-07-02 10:33:32,415 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:32,417 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00215059
2023-07-02 10:33:32,417 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:32,417 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:32,437 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.18314
2023-07-02 10:33:32,437 [model] Computed derived parameters: {}
2023-07-02 10:33:32,437 [model] Posterior to be computed for parameters {'Omega_m': 0.3098717700283572, 'b1': 0.7493333508975278}
2023-07-02 10:33:32,437 [prior] Evaluating prior at array([0.30987177, 0.74933335])
2023-07-02 10:33:32,437 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:32,437 [model] Got input parameters: {'Omega_m': 0.3098717700283572, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.7493333508975278, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:32,437 [classy] Got parameters {'Omega_m': 0.3098717700283572, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:32,437 [classy] Re-using computed results
2023-07-02 10:33:32,437 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.57562556356942}
2023-07-02 10:33:32,437 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:32,437 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.7493333508975278, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:32,437 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:32,456 [fs_likelihood.fslikelihood] Computed log-likelihood = -191.347
2023-07-02 10:33:32,457 [model] Computed derived parameters: {}
2023-07-02 10:33:32,457 [model] Posterior to be computed for parameters {'Omega_m': 0.3095633240365326, 'b1': 0.510511879507605}
2023-07-02 10:33:32,457 [prior] Evaluating prior at array([0.30956332, 0.51051188])
2023-07-02 10:33:32,457 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:32,457 [model] Got input parameters: {'Omega_m': 0.3095633240365326, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:32,457 [classy] Got parameters {'Omega_m': 0.3095633240365326, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:32,457 [classy] Computing new state
2023-07-02 10:33:32,457 [classy] Setting parameters: {'Omega_m': 0.3095633240365326, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:32,501 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.61303583139133}
2023-07-02 10:33:32,501 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:32,503 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000729336
2023-07-02 10:33:32,503 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:32,503 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:32,523 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.74412
2023-07-02 10:33:32,523 [model] Computed derived parameters: {}
2023-07-02 10:33:32,523 [mcmc] New sample, #96:
Omega_m:0.3098718, b1:0.5105119
2023-07-02 10:33:32,523 [model] Posterior to be computed for parameters {'Omega_m': 0.3095633240365326, 'b1': 0.7019446235702383}
2023-07-02 10:33:32,523 [prior] Evaluating prior at array([0.30956332, 0.70194462])
2023-07-02 10:33:32,524 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:32,524 [model] Got input parameters: {'Omega_m': 0.3095633240365326, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.7019446235702383, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:32,524 [classy] Got parameters {'Omega_m': 0.3095633240365326, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:32,524 [classy] Re-using computed results
2023-07-02 10:33:32,524 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.61303583139133}
2023-07-02 10:33:32,524 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:32,524 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.7019446235702383, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:32,524 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:32,544 [fs_likelihood.fslikelihood] Computed log-likelihood = -115.991
2023-07-02 10:33:32,544 [model] Computed derived parameters: {}
2023-07-02 10:33:32,544 [model] Posterior to be computed for parameters {'Omega_m': 0.3025119063100622, 'b1': 0.510511879507605}
2023-07-02 10:33:32,544 [prior] Evaluating prior at array([0.30251191, 0.51051188])
2023-07-02 10:33:32,544 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:32,544 [model] Got input parameters: {'Omega_m': 0.3025119063100622, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:32,544 [classy] Got parameters {'Omega_m': 0.3025119063100622, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:32,544 [classy] Computing new state
2023-07-02 10:33:32,544 [classy] Setting parameters: {'Omega_m': 0.3025119063100622, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:32,588 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.47730297595706}
2023-07-02 10:33:32,588 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:32,590 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00645483
2023-07-02 10:33:32,590 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:32,590 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:32,609 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.56148
2023-07-02 10:33:32,609 [model] Computed derived parameters: {}
2023-07-02 10:33:32,610 [model] Posterior to be computed for parameters {'Omega_m': 0.3095633240365326, 'b1': 0.5829274204437522}
2023-07-02 10:33:32,610 [prior] Evaluating prior at array([0.30956332, 0.58292742])
2023-07-02 10:33:32,610 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:32,610 [model] Got input parameters: {'Omega_m': 0.3095633240365326, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5829274204437522, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:32,610 [classy] Got parameters {'Omega_m': 0.3095633240365326, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:32,610 [classy] Re-using computed results
2023-07-02 10:33:32,610 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.61303583139133}
2023-07-02 10:33:32,610 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:32,610 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5829274204437522, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:32,610 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:32,630 [fs_likelihood.fslikelihood] Computed log-likelihood = -12.4893
2023-07-02 10:33:32,630 [model] Computed derived parameters: {}
2023-07-02 10:33:32,630 [model] Posterior to be computed for parameters {'Omega_m': 0.3276328459041586, 'b1': 0.510511879507605}
2023-07-02 10:33:32,630 [prior] Evaluating prior at array([0.32763285, 0.51051188])
2023-07-02 10:33:32,630 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:32,630 [model] Got input parameters: {'Omega_m': 0.3276328459041586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:32,631 [classy] Got parameters {'Omega_m': 0.3276328459041586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:32,631 [classy] Computing new state
2023-07-02 10:33:32,631 [classy] Setting parameters: {'Omega_m': 0.3276328459041586, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:32,674 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.47556045259122}
2023-07-02 10:33:32,674 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:32,676 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0137614
2023-07-02 10:33:32,676 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:32,676 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:32,695 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.983154
2023-07-02 10:33:32,696 [model] Computed derived parameters: {}
2023-07-02 10:33:32,696 [model] Posterior to be computed for parameters {'Omega_m': 0.3095633240365326, 'b1': 0.6411235121404907}
2023-07-02 10:33:32,696 [prior] Evaluating prior at array([0.30956332, 0.64112351])
2023-07-02 10:33:32,696 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:32,696 [model] Got input parameters: {'Omega_m': 0.3095633240365326, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6411235121404907, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:32,696 [classy] Got parameters {'Omega_m': 0.3095633240365326, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:32,696 [classy] Re-using computed results
2023-07-02 10:33:32,696 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.61303583139133}
2023-07-02 10:33:32,696 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:32,696 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6411235121404907, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:32,696 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:32,716 [fs_likelihood.fslikelihood] Computed log-likelihood = -49.4994
2023-07-02 10:33:32,716 [model] Computed derived parameters: {}
2023-07-02 10:33:32,716 [model] Posterior to be computed for parameters {'Omega_m': 0.31244015636324024, 'b1': 0.510511879507605}
2023-07-02 10:33:32,716 [prior] Evaluating prior at array([0.31244016, 0.51051188])
2023-07-02 10:33:32,716 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:32,716 [model] Got input parameters: {'Omega_m': 0.31244015636324024, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:32,716 [classy] Got parameters {'Omega_m': 0.31244015636324024, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:32,716 [classy] Computing new state
2023-07-02 10:33:32,716 [classy] Setting parameters: {'Omega_m': 0.31244015636324024, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:32,761 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.2653991901287}
2023-07-02 10:33:32,761 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:32,762 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000202492
2023-07-02 10:33:32,763 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:32,763 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:32,782 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.8014
2023-07-02 10:33:32,782 [model] Computed derived parameters: {}
2023-07-02 10:33:32,783 [mcmc] New sample, #97:
Omega_m:0.3095633, b1:0.5105119
2023-07-02 10:33:32,783 [model] Posterior to be computed for parameters {'Omega_m': 0.31244015636324024, 'b1': 0.8217941664462871}
2023-07-02 10:33:32,783 [prior] Evaluating prior at array([0.31244016, 0.82179417])
2023-07-02 10:33:32,783 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:32,783 [model] Got input parameters: {'Omega_m': 0.31244015636324024, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8217941664462871, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:32,783 [classy] Got parameters {'Omega_m': 0.31244015636324024, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:32,783 [classy] Re-using computed results
2023-07-02 10:33:32,783 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.2653991901287}
2023-07-02 10:33:32,783 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:32,783 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8217941664462871, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:32,783 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:32,802 [fs_likelihood.fslikelihood] Computed log-likelihood = -362.145
2023-07-02 10:33:32,802 [model] Computed derived parameters: {}
2023-07-02 10:33:32,802 [model] Posterior to be computed for parameters {'Omega_m': 0.31323915876884106, 'b1': 0.510511879507605}
2023-07-02 10:33:32,802 [prior] Evaluating prior at array([0.31323916, 0.51051188])
2023-07-02 10:33:32,803 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:32,803 [model] Got input parameters: {'Omega_m': 0.31323915876884106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:32,803 [classy] Got parameters {'Omega_m': 0.31323915876884106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:32,803 [classy] Computing new state
2023-07-02 10:33:32,803 [classy] Setting parameters: {'Omega_m': 0.31323915876884106, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:32,847 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.16935013865367}
2023-07-02 10:33:32,847 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:32,849 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0002373
2023-07-02 10:33:32,849 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:32,849 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:32,869 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.77358
2023-07-02 10:33:32,869 [model] Computed derived parameters: {}
2023-07-02 10:33:32,869 [mcmc] New sample, #98:
Omega_m:0.3124402, b1:0.5105119
2023-07-02 10:33:32,869 [model] Posterior to be computed for parameters {'Omega_m': 0.31323915876884106, 'b1': -0.34351747761885154}
2023-07-02 10:33:32,869 [prior] Evaluating prior at array([ 0.31323916, -0.34351748])
2023-07-02 10:33:32,869 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:32,869 [model] Posterior to be computed for parameters {'Omega_m': 0.3059748688108159, 'b1': 0.510511879507605}
2023-07-02 10:33:32,869 [prior] Evaluating prior at array([0.30597487, 0.51051188])
2023-07-02 10:33:32,870 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:32,870 [model] Got input parameters: {'Omega_m': 0.3059748688108159, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:32,870 [classy] Got parameters {'Omega_m': 0.3059748688108159, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:32,870 [classy] Computing new state
2023-07-02 10:33:32,870 [classy] Setting parameters: {'Omega_m': 0.3059748688108159, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:32,913 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.05067481764775}
2023-07-02 10:33:32,913 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:32,915 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00284329
2023-07-02 10:33:32,915 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:32,915 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:32,936 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.32728
2023-07-02 10:33:32,936 [model] Computed derived parameters: {}
2023-07-02 10:33:32,936 [mcmc] New sample, #99:
Omega_m:0.3132392, b1:0.5105119
2023-07-02 10:33:32,936 [model] Posterior to be computed for parameters {'Omega_m': 0.3059748688108159, 'b1': -0.051229575028154284}
2023-07-02 10:33:32,936 [prior] Evaluating prior at array([ 0.30597487, -0.05122958])
2023-07-02 10:33:32,936 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:32,936 [model] Posterior to be computed for parameters {'Omega_m': 0.3120549252100124, 'b1': 0.510511879507605}
2023-07-02 10:33:32,936 [prior] Evaluating prior at array([0.31205493, 0.51051188])
2023-07-02 10:33:32,936 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:32,936 [model] Got input parameters: {'Omega_m': 0.3120549252100124, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:32,936 [classy] Got parameters {'Omega_m': 0.3120549252100124, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:32,936 [classy] Computing new state
2023-07-02 10:33:32,936 [classy] Setting parameters: {'Omega_m': 0.3120549252100124, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:32,980 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.31178730067924}
2023-07-02 10:33:32,980 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:32,982 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00021367
2023-07-02 10:33:32,982 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:32,982 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:33,002 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.80802
2023-07-02 10:33:33,002 [model] Computed derived parameters: {}
2023-07-02 10:33:33,002 [mcmc] New sample, #100:
Omega_m:0.3059749, b1:0.5105119
2023-07-02 10:33:33,002 [model] Posterior to be computed for parameters {'Omega_m': 0.3120549252100124, 'b1': 0.4075412264820113}
2023-07-02 10:33:33,002 [prior] Evaluating prior at array([0.31205493, 0.40754123])
2023-07-02 10:33:33,002 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:33,002 [model] Got input parameters: {'Omega_m': 0.3120549252100124, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4075412264820113, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:33,002 [classy] Got parameters {'Omega_m': 0.3120549252100124, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:33,002 [classy] Re-using computed results
2023-07-02 10:33:33,002 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.31178730067924}
2023-07-02 10:33:33,002 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:33,002 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4075412264820113, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:33,002 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:33,022 [fs_likelihood.fslikelihood] Computed log-likelihood = -20.5697
2023-07-02 10:33:33,022 [model] Computed derived parameters: {}
2023-07-02 10:33:33,022 [model] Posterior to be computed for parameters {'Omega_m': 0.3088482424904877, 'b1': 0.510511879507605}
2023-07-02 10:33:33,022 [prior] Evaluating prior at array([0.30884824, 0.51051188])
2023-07-02 10:33:33,023 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:33,023 [model] Got input parameters: {'Omega_m': 0.3088482424904877, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:33,023 [classy] Got parameters {'Omega_m': 0.3088482424904877, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:33,023 [classy] Computing new state
2023-07-02 10:33:33,023 [classy] Setting parameters: {'Omega_m': 0.3088482424904877, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:33,067 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.69988718689928}
2023-07-02 10:33:33,067 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:33,069 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00102042
2023-07-02 10:33:33,069 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:33,069 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:33,089 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.69165
2023-07-02 10:33:33,089 [model] Computed derived parameters: {}
2023-07-02 10:33:33,089 [model] Posterior to be computed for parameters {'Omega_m': 0.3120549252100124, 'b1': 0.7261570305217346}
2023-07-02 10:33:33,089 [prior] Evaluating prior at array([0.31205493, 0.72615703])
2023-07-02 10:33:33,089 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:33,089 [model] Got input parameters: {'Omega_m': 0.3120549252100124, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.7261570305217346, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:33,089 [classy] Got parameters {'Omega_m': 0.3120549252100124, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:33,089 [classy] Re-using computed results
2023-07-02 10:33:33,089 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.31178730067924}
2023-07-02 10:33:33,089 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:33,089 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.7261570305217346, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:33,089 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:33,109 [fs_likelihood.fslikelihood] Computed log-likelihood = -158.863
2023-07-02 10:33:33,109 [model] Computed derived parameters: {}
2023-07-02 10:33:33,109 [model] Posterior to be computed for parameters {'Omega_m': 0.31088615709183126, 'b1': 0.510511879507605}
2023-07-02 10:33:33,109 [prior] Evaluating prior at array([0.31088616, 0.51051188])
2023-07-02 10:33:33,109 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:33,109 [model] Got input parameters: {'Omega_m': 0.31088615709183126, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:33,109 [classy] Got parameters {'Omega_m': 0.31088615709183126, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:33,109 [classy] Computing new state
2023-07-02 10:33:33,109 [classy] Setting parameters: {'Omega_m': 0.31088615709183126, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:33,163 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.4528310642076}
2023-07-02 10:33:33,163 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:33,165 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000359562
2023-07-02 10:33:33,165 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:33,165 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:33,185 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.80106
2023-07-02 10:33:33,185 [model] Computed derived parameters: {}
2023-07-02 10:33:33,185 [mcmc] New sample, #101:
Omega_m:0.3120549, b1:0.5105119
2023-07-02 10:33:33,185 [model] Posterior to be computed for parameters {'Omega_m': 0.31088615709183126, 'b1': 0.25565431804546845}
2023-07-02 10:33:33,185 [prior] Evaluating prior at array([0.31088616, 0.25565432])
2023-07-02 10:33:33,186 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:33,186 [model] Got input parameters: {'Omega_m': 0.31088615709183126, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.25565431804546845, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:33,186 [classy] Got parameters {'Omega_m': 0.31088615709183126, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:33,186 [classy] Re-using computed results
2023-07-02 10:33:33,186 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.4528310642076}
2023-07-02 10:33:33,186 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:33,186 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.25565431804546845, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:33,186 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:33,205 [fs_likelihood.fslikelihood] Computed log-likelihood = -128.582
2023-07-02 10:33:33,205 [model] Computed derived parameters: {}
2023-07-02 10:33:33,206 [model] Posterior to be computed for parameters {'Omega_m': 0.3024573072565006, 'b1': 0.510511879507605}
2023-07-02 10:33:33,206 [prior] Evaluating prior at array([0.30245731, 0.51051188])
2023-07-02 10:33:33,206 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:33,206 [model] Got input parameters: {'Omega_m': 0.3024573072565006, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:33,206 [classy] Got parameters {'Omega_m': 0.3024573072565006, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:33,206 [classy] Computing new state
2023-07-02 10:33:33,206 [classy] Setting parameters: {'Omega_m': 0.3024573072565006, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:33,251 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.48406417630432}
2023-07-02 10:33:33,251 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:33,253 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00652436
2023-07-02 10:33:33,253 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:33,253 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:33,273 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.54654
2023-07-02 10:33:33,273 [model] Computed derived parameters: {}
2023-07-02 10:33:33,273 [mcmc] New sample, #102:
Omega_m:0.3108862, b1:0.5105119
2023-07-02 10:33:33,273 [model] Posterior to be computed for parameters {'Omega_m': 0.3024573072565006, 'b1': -0.0029531139727430045}
2023-07-02 10:33:33,273 [prior] Evaluating prior at array([ 0.30245731, -0.00295311])
2023-07-02 10:33:33,273 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:33,273 [model] Posterior to be computed for parameters {'Omega_m': 0.2929279432859943, 'b1': 0.510511879507605}
2023-07-02 10:33:33,273 [prior] Evaluating prior at array([0.29292794, 0.51051188])
2023-07-02 10:33:33,273 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:33,273 [model] Got input parameters: {'Omega_m': 0.2929279432859943, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:33,273 [classy] Got parameters {'Omega_m': 0.2929279432859943, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:33,273 [classy] Computing new state
2023-07-02 10:33:33,273 [classy] Setting parameters: {'Omega_m': 0.2929279432859943, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:33,317 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.68081943336216}
2023-07-02 10:33:33,317 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:33,319 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0248466
2023-07-02 10:33:33,319 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:33,319 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:33,339 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.4195
2023-07-02 10:33:33,339 [model] Computed derived parameters: {}
2023-07-02 10:33:33,340 [model] Posterior to be computed for parameters {'Omega_m': 0.3024573072565006, 'b1': 1.0457747798097379}
2023-07-02 10:33:33,340 [prior] Evaluating prior at array([0.30245731, 1.04577478])
2023-07-02 10:33:33,340 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:33,340 [model] Got input parameters: {'Omega_m': 0.3024573072565006, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.0457747798097379, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:33,340 [classy] Got parameters {'Omega_m': 0.3024573072565006, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:33,340 [classy] Re-using computed results
2023-07-02 10:33:33,340 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.48406417630432}
2023-07-02 10:33:33,340 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:33,340 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.0457747798097379, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:33,340 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:33,359 [fs_likelihood.fslikelihood] Computed log-likelihood = -1171.06
2023-07-02 10:33:33,359 [model] Computed derived parameters: {}
2023-07-02 10:33:33,359 [model] Posterior to be computed for parameters {'Omega_m': 0.3107013164545705, 'b1': 0.510511879507605}
2023-07-02 10:33:33,359 [prior] Evaluating prior at array([0.31070132, 0.51051188])
2023-07-02 10:33:33,360 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:33,360 [model] Got input parameters: {'Omega_m': 0.3107013164545705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:33,360 [classy] Got parameters {'Omega_m': 0.3107013164545705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:33,360 [classy] Computing new state
2023-07-02 10:33:33,360 [classy] Setting parameters: {'Omega_m': 0.3107013164545705, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:33,403 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.4751799042501}
2023-07-02 10:33:33,403 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:33,405 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000398126
2023-07-02 10:33:33,405 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:33,405 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:33,425 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.79624
2023-07-02 10:33:33,425 [model] Computed derived parameters: {}
2023-07-02 10:33:33,425 [mcmc] New sample, #103:
Omega_m:0.3024573, b1:0.5105119
2023-07-02 10:33:33,425 [model] Posterior to be computed for parameters {'Omega_m': 0.3107013164545705, 'b1': 1.2630737449377112}
2023-07-02 10:33:33,425 [prior] Evaluating prior at array([0.31070132, 1.26307374])
2023-07-02 10:33:33,426 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:33,426 [model] Got input parameters: {'Omega_m': 0.3107013164545705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.2630737449377112, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:33,426 [classy] Got parameters {'Omega_m': 0.3107013164545705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:33,426 [classy] Re-using computed results
2023-07-02 10:33:33,426 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.4751799042501}
2023-07-02 10:33:33,426 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:33,426 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.2630737449377112, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:33,426 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:33,445 [fs_likelihood.fslikelihood] Computed log-likelihood = -2985.66
2023-07-02 10:33:33,445 [model] Computed derived parameters: {}
2023-07-02 10:33:33,445 [model] Posterior to be computed for parameters {'Omega_m': 0.31653720497102433, 'b1': 0.510511879507605}
2023-07-02 10:33:33,445 [prior] Evaluating prior at array([0.3165372 , 0.51051188])
2023-07-02 10:33:33,446 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:33,446 [model] Got input parameters: {'Omega_m': 0.31653720497102433, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:33,446 [classy] Got parameters {'Omega_m': 0.31653720497102433, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:33,446 [classy] Computing new state
2023-07-02 10:33:33,446 [classy] Setting parameters: {'Omega_m': 0.31653720497102433, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:33,489 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.77520280376365}
2023-07-02 10:33:33,490 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:33,491 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00119973
2023-07-02 10:33:33,491 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:33,491 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:33,511 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.45759
2023-07-02 10:33:33,511 [model] Computed derived parameters: {}
2023-07-02 10:33:33,511 [model] Posterior to be computed for parameters {'Omega_m': 0.3107013164545705, 'b1': 0.35923669070561437}
2023-07-02 10:33:33,511 [prior] Evaluating prior at array([0.31070132, 0.35923669])
2023-07-02 10:33:33,511 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:33,511 [model] Got input parameters: {'Omega_m': 0.3107013164545705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.35923669070561437, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:33,511 [classy] Got parameters {'Omega_m': 0.3107013164545705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:33,511 [classy] Re-using computed results
2023-07-02 10:33:33,511 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.4751799042501}
2023-07-02 10:33:33,511 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:33,511 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.35923669070561437, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:33,511 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:33,531 [fs_likelihood.fslikelihood] Computed log-likelihood = -48.309
2023-07-02 10:33:33,531 [model] Computed derived parameters: {}
2023-07-02 10:33:33,532 [model] Posterior to be computed for parameters {'Omega_m': 0.3241404327454483, 'b1': 0.510511879507605}
2023-07-02 10:33:33,532 [prior] Evaluating prior at array([0.32414043, 0.51051188])
2023-07-02 10:33:33,532 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:33,532 [model] Got input parameters: {'Omega_m': 0.3241404327454483, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:33,532 [classy] Got parameters {'Omega_m': 0.3241404327454483, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:33,532 [classy] Computing new state
2023-07-02 10:33:33,532 [classy] Setting parameters: {'Omega_m': 0.3241404327454483, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:33,575 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.88033485696266}
2023-07-02 10:33:33,576 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:33,577 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00829815
2023-07-02 10:33:33,577 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:33,577 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:33,597 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.49516
2023-07-02 10:33:33,597 [model] Computed derived parameters: {}
2023-07-02 10:33:33,597 [model] Posterior to be computed for parameters {'Omega_m': 0.3107013164545705, 'b1': -3.7181572723007545}
2023-07-02 10:33:33,597 [prior] Evaluating prior at array([ 0.31070132, -3.71815727])
2023-07-02 10:33:33,597 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:33,597 [model] Posterior to be computed for parameters {'Omega_m': 0.3192744571498333, 'b1': 0.510511879507605}
2023-07-02 10:33:33,597 [prior] Evaluating prior at array([0.31927446, 0.51051188])
2023-07-02 10:33:33,598 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:33,598 [model] Got input parameters: {'Omega_m': 0.3192744571498333, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:33,598 [classy] Got parameters {'Omega_m': 0.3192744571498333, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:33,598 [classy] Computing new state
2023-07-02 10:33:33,598 [classy] Setting parameters: {'Omega_m': 0.3192744571498333, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:33,642 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.45085462148103}
2023-07-02 10:33:33,642 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:33,643 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00298263
2023-07-02 10:33:33,643 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:33,643 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:33,663 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.94939
2023-07-02 10:33:33,663 [model] Computed derived parameters: {}
2023-07-02 10:33:33,663 [model] Posterior to be computed for parameters {'Omega_m': 0.3107013164545705, 'b1': 0.6962168149088418}
2023-07-02 10:33:33,663 [prior] Evaluating prior at array([0.31070132, 0.69621681])
2023-07-02 10:33:33,663 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:33,663 [model] Got input parameters: {'Omega_m': 0.3107013164545705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6962168149088418, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:33,663 [classy] Got parameters {'Omega_m': 0.3107013164545705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:33,663 [classy] Re-using computed results
2023-07-02 10:33:33,664 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.4751799042501}
2023-07-02 10:33:33,664 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:33,664 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6962168149088418, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:33,664 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:33,684 [fs_likelihood.fslikelihood] Computed log-likelihood = -111.185
2023-07-02 10:33:33,684 [model] Computed derived parameters: {}
2023-07-02 10:33:33,684 [model] Posterior to be computed for parameters {'Omega_m': 0.31810829980286986, 'b1': 0.510511879507605}
2023-07-02 10:33:33,684 [prior] Evaluating prior at array([0.3181083 , 0.51051188])
2023-07-02 10:33:33,684 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:33,684 [model] Got input parameters: {'Omega_m': 0.31810829980286986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:33,684 [classy] Got parameters {'Omega_m': 0.31810829980286986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:33,684 [classy] Computing new state
2023-07-02 10:33:33,684 [classy] Setting parameters: {'Omega_m': 0.31810829980286986, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:33,728 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.5887336823783}
2023-07-02 10:33:33,728 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:33,730 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00211521
2023-07-02 10:33:33,730 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:33,730 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:33,750 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.19317
2023-07-02 10:33:33,750 [model] Computed derived parameters: {}
2023-07-02 10:33:33,750 [model] Posterior to be computed for parameters {'Omega_m': 0.3107013164545705, 'b1': 1.3688422331235148}
2023-07-02 10:33:33,750 [prior] Evaluating prior at array([0.31070132, 1.36884223])
2023-07-02 10:33:33,750 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:33,750 [model] Got input parameters: {'Omega_m': 0.3107013164545705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.3688422331235148, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:33,750 [classy] Got parameters {'Omega_m': 0.3107013164545705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:33,750 [classy] Re-using computed results
2023-07-02 10:33:33,750 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.4751799042501}
2023-07-02 10:33:33,750 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:33,750 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.3688422331235148, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:33,750 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:33,769 [fs_likelihood.fslikelihood] Computed log-likelihood = -4210.03
2023-07-02 10:33:33,770 [model] Computed derived parameters: {}
2023-07-02 10:33:33,770 [model] Posterior to be computed for parameters {'Omega_m': 0.3156534962270178, 'b1': 0.510511879507605}
2023-07-02 10:33:33,770 [prior] Evaluating prior at array([0.3156535 , 0.51051188])
2023-07-02 10:33:33,770 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:33,770 [model] Got input parameters: {'Omega_m': 0.3156534962270178, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:33,770 [classy] Got parameters {'Omega_m': 0.3156534962270178, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:33,770 [classy] Computing new state
2023-07-02 10:33:33,770 [classy] Setting parameters: {'Omega_m': 0.3156534962270178, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:33,814 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.88044928905788}
2023-07-02 10:33:33,814 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:33,816 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000813639
2023-07-02 10:33:33,816 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:33,816 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:33,836 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.57402
2023-07-02 10:33:33,836 [model] Computed derived parameters: {}
2023-07-02 10:33:33,836 [mcmc] New sample, #104:
Omega_m:0.3107013, b1:0.5105119
2023-07-02 10:33:33,836 [model] Posterior to be computed for parameters {'Omega_m': 0.3156534962270178, 'b1': 0.7331327887857564}
2023-07-02 10:33:33,836 [prior] Evaluating prior at array([0.3156535 , 0.73313279])
2023-07-02 10:33:33,837 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:33,837 [model] Got input parameters: {'Omega_m': 0.3156534962270178, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.7331327887857564, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:33,837 [classy] Got parameters {'Omega_m': 0.3156534962270178, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:33,837 [classy] Re-using computed results
2023-07-02 10:33:33,837 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.88044928905788}
2023-07-02 10:33:33,837 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:33,837 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.7331327887857564, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:33,837 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:33,857 [fs_likelihood.fslikelihood] Computed log-likelihood = -182.285
2023-07-02 10:33:33,857 [model] Computed derived parameters: {}
2023-07-02 10:33:33,857 [model] Posterior to be computed for parameters {'Omega_m': 0.30148400148954707, 'b1': 0.510511879507605}
2023-07-02 10:33:33,857 [prior] Evaluating prior at array([0.301484 , 0.51051188])
2023-07-02 10:33:33,857 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:33,857 [model] Got input parameters: {'Omega_m': 0.30148400148954707, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:33,857 [classy] Got parameters {'Omega_m': 0.30148400148954707, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:33,857 [classy] Computing new state
2023-07-02 10:33:33,857 [classy] Setting parameters: {'Omega_m': 0.30148400148954707, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:33,901 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.60476320536847}
2023-07-02 10:33:33,902 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:33,903 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00782998
2023-07-02 10:33:33,903 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:33,903 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:33,923 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.26544
2023-07-02 10:33:33,923 [model] Computed derived parameters: {}
2023-07-02 10:33:33,923 [mcmc] New sample, #105:
Omega_m:0.3156535, b1:0.5105119
2023-07-02 10:33:33,923 [model] Posterior to be computed for parameters {'Omega_m': 0.30148400148954707, 'b1': 0.6548111534981944}
2023-07-02 10:33:33,923 [prior] Evaluating prior at array([0.301484 , 0.65481115])
2023-07-02 10:33:33,923 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:33,923 [model] Got input parameters: {'Omega_m': 0.30148400148954707, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6548111534981944, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:33,923 [classy] Got parameters {'Omega_m': 0.30148400148954707, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:33,923 [classy] Re-using computed results
2023-07-02 10:33:33,923 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.60476320536847}
2023-07-02 10:33:33,923 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:33,923 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6548111534981944, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:33,923 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:33,943 [fs_likelihood.fslikelihood] Computed log-likelihood = -49.1438
2023-07-02 10:33:33,943 [model] Computed derived parameters: {}
2023-07-02 10:33:33,944 [model] Posterior to be computed for parameters {'Omega_m': 0.32427377016611164, 'b1': 0.510511879507605}
2023-07-02 10:33:33,944 [prior] Evaluating prior at array([0.32427377, 0.51051188])
2023-07-02 10:33:33,944 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:33,944 [model] Got input parameters: {'Omega_m': 0.32427377016611164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:33,944 [classy] Got parameters {'Omega_m': 0.32427377016611164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:33,944 [classy] Computing new state
2023-07-02 10:33:33,944 [classy] Setting parameters: {'Omega_m': 0.32427377016611164, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:33,988 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.86481076925278}
2023-07-02 10:33:33,988 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:33,990 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00848171
2023-07-02 10:33:33,990 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:33,990 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:34,009 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.445387
2023-07-02 10:33:34,009 [model] Computed derived parameters: {}
2023-07-02 10:33:34,010 [mcmc] New sample, #106:
Omega_m:0.301484, b1:0.5105119
2023-07-02 10:33:34,010 [model] Posterior to be computed for parameters {'Omega_m': 0.32427377016611164, 'b1': 1.3676556980386505}
2023-07-02 10:33:34,010 [prior] Evaluating prior at array([0.32427377, 1.3676557 ])
2023-07-02 10:33:34,010 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:34,010 [model] Got input parameters: {'Omega_m': 0.32427377016611164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.3676556980386505, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:34,010 [classy] Got parameters {'Omega_m': 0.32427377016611164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:34,010 [classy] Re-using computed results
2023-07-02 10:33:34,010 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.86481076925278}
2023-07-02 10:33:34,010 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:34,010 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.3676556980386505, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:34,010 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:34,029 [fs_likelihood.fslikelihood] Computed log-likelihood = -4618.11
2023-07-02 10:33:34,030 [model] Computed derived parameters: {}
2023-07-02 10:33:34,030 [model] Posterior to be computed for parameters {'Omega_m': 0.3149906783622375, 'b1': 0.510511879507605}
2023-07-02 10:33:34,030 [prior] Evaluating prior at array([0.31499068, 0.51051188])
2023-07-02 10:33:34,030 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:34,030 [model] Got input parameters: {'Omega_m': 0.3149906783622375, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:34,030 [classy] Got parameters {'Omega_m': 0.3149906783622375, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:34,030 [classy] Computing new state
2023-07-02 10:33:34,030 [classy] Setting parameters: {'Omega_m': 0.3149906783622375, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:34,074 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.95955644070628}
2023-07-02 10:33:34,074 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:34,075 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000585428
2023-07-02 10:33:34,075 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:34,076 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:34,095 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.64609
2023-07-02 10:33:34,095 [model] Computed derived parameters: {}
2023-07-02 10:33:34,095 [mcmc] New sample, #107:
Omega_m:0.3242738, b1:0.5105119
2023-07-02 10:33:34,096 [model] Posterior to be computed for parameters {'Omega_m': 0.3149906783622375, 'b1': 0.5715477115202471}
2023-07-02 10:33:34,096 [prior] Evaluating prior at array([0.31499068, 0.57154771])
2023-07-02 10:33:34,096 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:34,096 [model] Got input parameters: {'Omega_m': 0.3149906783622375, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5715477115202471, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:34,096 [classy] Got parameters {'Omega_m': 0.3149906783622375, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:34,096 [classy] Re-using computed results
2023-07-02 10:33:34,096 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.95955644070628}
2023-07-02 10:33:34,096 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:34,096 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5715477115202471, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:34,096 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:34,115 [fs_likelihood.fslikelihood] Computed log-likelihood = -11.7343
2023-07-02 10:33:34,115 [model] Computed derived parameters: {}
2023-07-02 10:33:34,115 [model] Posterior to be computed for parameters {'Omega_m': 0.30856513789660195, 'b1': 0.510511879507605}
2023-07-02 10:33:34,115 [prior] Evaluating prior at array([0.30856514, 0.51051188])
2023-07-02 10:33:34,115 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:34,116 [model] Got input parameters: {'Omega_m': 0.30856513789660195, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:34,116 [classy] Got parameters {'Omega_m': 0.30856513789660195, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:34,116 [classy] Computing new state
2023-07-02 10:33:34,116 [classy] Setting parameters: {'Omega_m': 0.30856513789660195, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:34,162 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.7343185492424}
2023-07-02 10:33:34,162 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:34,164 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00115343
2023-07-02 10:33:34,164 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:34,164 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:34,184 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.66666
2023-07-02 10:33:34,184 [model] Computed derived parameters: {}
2023-07-02 10:33:34,184 [mcmc] New sample, #108:
Omega_m:0.3149907, b1:0.5105119
2023-07-02 10:33:34,184 [model] Posterior to be computed for parameters {'Omega_m': 0.30856513789660195, 'b1': 1.8662402570490157}
2023-07-02 10:33:34,184 [prior] Evaluating prior at array([0.30856514, 1.86624026])
2023-07-02 10:33:34,184 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:34,184 [model] Got input parameters: {'Omega_m': 0.30856513789660195, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.8662402570490157, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:34,184 [classy] Got parameters {'Omega_m': 0.30856513789660195, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:34,184 [classy] Re-using computed results
2023-07-02 10:33:34,184 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.7343185492424}
2023-07-02 10:33:34,184 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:34,184 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.8662402570490157, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:34,184 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:34,204 [fs_likelihood.fslikelihood] Computed log-likelihood = -14663.7
2023-07-02 10:33:34,204 [model] Computed derived parameters: {}
2023-07-02 10:33:34,204 [model] Posterior to be computed for parameters {'Omega_m': 0.3272101788752867, 'b1': 0.510511879507605}
2023-07-02 10:33:34,204 [prior] Evaluating prior at array([0.32721018, 0.51051188])
2023-07-02 10:33:34,204 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:34,204 [model] Got input parameters: {'Omega_m': 0.3272101788752867, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:34,204 [classy] Got parameters {'Omega_m': 0.3272101788752867, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:34,204 [classy] Computing new state
2023-07-02 10:33:34,204 [classy] Setting parameters: {'Omega_m': 0.3272101788752867, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:34,248 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.5243403707738}
2023-07-02 10:33:34,249 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:34,250 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0130284
2023-07-02 10:33:34,250 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:34,250 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:34,270 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.784926
2023-07-02 10:33:34,270 [model] Computed derived parameters: {}
2023-07-02 10:33:34,270 [model] Posterior to be computed for parameters {'Omega_m': 0.30856513789660195, 'b1': 1.3276045244962118}
2023-07-02 10:33:34,270 [prior] Evaluating prior at array([0.30856514, 1.32760452])
2023-07-02 10:33:34,270 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:34,270 [model] Got input parameters: {'Omega_m': 0.30856513789660195, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.3276045244962118, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:34,270 [classy] Got parameters {'Omega_m': 0.30856513789660195, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:34,270 [classy] Re-using computed results
2023-07-02 10:33:34,270 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.7343185492424}
2023-07-02 10:33:34,270 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:34,270 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.3276045244962118, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:34,270 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:34,291 [fs_likelihood.fslikelihood] Computed log-likelihood = -3640.44
2023-07-02 10:33:34,291 [model] Computed derived parameters: {}
2023-07-02 10:33:34,291 [model] Posterior to be computed for parameters {'Omega_m': 0.3015858455640156, 'b1': 0.510511879507605}
2023-07-02 10:33:34,291 [prior] Evaluating prior at array([0.30158585, 0.51051188])
2023-07-02 10:33:34,291 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:34,291 [model] Got input parameters: {'Omega_m': 0.3015858455640156, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:34,291 [classy] Got parameters {'Omega_m': 0.3015858455640156, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:34,291 [classy] Computing new state
2023-07-02 10:33:34,291 [classy] Setting parameters: {'Omega_m': 0.3015858455640156, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:34,336 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.59211816124062}
2023-07-02 10:33:34,336 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:34,338 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00768748
2023-07-02 10:33:34,338 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:34,338 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:34,357 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.29618
2023-07-02 10:33:34,358 [model] Computed derived parameters: {}
2023-07-02 10:33:34,358 [mcmc] New sample, #109:
Omega_m:0.3085651, b1:0.5105119
2023-07-02 10:33:34,358 [model] Posterior to be computed for parameters {'Omega_m': 0.3015858455640156, 'b1': 0.37105933901204513}
2023-07-02 10:33:34,358 [prior] Evaluating prior at array([0.30158585, 0.37105934])
2023-07-02 10:33:34,358 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:34,358 [model] Got input parameters: {'Omega_m': 0.3015858455640156, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.37105933901204513, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:34,358 [classy] Got parameters {'Omega_m': 0.3015858455640156, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:34,358 [classy] Re-using computed results
2023-07-02 10:33:34,358 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.59211816124062}
2023-07-02 10:33:34,358 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:34,358 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.37105933901204513, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:34,358 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:34,377 [fs_likelihood.fslikelihood] Computed log-likelihood = -51.8586
2023-07-02 10:33:34,377 [model] Computed derived parameters: {}
2023-07-02 10:33:34,378 [model] Posterior to be computed for parameters {'Omega_m': 0.30640491918876894, 'b1': 0.510511879507605}
2023-07-02 10:33:34,378 [prior] Evaluating prior at array([0.30640492, 0.51051188])
2023-07-02 10:33:34,378 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:34,378 [model] Got input parameters: {'Omega_m': 0.30640491918876894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:34,378 [classy] Got parameters {'Omega_m': 0.30640491918876894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:34,378 [classy] Computing new state
2023-07-02 10:33:34,378 [classy] Setting parameters: {'Omega_m': 0.30640491918876894, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:34,422 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.99798733247482}
2023-07-02 10:33:34,422 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:34,424 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00250335
2023-07-02 10:33:34,424 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:34,424 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:34,444 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.39746
2023-07-02 10:33:34,444 [model] Computed derived parameters: {}
2023-07-02 10:33:34,444 [mcmc] New sample, #110:
Omega_m:0.3015858, b1:0.5105119
2023-07-02 10:33:34,444 [model] Posterior to be computed for parameters {'Omega_m': 0.30640491918876894, 'b1': 0.7862924022000481}
2023-07-02 10:33:34,444 [prior] Evaluating prior at array([0.30640492, 0.7862924 ])
2023-07-02 10:33:34,444 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:34,444 [model] Got input parameters: {'Omega_m': 0.30640491918876894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.7862924022000481, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:34,445 [classy] Got parameters {'Omega_m': 0.30640491918876894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:34,445 [classy] Re-using computed results
2023-07-02 10:33:34,445 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.99798733247482}
2023-07-02 10:33:34,445 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:34,445 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.7862924022000481, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:34,445 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:34,464 [fs_likelihood.fslikelihood] Computed log-likelihood = -250.508
2023-07-02 10:33:34,464 [model] Computed derived parameters: {}
2023-07-02 10:33:34,464 [model] Posterior to be computed for parameters {'Omega_m': 0.32403621479825445, 'b1': 0.510511879507605}
2023-07-02 10:33:34,464 [prior] Evaluating prior at array([0.32403621, 0.51051188])
2023-07-02 10:33:34,465 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:34,465 [model] Got input parameters: {'Omega_m': 0.32403621479825445, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:34,465 [classy] Got parameters {'Omega_m': 0.32403621479825445, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:34,465 [classy] Computing new state
2023-07-02 10:33:34,465 [classy] Setting parameters: {'Omega_m': 0.32403621479825445, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:34,510 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.89247512917976}
2023-07-02 10:33:34,510 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:34,512 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.008156
2023-07-02 10:33:34,512 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:34,512 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:34,532 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.533694
2023-07-02 10:33:34,532 [model] Computed derived parameters: {}
2023-07-02 10:33:34,533 [model] Posterior to be computed for parameters {'Omega_m': 0.30640491918876894, 'b1': -0.011921170393763059}
2023-07-02 10:33:34,533 [prior] Evaluating prior at array([ 0.30640492, -0.01192117])
2023-07-02 10:33:34,533 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:34,533 [model] Posterior to be computed for parameters {'Omega_m': 0.2873490517865083, 'b1': 0.510511879507605}
2023-07-02 10:33:34,533 [prior] Evaluating prior at array([0.28734905, 0.51051188])
2023-07-02 10:33:34,533 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:34,533 [model] Got input parameters: {'Omega_m': 0.2873490517865083, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:34,533 [classy] Got parameters {'Omega_m': 0.2873490517865083, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:34,533 [classy] Computing new state
2023-07-02 10:33:34,533 [classy] Setting parameters: {'Omega_m': 0.2873490517865083, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:34,579 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.3972400177031}
2023-07-02 10:33:34,579 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:34,581 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0415063
2023-07-02 10:33:34,581 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:34,581 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:34,602 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.99622
2023-07-02 10:33:34,602 [model] Computed derived parameters: {}
2023-07-02 10:33:34,602 [model] Posterior to be computed for parameters {'Omega_m': 0.30640491918876894, 'b1': 1.2527258787121205}
2023-07-02 10:33:34,602 [prior] Evaluating prior at array([0.30640492, 1.25272588])
2023-07-02 10:33:34,602 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:34,602 [model] Got input parameters: {'Omega_m': 0.30640491918876894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.2527258787121205, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:34,602 [classy] Got parameters {'Omega_m': 0.30640491918876894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:34,602 [classy] Re-using computed results
2023-07-02 10:33:34,602 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.99798733247482}
2023-07-02 10:33:34,603 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:34,603 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.2527258787121205, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:34,603 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:34,623 [fs_likelihood.fslikelihood] Computed log-likelihood = -2785.61
2023-07-02 10:33:34,623 [model] Computed derived parameters: {}
2023-07-02 10:33:34,623 [model] Posterior to be computed for parameters {'Omega_m': 0.2960827374482946, 'b1': 0.510511879507605}
2023-07-02 10:33:34,623 [prior] Evaluating prior at array([0.29608274, 0.51051188])
2023-07-02 10:33:34,623 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:34,623 [model] Got input parameters: {'Omega_m': 0.2960827374482946, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:34,623 [classy] Got parameters {'Omega_m': 0.2960827374482946, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:34,623 [classy] Computing new state
2023-07-02 10:33:34,623 [classy] Setting parameters: {'Omega_m': 0.2960827374482946, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:34,668 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.28090295650202}
2023-07-02 10:33:34,668 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:34,670 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0173962
2023-07-02 10:33:34,670 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:34,670 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:34,690 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.807101
2023-07-02 10:33:34,690 [model] Computed derived parameters: {}
2023-07-02 10:33:34,690 [model] Posterior to be computed for parameters {'Omega_m': 0.30640491918876894, 'b1': -0.1418431505032861}
2023-07-02 10:33:34,690 [prior] Evaluating prior at array([ 0.30640492, -0.14184315])
2023-07-02 10:33:34,690 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:34,690 [model] Posterior to be computed for parameters {'Omega_m': 0.3214539709503879, 'b1': 0.510511879507605}
2023-07-02 10:33:34,690 [prior] Evaluating prior at array([0.32145397, 0.51051188])
2023-07-02 10:33:34,690 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:34,690 [model] Got input parameters: {'Omega_m': 0.3214539709503879, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:34,690 [classy] Got parameters {'Omega_m': 0.3214539709503879, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:34,690 [classy] Computing new state
2023-07-02 10:33:34,690 [classy] Setting parameters: {'Omega_m': 0.3214539709503879, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:34,734 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.19436419033698}
2023-07-02 10:33:34,734 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:34,736 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00502786
2023-07-02 10:33:34,736 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:34,736 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:34,756 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.3852
2023-07-02 10:33:34,756 [model] Computed derived parameters: {}
2023-07-02 10:33:34,756 [model] Posterior to be computed for parameters {'Omega_m': 0.30640491918876894, 'b1': 1.8165945394336296}
2023-07-02 10:33:34,756 [prior] Evaluating prior at array([0.30640492, 1.81659454])
2023-07-02 10:33:34,757 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:34,757 [model] Got input parameters: {'Omega_m': 0.30640491918876894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.8165945394336296, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:34,757 [classy] Got parameters {'Omega_m': 0.30640491918876894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:34,757 [classy] Re-using computed results
2023-07-02 10:33:34,757 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.99798733247482}
2023-07-02 10:33:34,757 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:34,757 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.8165945394336296, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:34,757 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:34,776 [fs_likelihood.fslikelihood] Computed log-likelihood = -13009
2023-07-02 10:33:34,776 [model] Computed derived parameters: {}
2023-07-02 10:33:34,776 [model] Posterior to be computed for parameters {'Omega_m': 0.3028093078409774, 'b1': 0.510511879507605}
2023-07-02 10:33:34,776 [prior] Evaluating prior at array([0.30280931, 0.51051188])
2023-07-02 10:33:34,776 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:34,776 [model] Got input parameters: {'Omega_m': 0.3028093078409774, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:34,776 [classy] Got parameters {'Omega_m': 0.3028093078409774, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:34,777 [classy] Computing new state
2023-07-02 10:33:34,777 [classy] Setting parameters: {'Omega_m': 0.3028093078409774, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:34,820 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.44049426996006}
2023-07-02 10:33:34,820 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:34,822 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00608301
2023-07-02 10:33:34,822 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:34,822 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:34,843 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.64126
2023-07-02 10:33:34,843 [model] Computed derived parameters: {}
2023-07-02 10:33:34,843 [model] Posterior to be computed for parameters {'Omega_m': 0.30640491918876894, 'b1': 0.265638383221054}
2023-07-02 10:33:34,843 [prior] Evaluating prior at array([0.30640492, 0.26563838])
2023-07-02 10:33:34,843 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:34,843 [model] Got input parameters: {'Omega_m': 0.30640491918876894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.265638383221054, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:34,843 [classy] Got parameters {'Omega_m': 0.30640491918876894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:34,843 [classy] Re-using computed results
2023-07-02 10:33:34,843 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.99798733247482}
2023-07-02 10:33:34,843 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:34,843 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.265638383221054, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:34,843 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:34,863 [fs_likelihood.fslikelihood] Computed log-likelihood = -126.743
2023-07-02 10:33:34,863 [model] Computed derived parameters: {}
2023-07-02 10:33:34,863 [model] Posterior to be computed for parameters {'Omega_m': 0.2886325961293404, 'b1': 0.510511879507605}
2023-07-02 10:33:34,863 [prior] Evaluating prior at array([0.2886326 , 0.51051188])
2023-07-02 10:33:34,863 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:34,863 [model] Got input parameters: {'Omega_m': 0.2886325961293404, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:34,863 [classy] Got parameters {'Omega_m': 0.2886325961293404, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:34,863 [classy] Computing new state
2023-07-02 10:33:34,863 [classy] Setting parameters: {'Omega_m': 0.2886325961293404, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:34,907 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.23135530095783}
2023-07-02 10:33:34,907 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:34,909 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0372716
2023-07-02 10:33:34,909 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:34,909 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:34,928 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.09124
2023-07-02 10:33:34,928 [model] Computed derived parameters: {}
2023-07-02 10:33:34,928 [model] Posterior to be computed for parameters {'Omega_m': 0.30640491918876894, 'b1': 0.7013760088753697}
2023-07-02 10:33:34,928 [prior] Evaluating prior at array([0.30640492, 0.70137601])
2023-07-02 10:33:34,929 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:34,929 [model] Got input parameters: {'Omega_m': 0.30640491918876894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.7013760088753697, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:34,929 [classy] Got parameters {'Omega_m': 0.30640491918876894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:34,929 [classy] Re-using computed results
2023-07-02 10:33:34,929 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.99798733247482}
2023-07-02 10:33:34,929 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:34,929 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.7013760088753697, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:34,929 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:34,949 [fs_likelihood.fslikelihood] Computed log-likelihood = -107.528
2023-07-02 10:33:34,949 [model] Computed derived parameters: {}
2023-07-02 10:33:34,950 [model] Posterior to be computed for parameters {'Omega_m': 0.2958630388693177, 'b1': 0.510511879507605}
2023-07-02 10:33:34,950 [prior] Evaluating prior at array([0.29586304, 0.51051188])
2023-07-02 10:33:34,950 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:34,950 [model] Got input parameters: {'Omega_m': 0.2958630388693177, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:34,950 [classy] Got parameters {'Omega_m': 0.2958630388693177, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:34,950 [classy] Computing new state
2023-07-02 10:33:34,950 [classy] Setting parameters: {'Omega_m': 0.2958630388693177, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:34,994 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.30863171003898}
2023-07-02 10:33:34,994 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:34,996 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0178699
2023-07-02 10:33:34,996 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:34,996 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:35,015 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.909787
2023-07-02 10:33:35,015 [model] Computed derived parameters: {}
2023-07-02 10:33:35,016 [model] Posterior to be computed for parameters {'Omega_m': 0.30640491918876894, 'b1': 2.189496972879572}
2023-07-02 10:33:35,016 [prior] Evaluating prior at array([0.30640492, 2.18949697])
2023-07-02 10:33:35,016 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:35,016 [model] Got input parameters: {'Omega_m': 0.30640491918876894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 2.189496972879572, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:35,016 [classy] Got parameters {'Omega_m': 0.30640491918876894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:35,016 [classy] Re-using computed results
2023-07-02 10:33:35,016 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.99798733247482}
2023-07-02 10:33:35,016 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:35,016 [fs_likelihood.fslikelihood] Got parameters {'b1': 2.189496972879572, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:35,016 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:35,036 [fs_likelihood.fslikelihood] Computed log-likelihood = -27166.8
2023-07-02 10:33:35,036 [model] Computed derived parameters: {}
2023-07-02 10:33:35,036 [model] Posterior to be computed for parameters {'Omega_m': 0.31210423397057946, 'b1': 0.510511879507605}
2023-07-02 10:33:35,036 [prior] Evaluating prior at array([0.31210423, 0.51051188])
2023-07-02 10:33:35,036 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:35,036 [model] Got input parameters: {'Omega_m': 0.31210423397057946, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:35,036 [classy] Got parameters {'Omega_m': 0.31210423397057946, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:35,036 [classy] Computing new state
2023-07-02 10:33:35,036 [classy] Setting parameters: {'Omega_m': 0.31210423397057946, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:35,080 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.30584766721276}
2023-07-02 10:33:35,080 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:35,082 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000211219
2023-07-02 10:33:35,082 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:35,082 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:35,102 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.80742
2023-07-02 10:33:35,102 [model] Computed derived parameters: {}
2023-07-02 10:33:35,102 [mcmc] New sample, #111:
Omega_m:0.3064049, b1:0.5105119
2023-07-02 10:33:35,102 [model] Posterior to be computed for parameters {'Omega_m': 0.31210423397057946, 'b1': 1.3012550945458492}
2023-07-02 10:33:35,102 [prior] Evaluating prior at array([0.31210423, 1.30125509])
2023-07-02 10:33:35,102 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:35,102 [model] Got input parameters: {'Omega_m': 0.31210423397057946, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.3012550945458492, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:35,102 [classy] Got parameters {'Omega_m': 0.31210423397057946, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:35,102 [classy] Re-using computed results
2023-07-02 10:33:35,102 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.30584766721276}
2023-07-02 10:33:35,102 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:35,103 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.3012550945458492, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:35,103 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:35,125 [fs_likelihood.fslikelihood] Computed log-likelihood = -3430.64
2023-07-02 10:33:35,125 [model] Computed derived parameters: {}
2023-07-02 10:33:35,125 [model] Posterior to be computed for parameters {'Omega_m': 0.3099244840089716, 'b1': 0.510511879507605}
2023-07-02 10:33:35,125 [prior] Evaluating prior at array([0.30992448, 0.51051188])
2023-07-02 10:33:35,125 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:35,125 [model] Got input parameters: {'Omega_m': 0.3099244840089716, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:35,125 [classy] Got parameters {'Omega_m': 0.3099244840089716, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:35,126 [classy] Computing new state
2023-07-02 10:33:35,126 [classy] Setting parameters: {'Omega_m': 0.3099244840089716, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:35,171 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.5692376472202}
2023-07-02 10:33:35,171 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:35,173 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000606703
2023-07-02 10:33:35,173 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:35,173 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:35,192 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.76484
2023-07-02 10:33:35,192 [model] Computed derived parameters: {}
2023-07-02 10:33:35,192 [mcmc] New sample, #112:
Omega_m:0.3121042, b1:0.5105119
2023-07-02 10:33:35,193 [model] Posterior to be computed for parameters {'Omega_m': 0.3099244840089716, 'b1': 0.9563985836392042}
2023-07-02 10:33:35,193 [prior] Evaluating prior at array([0.30992448, 0.95639858])
2023-07-02 10:33:35,193 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:35,193 [model] Got input parameters: {'Omega_m': 0.3099244840089716, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.9563985836392042, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:35,193 [classy] Got parameters {'Omega_m': 0.3099244840089716, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:35,193 [classy] Re-using computed results
2023-07-02 10:33:35,193 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.5692376472202}
2023-07-02 10:33:35,193 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:35,193 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.9563985836392042, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:35,193 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:35,213 [fs_likelihood.fslikelihood] Computed log-likelihood = -809.324
2023-07-02 10:33:35,213 [model] Computed derived parameters: {}
2023-07-02 10:33:35,213 [model] Posterior to be computed for parameters {'Omega_m': 0.2631472327268247, 'b1': 0.510511879507605}
2023-07-02 10:33:35,213 [prior] Evaluating prior at array([0.26314723, 0.51051188])
2023-07-02 10:33:35,213 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:35,213 [model] Got input parameters: {'Omega_m': 0.2631472327268247, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:35,213 [classy] Got parameters {'Omega_m': 0.2631472327268247, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:35,213 [classy] Computing new state
2023-07-02 10:33:35,213 [classy] Setting parameters: {'Omega_m': 0.2631472327268247, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:35,257 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.65060781565}
2023-07-02 10:33:35,257 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:35,259 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.170018
2023-07-02 10:33:35,259 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:35,259 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:35,278 [fs_likelihood.fslikelihood] Computed log-likelihood = -32.2427
2023-07-02 10:33:35,279 [model] Computed derived parameters: {}
2023-07-02 10:33:35,279 [model] Posterior to be computed for parameters {'Omega_m': 0.3099244840089716, 'b1': 0.849369882136066}
2023-07-02 10:33:35,279 [prior] Evaluating prior at array([0.30992448, 0.84936988])
2023-07-02 10:33:35,279 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:35,279 [model] Got input parameters: {'Omega_m': 0.3099244840089716, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.849369882136066, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:35,279 [classy] Got parameters {'Omega_m': 0.3099244840089716, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:35,279 [classy] Re-using computed results
2023-07-02 10:33:35,279 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.5692376472202}
2023-07-02 10:33:35,279 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:35,279 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.849369882136066, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:35,279 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:35,299 [fs_likelihood.fslikelihood] Computed log-likelihood = -424.693
2023-07-02 10:33:35,299 [model] Computed derived parameters: {}
2023-07-02 10:33:35,299 [model] Posterior to be computed for parameters {'Omega_m': 0.283507249741276, 'b1': 0.510511879507605}
2023-07-02 10:33:35,299 [prior] Evaluating prior at array([0.28350725, 0.51051188])
2023-07-02 10:33:35,299 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:35,299 [model] Got input parameters: {'Omega_m': 0.283507249741276, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:35,299 [classy] Got parameters {'Omega_m': 0.283507249741276, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:35,299 [classy] Computing new state
2023-07-02 10:33:35,299 [classy] Setting parameters: {'Omega_m': 0.283507249741276, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:35,343 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.89765195794948}
2023-07-02 10:33:35,343 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:35,345 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0556552
2023-07-02 10:33:35,345 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:35,345 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:35,365 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.99809
2023-07-02 10:33:35,365 [model] Computed derived parameters: {}
2023-07-02 10:33:35,365 [model] Posterior to be computed for parameters {'Omega_m': 0.3099244840089716, 'b1': 1.3533112392523106}
2023-07-02 10:33:35,365 [prior] Evaluating prior at array([0.30992448, 1.35331124])
2023-07-02 10:33:35,366 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:35,366 [model] Got input parameters: {'Omega_m': 0.3099244840089716, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.3533112392523106, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:35,366 [classy] Got parameters {'Omega_m': 0.3099244840089716, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:35,366 [classy] Re-using computed results
2023-07-02 10:33:35,366 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.5692376472202}
2023-07-02 10:33:35,366 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:35,366 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.3533112392523106, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:35,366 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:35,385 [fs_likelihood.fslikelihood] Computed log-likelihood = -3989.43
2023-07-02 10:33:35,385 [model] Computed derived parameters: {}
2023-07-02 10:33:35,385 [model] Posterior to be computed for parameters {'Omega_m': 0.32716443271861545, 'b1': 0.510511879507605}
2023-07-02 10:33:35,385 [prior] Evaluating prior at array([0.32716443, 0.51051188])
2023-07-02 10:33:35,385 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:35,386 [model] Got input parameters: {'Omega_m': 0.32716443271861545, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:35,386 [classy] Got parameters {'Omega_m': 0.32716443271861545, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:35,386 [classy] Computing new state
2023-07-02 10:33:35,386 [classy] Setting parameters: {'Omega_m': 0.32716443271861545, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:35,430 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.52962483448624}
2023-07-02 10:33:35,430 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:35,431 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0129502
2023-07-02 10:33:35,432 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:35,432 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:35,451 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.76379
2023-07-02 10:33:35,451 [model] Computed derived parameters: {}
2023-07-02 10:33:35,452 [model] Posterior to be computed for parameters {'Omega_m': 0.3099244840089716, 'b1': 0.9022045435649878}
2023-07-02 10:33:35,452 [prior] Evaluating prior at array([0.30992448, 0.90220454])
2023-07-02 10:33:35,452 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:35,452 [model] Got input parameters: {'Omega_m': 0.3099244840089716, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.9022045435649878, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:35,452 [classy] Got parameters {'Omega_m': 0.3099244840089716, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:35,452 [classy] Re-using computed results
2023-07-02 10:33:35,452 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.5692376472202}
2023-07-02 10:33:35,452 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:35,452 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.9022045435649878, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:35,452 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:35,471 [fs_likelihood.fslikelihood] Computed log-likelihood = -595.351
2023-07-02 10:33:35,471 [model] Computed derived parameters: {}
2023-07-02 10:33:35,472 [model] Posterior to be computed for parameters {'Omega_m': 0.31314118591289486, 'b1': 0.510511879507605}
2023-07-02 10:33:35,472 [prior] Evaluating prior at array([0.31314119, 0.51051188])
2023-07-02 10:33:35,472 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:35,472 [model] Got input parameters: {'Omega_m': 0.31314118591289486, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:35,472 [classy] Got parameters {'Omega_m': 0.31314118591289486, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:35,472 [classy] Computing new state
2023-07-02 10:33:35,472 [classy] Setting parameters: {'Omega_m': 0.31314118591289486, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:35,515 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.18111680186226}
2023-07-02 10:33:35,516 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:35,517 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00022883
2023-07-02 10:33:35,517 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:35,517 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:35,537 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.77801
2023-07-02 10:33:35,537 [model] Computed derived parameters: {}
2023-07-02 10:33:35,537 [mcmc] New sample, #113:
Omega_m:0.3099245, b1:0.5105119
2023-07-02 10:33:35,537 [model] Posterior to be computed for parameters {'Omega_m': 0.31314118591289486, 'b1': -1.2613782238027467}
2023-07-02 10:33:35,537 [prior] Evaluating prior at array([ 0.31314119, -1.26137822])
2023-07-02 10:33:35,537 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:35,537 [model] Posterior to be computed for parameters {'Omega_m': 0.34673835194328295, 'b1': 0.510511879507605}
2023-07-02 10:33:35,537 [prior] Evaluating prior at array([0.34673835, 0.51051188])
2023-07-02 10:33:35,537 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:35,538 [model] Got input parameters: {'Omega_m': 0.34673835194328295, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:35,538 [classy] Got parameters {'Omega_m': 0.34673835194328295, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:35,538 [classy] Computing new state
2023-07-02 10:33:35,538 [classy] Setting parameters: {'Omega_m': 0.34673835194328295, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:35,581 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.32802129322866}
2023-07-02 10:33:35,582 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:35,583 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0664531
2023-07-02 10:33:35,583 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:35,583 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:35,603 [fs_likelihood.fslikelihood] Computed log-likelihood = -15.498
2023-07-02 10:33:35,603 [model] Computed derived parameters: {}
2023-07-02 10:33:35,603 [model] Posterior to be computed for parameters {'Omega_m': 0.31314118591289486, 'b1': 0.4270051335449099}
2023-07-02 10:33:35,603 [prior] Evaluating prior at array([0.31314119, 0.42700513])
2023-07-02 10:33:35,603 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:35,603 [model] Got input parameters: {'Omega_m': 0.31314118591289486, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4270051335449099, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:35,603 [classy] Got parameters {'Omega_m': 0.31314118591289486, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:35,603 [classy] Re-using computed results
2023-07-02 10:33:35,603 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.18111680186226}
2023-07-02 10:33:35,604 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:35,604 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4270051335449099, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:35,604 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:35,623 [fs_likelihood.fslikelihood] Computed log-likelihood = -11.751
2023-07-02 10:33:35,623 [model] Computed derived parameters: {}
2023-07-02 10:33:35,623 [model] Posterior to be computed for parameters {'Omega_m': 0.3199550765255515, 'b1': 0.510511879507605}
2023-07-02 10:33:35,623 [prior] Evaluating prior at array([0.31995508, 0.51051188])
2023-07-02 10:33:35,623 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:35,623 [model] Got input parameters: {'Omega_m': 0.3199550765255515, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:35,623 [classy] Got parameters {'Omega_m': 0.3199550765255515, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:35,623 [classy] Computing new state
2023-07-02 10:33:35,623 [classy] Setting parameters: {'Omega_m': 0.3199550765255515, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:35,667 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.37059227133813}
2023-07-02 10:33:35,667 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:35,669 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00356222
2023-07-02 10:33:35,669 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:35,669 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:35,689 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.78839
2023-07-02 10:33:35,689 [model] Computed derived parameters: {}
2023-07-02 10:33:35,689 [mcmc] New sample, #114:
Omega_m:0.3131412, b1:0.5105119
2023-07-02 10:33:35,689 [model] Posterior to be computed for parameters {'Omega_m': 0.3199550765255515, 'b1': 0.6008238436729927}
2023-07-02 10:33:35,689 [prior] Evaluating prior at array([0.31995508, 0.60082384])
2023-07-02 10:33:35,689 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:35,689 [model] Got input parameters: {'Omega_m': 0.3199550765255515, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6008238436729927, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:35,689 [classy] Got parameters {'Omega_m': 0.3199550765255515, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:35,689 [classy] Re-using computed results
2023-07-02 10:33:35,689 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.37059227133813}
2023-07-02 10:33:35,689 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:35,689 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6008238436729927, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:35,689 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:35,709 [fs_likelihood.fslikelihood] Computed log-likelihood = -33.3702
2023-07-02 10:33:35,709 [model] Computed derived parameters: {}
2023-07-02 10:33:35,709 [model] Posterior to be computed for parameters {'Omega_m': 0.3184991828302559, 'b1': 0.510511879507605}
2023-07-02 10:33:35,709 [prior] Evaluating prior at array([0.31849918, 0.51051188])
2023-07-02 10:33:35,709 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:35,710 [model] Got input parameters: {'Omega_m': 0.3184991828302559, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:35,710 [classy] Got parameters {'Omega_m': 0.3184991828302559, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:35,710 [classy] Computing new state
2023-07-02 10:33:35,710 [classy] Setting parameters: {'Omega_m': 0.3184991828302559, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:35,753 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.54246953078496}
2023-07-02 10:33:35,753 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:35,755 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00238819
2023-07-02 10:33:35,755 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:35,755 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:35,775 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.11597
2023-07-02 10:33:35,775 [model] Computed derived parameters: {}
2023-07-02 10:33:35,775 [mcmc] New sample, #115:
Omega_m:0.3199551, b1:0.5105119
2023-07-02 10:33:35,775 [model] Posterior to be computed for parameters {'Omega_m': 0.3184991828302559, 'b1': -0.3297785535581541}
2023-07-02 10:33:35,775 [prior] Evaluating prior at array([ 0.31849918, -0.32977855])
2023-07-02 10:33:35,775 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:35,775 [model] Posterior to be computed for parameters {'Omega_m': 0.31022168957578045, 'b1': 0.510511879507605}
2023-07-02 10:33:35,775 [prior] Evaluating prior at array([0.31022169, 0.51051188])
2023-07-02 10:33:35,775 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:35,776 [model] Got input parameters: {'Omega_m': 0.31022168957578045, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:35,776 [classy] Got parameters {'Omega_m': 0.31022168957578045, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:35,776 [classy] Computing new state
2023-07-02 10:33:35,776 [classy] Setting parameters: {'Omega_m': 0.31022168957578045, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:35,819 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.53322897143858}
2023-07-02 10:33:35,819 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:35,821 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000518019
2023-07-02 10:33:35,821 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:35,821 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:35,841 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.77897
2023-07-02 10:33:35,841 [model] Computed derived parameters: {}
2023-07-02 10:33:35,841 [mcmc] New sample, #116:
Omega_m:0.3184992, b1:0.5105119
2023-07-02 10:33:35,841 [model] Posterior to be computed for parameters {'Omega_m': 0.31022168957578045, 'b1': 2.3113839673775423}
2023-07-02 10:33:35,841 [prior] Evaluating prior at array([0.31022169, 2.31138397])
2023-07-02 10:33:35,841 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:35,841 [model] Got input parameters: {'Omega_m': 0.31022168957578045, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 2.3113839673775423, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:35,841 [classy] Got parameters {'Omega_m': 0.31022168957578045, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:35,841 [classy] Re-using computed results
2023-07-02 10:33:35,841 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.53322897143858}
2023-07-02 10:33:35,841 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:35,842 [fs_likelihood.fslikelihood] Got parameters {'b1': 2.3113839673775423, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:35,842 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:35,861 [fs_likelihood.fslikelihood] Computed log-likelihood = -34233.8
2023-07-02 10:33:35,862 [model] Computed derived parameters: {}
2023-07-02 10:33:35,862 [model] Posterior to be computed for parameters {'Omega_m': 0.2991125986817331, 'b1': 0.510511879507605}
2023-07-02 10:33:35,862 [prior] Evaluating prior at array([0.2991126 , 0.51051188])
2023-07-02 10:33:35,862 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:35,862 [model] Got input parameters: {'Omega_m': 0.2991125986817331, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:35,862 [classy] Got parameters {'Omega_m': 0.2991125986817331, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:35,862 [classy] Computing new state
2023-07-02 10:33:35,862 [classy] Setting parameters: {'Omega_m': 0.2991125986817331, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:35,906 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.90029665267363}
2023-07-02 10:33:35,906 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:35,908 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0115417
2023-07-02 10:33:35,908 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510511879507605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:35,908 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:35,927 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.462469
2023-07-02 10:33:35,927 [model] Computed derived parameters: {}
2023-07-02 10:33:35,927 [model] Posterior to be computed for parameters {'Omega_m': 0.31022168957578045, 'b1': 0.5081695971600135}
2023-07-02 10:33:35,927 [prior] Evaluating prior at array([0.31022169, 0.5081696 ])
2023-07-02 10:33:35,928 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:35,928 [model] Got input parameters: {'Omega_m': 0.31022168957578045, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:35,928 [classy] Got parameters {'Omega_m': 0.31022168957578045, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:35,928 [classy] Re-using computed results
2023-07-02 10:33:35,928 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.53322897143858}
2023-07-02 10:33:35,928 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:35,928 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:35,928 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:35,947 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.78295
2023-07-02 10:33:35,948 [model] Computed derived parameters: {}
2023-07-02 10:33:35,948 [mcmc] New sample, #117:
Omega_m:0.3102217, b1:0.5105119
2023-07-02 10:33:35,948 [model] Posterior to be computed for parameters {'Omega_m': 0.304926998135763, 'b1': 0.5081695971600135}
2023-07-02 10:33:35,948 [prior] Evaluating prior at array([0.304927 , 0.5081696])
2023-07-02 10:33:35,948 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:35,948 [model] Got input parameters: {'Omega_m': 0.304926998135763, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:35,948 [classy] Got parameters {'Omega_m': 0.304926998135763, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:35,948 [classy] Computing new state
2023-07-02 10:33:35,948 [classy] Setting parameters: {'Omega_m': 0.304926998135763, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:35,992 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.17931935125597}
2023-07-02 10:33:35,992 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:35,994 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00377134
2023-07-02 10:33:35,994 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:35,994 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:36,014 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.01857
2023-07-02 10:33:36,014 [model] Computed derived parameters: {}
2023-07-02 10:33:36,014 [mcmc] New sample, #118:
Omega_m:0.3102217, b1:0.5081696
2023-07-02 10:33:36,014 [model] Posterior to be computed for parameters {'Omega_m': 0.304926998135763, 'b1': 1.060201838310671}
2023-07-02 10:33:36,014 [prior] Evaluating prior at array([0.304927 , 1.06020184])
2023-07-02 10:33:36,015 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:36,015 [model] Got input parameters: {'Omega_m': 0.304926998135763, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.060201838310671, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:36,015 [classy] Got parameters {'Omega_m': 0.304926998135763, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:36,015 [classy] Re-using computed results
2023-07-02 10:33:36,015 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.17931935125597}
2023-07-02 10:33:36,015 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:36,015 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.060201838310671, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:36,015 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:36,034 [fs_likelihood.fslikelihood] Computed log-likelihood = -1281.68
2023-07-02 10:33:36,034 [model] Computed derived parameters: {}
2023-07-02 10:33:36,034 [model] Posterior to be computed for parameters {'Omega_m': 0.3008093573410816, 'b1': 0.5081695971600135}
2023-07-02 10:33:36,034 [prior] Evaluating prior at array([0.30080936, 0.5081696 ])
2023-07-02 10:33:36,035 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:36,035 [model] Got input parameters: {'Omega_m': 0.3008093573410816, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:36,035 [classy] Got parameters {'Omega_m': 0.3008093573410816, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:36,035 [classy] Computing new state
2023-07-02 10:33:36,035 [classy] Setting parameters: {'Omega_m': 0.3008093573410816, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:36,079 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.6886239463967}
2023-07-02 10:33:36,079 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:36,081 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0088089
2023-07-02 10:33:36,081 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:36,081 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:36,100 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.850393
2023-07-02 10:33:36,100 [model] Computed derived parameters: {}
2023-07-02 10:33:36,100 [mcmc] New sample, #119:
Omega_m:0.304927, b1:0.5081696
2023-07-02 10:33:36,101 [model] Posterior to be computed for parameters {'Omega_m': 0.3008093573410816, 'b1': -0.503101310011393}
2023-07-02 10:33:36,101 [prior] Evaluating prior at array([ 0.30080936, -0.50310131])
2023-07-02 10:33:36,101 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:36,101 [model] Posterior to be computed for parameters {'Omega_m': 0.3055764962815365, 'b1': 0.5081695971600135}
2023-07-02 10:33:36,101 [prior] Evaluating prior at array([0.3055765, 0.5081696])
2023-07-02 10:33:36,101 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:36,101 [model] Got input parameters: {'Omega_m': 0.3055764962815365, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:36,101 [classy] Got parameters {'Omega_m': 0.3055764962815365, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:36,101 [classy] Computing new state
2023-07-02 10:33:36,101 [classy] Setting parameters: {'Omega_m': 0.3055764962815365, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:36,147 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.0995371775601}
2023-07-02 10:33:36,147 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:36,149 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0031794
2023-07-02 10:33:36,149 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:36,149 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:36,169 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.15699
2023-07-02 10:33:36,169 [model] Computed derived parameters: {}
2023-07-02 10:33:36,169 [mcmc] New sample, #120:
Omega_m:0.3008094, b1:0.5081696
2023-07-02 10:33:36,169 [model] Posterior to be computed for parameters {'Omega_m': 0.3055764962815365, 'b1': 1.2054939901200719}
2023-07-02 10:33:36,170 [prior] Evaluating prior at array([0.3055765 , 1.20549399])
2023-07-02 10:33:36,170 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:36,170 [model] Got input parameters: {'Omega_m': 0.3055764962815365, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.2054939901200719, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:36,170 [classy] Got parameters {'Omega_m': 0.3055764962815365, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:36,170 [classy] Re-using computed results
2023-07-02 10:33:36,170 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.0995371775601}
2023-07-02 10:33:36,170 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:36,170 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.2054939901200719, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:36,170 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:36,189 [fs_likelihood.fslikelihood] Computed log-likelihood = -2334.48
2023-07-02 10:33:36,189 [model] Computed derived parameters: {}
2023-07-02 10:33:36,189 [model] Posterior to be computed for parameters {'Omega_m': 0.3260408447717924, 'b1': 0.5081695971600135}
2023-07-02 10:33:36,189 [prior] Evaluating prior at array([0.32604084, 0.5081696 ])
2023-07-02 10:33:36,190 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:36,190 [model] Got input parameters: {'Omega_m': 0.3260408447717924, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:36,190 [classy] Got parameters {'Omega_m': 0.3260408447717924, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:36,190 [classy] Computing new state
2023-07-02 10:33:36,190 [classy] Setting parameters: {'Omega_m': 0.3260408447717924, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:36,233 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.65959264316893}
2023-07-02 10:33:36,233 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:36,235 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.011103
2023-07-02 10:33:36,235 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:36,235 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:36,255 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.122503
2023-07-02 10:33:36,255 [model] Computed derived parameters: {}
2023-07-02 10:33:36,255 [model] Posterior to be computed for parameters {'Omega_m': 0.3055764962815365, 'b1': 1.079658733028018}
2023-07-02 10:33:36,255 [prior] Evaluating prior at array([0.3055765 , 1.07965873])
2023-07-02 10:33:36,255 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:36,255 [model] Got input parameters: {'Omega_m': 0.3055764962815365, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.079658733028018, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:36,255 [classy] Got parameters {'Omega_m': 0.3055764962815365, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:36,255 [classy] Re-using computed results
2023-07-02 10:33:36,255 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.0995371775601}
2023-07-02 10:33:36,255 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:36,255 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.079658733028018, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:36,255 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:36,275 [fs_likelihood.fslikelihood] Computed log-likelihood = -1406.53
2023-07-02 10:33:36,275 [model] Computed derived parameters: {}
2023-07-02 10:33:36,275 [model] Posterior to be computed for parameters {'Omega_m': 0.31247175656915455, 'b1': 0.5081695971600135}
2023-07-02 10:33:36,275 [prior] Evaluating prior at array([0.31247176, 0.5081696 ])
2023-07-02 10:33:36,275 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:36,275 [model] Got input parameters: {'Omega_m': 0.31247175656915455, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:36,276 [classy] Got parameters {'Omega_m': 0.31247175656915455, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:36,276 [classy] Computing new state
2023-07-02 10:33:36,276 [classy] Setting parameters: {'Omega_m': 0.31247175656915455, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:36,319 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.2615973800514}
2023-07-02 10:33:36,319 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:36,321 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000202381
2023-07-02 10:33:36,321 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:36,321 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:36,342 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.8565
2023-07-02 10:33:36,342 [model] Computed derived parameters: {}
2023-07-02 10:33:36,342 [mcmc] New sample, #121:
Omega_m:0.3055765, b1:0.5081696
2023-07-02 10:33:36,342 [model] Posterior to be computed for parameters {'Omega_m': 0.31247175656915455, 'b1': 0.7720336305758482}
2023-07-02 10:33:36,342 [prior] Evaluating prior at array([0.31247176, 0.77203363])
2023-07-02 10:33:36,342 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:36,342 [model] Got input parameters: {'Omega_m': 0.31247175656915455, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.7720336305758482, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:36,342 [classy] Got parameters {'Omega_m': 0.31247175656915455, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:36,342 [classy] Re-using computed results
2023-07-02 10:33:36,342 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.2615973800514}
2023-07-02 10:33:36,342 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:36,342 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.7720336305758482, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:36,342 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:36,363 [fs_likelihood.fslikelihood] Computed log-likelihood = -245.103
2023-07-02 10:33:36,363 [model] Computed derived parameters: {}
2023-07-02 10:33:36,363 [model] Posterior to be computed for parameters {'Omega_m': 0.29155448467519973, 'b1': 0.5081695971600135}
2023-07-02 10:33:36,363 [prior] Evaluating prior at array([0.29155448, 0.5081696 ])
2023-07-02 10:33:36,363 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:36,363 [model] Got input parameters: {'Omega_m': 0.29155448467519973, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:36,363 [classy] Got parameters {'Omega_m': 0.29155448467519973, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:36,363 [classy] Computing new state
2023-07-02 10:33:36,363 [classy] Setting parameters: {'Omega_m': 0.29155448467519973, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:36,407 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.85609140897708}
2023-07-02 10:33:36,407 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:36,408 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0285302
2023-07-02 10:33:36,408 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:36,408 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:36,428 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.60724
2023-07-02 10:33:36,428 [model] Computed derived parameters: {}
2023-07-02 10:33:36,428 [model] Posterior to be computed for parameters {'Omega_m': 0.31247175656915455, 'b1': 1.7393984440137882}
2023-07-02 10:33:36,428 [prior] Evaluating prior at array([0.31247176, 1.73939844])
2023-07-02 10:33:36,429 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:36,429 [model] Got input parameters: {'Omega_m': 0.31247175656915455, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.7393984440137882, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:36,429 [classy] Got parameters {'Omega_m': 0.31247175656915455, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:36,429 [classy] Re-using computed results
2023-07-02 10:33:36,429 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.2615973800514}
2023-07-02 10:33:36,429 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:36,429 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.7393984440137882, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:36,429 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:36,448 [fs_likelihood.fslikelihood] Computed log-likelihood = -11340.5
2023-07-02 10:33:36,448 [model] Computed derived parameters: {}
2023-07-02 10:33:36,448 [model] Posterior to be computed for parameters {'Omega_m': 0.29316465552280807, 'b1': 0.5081695971600135}
2023-07-02 10:33:36,448 [prior] Evaluating prior at array([0.29316466, 0.5081696 ])
2023-07-02 10:33:36,448 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:36,448 [model] Got input parameters: {'Omega_m': 0.29316465552280807, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:36,448 [classy] Got parameters {'Omega_m': 0.29316465552280807, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:36,448 [classy] Computing new state
2023-07-02 10:33:36,449 [classy] Setting parameters: {'Omega_m': 0.29316465552280807, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:36,493 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.65068292008283}
2023-07-02 10:33:36,493 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:36,494 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0242389
2023-07-02 10:33:36,495 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:36,495 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:36,514 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.64948
2023-07-02 10:33:36,514 [model] Computed derived parameters: {}
2023-07-02 10:33:36,514 [model] Posterior to be computed for parameters {'Omega_m': 0.31247175656915455, 'b1': 0.33105147055559525}
2023-07-02 10:33:36,514 [prior] Evaluating prior at array([0.31247176, 0.33105147])
2023-07-02 10:33:36,515 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:36,515 [model] Got input parameters: {'Omega_m': 0.31247175656915455, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.33105147055559525, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:36,515 [classy] Got parameters {'Omega_m': 0.31247175656915455, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:36,515 [classy] Re-using computed results
2023-07-02 10:33:36,515 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.2615973800514}
2023-07-02 10:33:36,515 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:36,515 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.33105147055559525, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:36,515 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:36,534 [fs_likelihood.fslikelihood] Computed log-likelihood = -65.1219
2023-07-02 10:33:36,534 [model] Computed derived parameters: {}
2023-07-02 10:33:36,535 [model] Posterior to be computed for parameters {'Omega_m': 0.30840967264956726, 'b1': 0.5081695971600135}
2023-07-02 10:33:36,535 [prior] Evaluating prior at array([0.30840967, 0.5081696 ])
2023-07-02 10:33:36,535 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:36,535 [model] Got input parameters: {'Omega_m': 0.30840967264956726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:36,535 [classy] Got parameters {'Omega_m': 0.30840967264956726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:36,535 [classy] Computing new state
2023-07-02 10:33:36,535 [classy] Setting parameters: {'Omega_m': 0.30840967264956726, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:36,580 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.75324189963197}
2023-07-02 10:33:36,580 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:36,582 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0012308
2023-07-02 10:33:36,582 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:36,582 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:36,601 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.61477
2023-07-02 10:33:36,601 [model] Computed derived parameters: {}
2023-07-02 10:33:36,601 [mcmc] New sample, #122:
Omega_m:0.3124718, b1:0.5081696
2023-07-02 10:33:36,601 [model] Posterior to be computed for parameters {'Omega_m': 0.30840967264956726, 'b1': 1.7275159147977868}
2023-07-02 10:33:36,601 [prior] Evaluating prior at array([0.30840967, 1.72751591])
2023-07-02 10:33:36,602 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:36,602 [model] Got input parameters: {'Omega_m': 0.30840967264956726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.7275159147977868, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:36,602 [classy] Got parameters {'Omega_m': 0.30840967264956726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:36,602 [classy] Re-using computed results
2023-07-02 10:33:36,602 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.75324189963197}
2023-07-02 10:33:36,602 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:36,602 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.7275159147977868, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:36,602 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:36,622 [fs_likelihood.fslikelihood] Computed log-likelihood = -10768.1
2023-07-02 10:33:36,622 [model] Computed derived parameters: {}
2023-07-02 10:33:36,623 [model] Posterior to be computed for parameters {'Omega_m': 0.30446167646349287, 'b1': 0.5081695971600135}
2023-07-02 10:33:36,623 [prior] Evaluating prior at array([0.30446168, 0.5081696 ])
2023-07-02 10:33:36,623 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:36,623 [model] Got input parameters: {'Omega_m': 0.30446167646349287, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:36,623 [classy] Got parameters {'Omega_m': 0.30446167646349287, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:36,623 [classy] Computing new state
2023-07-02 10:33:36,623 [classy] Setting parameters: {'Omega_m': 0.30446167646349287, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:36,667 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.23657293161716}
2023-07-02 10:33:36,667 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:36,669 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00422911
2023-07-02 10:33:36,669 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:36,669 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:36,688 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.91171
2023-07-02 10:33:36,689 [model] Computed derived parameters: {}
2023-07-02 10:33:36,689 [model] Posterior to be computed for parameters {'Omega_m': 0.30840967264956726, 'b1': 0.015378842072254428}
2023-07-02 10:33:36,689 [prior] Evaluating prior at array([0.30840967, 0.01537884])
2023-07-02 10:33:36,689 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:36,689 [model] Got input parameters: {'Omega_m': 0.30840967264956726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.015378842072254428, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:36,689 [classy] Got parameters {'Omega_m': 0.30840967264956726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:36,689 [classy] Re-using computed results
2023-07-02 10:33:36,689 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.75324189963197}
2023-07-02 10:33:36,689 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:36,689 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.015378842072254428, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:36,689 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:36,708 [fs_likelihood.fslikelihood] Computed log-likelihood = -386.368
2023-07-02 10:33:36,708 [model] Computed derived parameters: {}
2023-07-02 10:33:36,708 [model] Posterior to be computed for parameters {'Omega_m': 0.3018960180983903, 'b1': 0.5081695971600135}
2023-07-02 10:33:36,709 [prior] Evaluating prior at array([0.30189602, 0.5081696 ])
2023-07-02 10:33:36,709 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:36,709 [model] Got input parameters: {'Omega_m': 0.3018960180983903, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:36,709 [classy] Got parameters {'Omega_m': 0.3018960180983903, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:36,709 [classy] Computing new state
2023-07-02 10:33:36,709 [classy] Setting parameters: {'Omega_m': 0.3018960180983903, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:36,752 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.55362652446505}
2023-07-02 10:33:36,753 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:36,754 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00726192
2023-07-02 10:33:36,754 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:36,754 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:36,775 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.20743
2023-07-02 10:33:36,775 [model] Computed derived parameters: {}
2023-07-02 10:33:36,775 [model] Posterior to be computed for parameters {'Omega_m': 0.30840967264956726, 'b1': -0.29249185115331444}
2023-07-02 10:33:36,775 [prior] Evaluating prior at array([ 0.30840967, -0.29249185])
2023-07-02 10:33:36,775 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:36,776 [model] Posterior to be computed for parameters {'Omega_m': 0.2946358412335537, 'b1': 0.5081695971600135}
2023-07-02 10:33:36,776 [prior] Evaluating prior at array([0.29463584, 0.5081696 ])
2023-07-02 10:33:36,776 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:36,776 [model] Got input parameters: {'Omega_m': 0.2946358412335537, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:36,776 [classy] Got parameters {'Omega_m': 0.2946358412335537, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:36,776 [classy] Computing new state
2023-07-02 10:33:36,776 [classy] Setting parameters: {'Omega_m': 0.2946358412335537, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:36,820 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.46385592365976}
2023-07-02 10:33:36,820 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:36,822 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0206397
2023-07-02 10:33:36,822 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:36,822 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:36,841 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.8415
2023-07-02 10:33:36,841 [model] Computed derived parameters: {}
2023-07-02 10:33:36,842 [model] Posterior to be computed for parameters {'Omega_m': 0.30840967264956726, 'b1': 1.6850664810807543}
2023-07-02 10:33:36,842 [prior] Evaluating prior at array([0.30840967, 1.68506648])
2023-07-02 10:33:36,842 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:36,842 [model] Got input parameters: {'Omega_m': 0.30840967264956726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.6850664810807543, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:36,842 [classy] Got parameters {'Omega_m': 0.30840967264956726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:36,842 [classy] Re-using computed results
2023-07-02 10:33:36,842 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.75324189963197}
2023-07-02 10:33:36,842 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:36,842 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.6850664810807543, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:36,842 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:36,862 [fs_likelihood.fslikelihood] Computed log-likelihood = -9743.94
2023-07-02 10:33:36,862 [model] Computed derived parameters: {}
2023-07-02 10:33:36,862 [model] Posterior to be computed for parameters {'Omega_m': 0.3288175442948318, 'b1': 0.5081695971600135}
2023-07-02 10:33:36,862 [prior] Evaluating prior at array([0.32881754, 0.5081696 ])
2023-07-02 10:33:36,862 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:36,862 [model] Got input parameters: {'Omega_m': 0.3288175442948318, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:36,862 [classy] Got parameters {'Omega_m': 0.3288175442948318, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:36,862 [classy] Computing new state
2023-07-02 10:33:36,862 [classy] Setting parameters: {'Omega_m': 0.3288175442948318, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:36,906 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.3391297745185}
2023-07-02 10:33:36,906 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:36,908 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0159204
2023-07-02 10:33:36,908 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:36,908 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:36,928 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.10883
2023-07-02 10:33:36,928 [model] Computed derived parameters: {}
2023-07-02 10:33:36,929 [model] Posterior to be computed for parameters {'Omega_m': 0.30840967264956726, 'b1': -0.05116341311026684}
2023-07-02 10:33:36,929 [prior] Evaluating prior at array([ 0.30840967, -0.05116341])
2023-07-02 10:33:36,929 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:36,929 [model] Posterior to be computed for parameters {'Omega_m': 0.3232899819571299, 'b1': 0.5081695971600135}
2023-07-02 10:33:36,929 [prior] Evaluating prior at array([0.32328998, 0.5081696 ])
2023-07-02 10:33:36,929 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:36,929 [model] Got input parameters: {'Omega_m': 0.3232899819571299, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:36,929 [classy] Got parameters {'Omega_m': 0.3232899819571299, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:36,929 [classy] Computing new state
2023-07-02 10:33:36,929 [classy] Setting parameters: {'Omega_m': 0.3232899819571299, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:36,973 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.97949359718532}
2023-07-02 10:33:36,973 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:36,975 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00717428
2023-07-02 10:33:36,975 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:36,975 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:36,994 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.11729
2023-07-02 10:33:36,994 [model] Computed derived parameters: {}
2023-07-02 10:33:36,994 [mcmc] New sample, #123:
Omega_m:0.3084097, b1:0.5081696
2023-07-02 10:33:36,995 [model] Posterior to be computed for parameters {'Omega_m': 0.3232899819571299, 'b1': -0.44932249114335177}
2023-07-02 10:33:36,995 [prior] Evaluating prior at array([ 0.32328998, -0.44932249])
2023-07-02 10:33:36,995 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:36,995 [model] Posterior to be computed for parameters {'Omega_m': 0.3311757114228575, 'b1': 0.5081695971600135}
2023-07-02 10:33:36,995 [prior] Evaluating prior at array([0.33117571, 0.5081696 ])
2023-07-02 10:33:36,995 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:36,995 [model] Got input parameters: {'Omega_m': 0.3311757114228575, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:36,995 [classy] Got parameters {'Omega_m': 0.3311757114228575, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:36,995 [classy] Computing new state
2023-07-02 10:33:36,995 [classy] Setting parameters: {'Omega_m': 0.3311757114228575, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:37,042 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.0689004795194}
2023-07-02 10:33:37,042 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:37,044 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0206697
2023-07-02 10:33:37,044 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:37,044 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:37,063 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.33382
2023-07-02 10:33:37,063 [model] Computed derived parameters: {}
2023-07-02 10:33:37,063 [model] Posterior to be computed for parameters {'Omega_m': 0.3232899819571299, 'b1': 0.24520817249958016}
2023-07-02 10:33:37,063 [prior] Evaluating prior at array([0.32328998, 0.24520817])
2023-07-02 10:33:37,064 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:37,064 [model] Got input parameters: {'Omega_m': 0.3232899819571299, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.24520817249958016, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:37,064 [classy] Got parameters {'Omega_m': 0.3232899819571299, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:37,064 [classy] Re-using computed results
2023-07-02 10:33:37,064 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.97949359718532}
2023-07-02 10:33:37,064 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:37,064 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.24520817249958016, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:37,064 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:37,084 [fs_likelihood.fslikelihood] Computed log-likelihood = -119.381
2023-07-02 10:33:37,084 [model] Computed derived parameters: {}
2023-07-02 10:33:37,084 [model] Posterior to be computed for parameters {'Omega_m': 0.33501843113753715, 'b1': 0.5081695971600135}
2023-07-02 10:33:37,084 [prior] Evaluating prior at array([0.33501843, 0.5081696 ])
2023-07-02 10:33:37,084 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:37,084 [model] Got input parameters: {'Omega_m': 0.33501843113753715, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:37,084 [classy] Got parameters {'Omega_m': 0.33501843113753715, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:37,084 [classy] Computing new state
2023-07-02 10:33:37,084 [classy] Setting parameters: {'Omega_m': 0.33501843113753715, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:37,129 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.6322592423256}
2023-07-02 10:33:37,129 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:37,131 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0296771
2023-07-02 10:33:37,131 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:37,131 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:37,152 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.68271
2023-07-02 10:33:37,152 [model] Computed derived parameters: {}
2023-07-02 10:33:37,152 [model] Posterior to be computed for parameters {'Omega_m': 0.3232899819571299, 'b1': 1.3789346849233155}
2023-07-02 10:33:37,152 [prior] Evaluating prior at array([0.32328998, 1.37893468])
2023-07-02 10:33:37,152 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:37,152 [model] Got input parameters: {'Omega_m': 0.3232899819571299, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.3789346849233155, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:37,152 [classy] Got parameters {'Omega_m': 0.3232899819571299, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:37,152 [classy] Re-using computed results
2023-07-02 10:33:37,152 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.97949359718532}
2023-07-02 10:33:37,152 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:37,152 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.3789346849233155, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:37,152 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:37,173 [fs_likelihood.fslikelihood] Computed log-likelihood = -4744.79
2023-07-02 10:33:37,173 [model] Computed derived parameters: {}
2023-07-02 10:33:37,173 [model] Posterior to be computed for parameters {'Omega_m': 0.32697971639747914, 'b1': 0.5081695971600135}
2023-07-02 10:33:37,173 [prior] Evaluating prior at array([0.32697972, 0.5081696 ])
2023-07-02 10:33:37,173 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:37,173 [model] Got input parameters: {'Omega_m': 0.32697971639747914, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:37,173 [classy] Got parameters {'Omega_m': 0.32697971639747914, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:37,173 [classy] Computing new state
2023-07-02 10:33:37,173 [classy] Setting parameters: {'Omega_m': 0.32697971639747914, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:37,216 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.55096424676256}
2023-07-02 10:33:37,217 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:37,218 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0126369
2023-07-02 10:33:37,218 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:37,218 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:37,238 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.2683
2023-07-02 10:33:37,238 [model] Computed derived parameters: {}
2023-07-02 10:33:37,238 [mcmc] New sample, #124:
Omega_m:0.32329, b1:0.5081696
2023-07-02 10:33:37,238 [model] Posterior to be computed for parameters {'Omega_m': 0.32697971639747914, 'b1': -0.5229581498477165}
2023-07-02 10:33:37,238 [prior] Evaluating prior at array([ 0.32697972, -0.52295815])
2023-07-02 10:33:37,239 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:37,239 [model] Posterior to be computed for parameters {'Omega_m': 0.33430723245825184, 'b1': 0.5081695971600135}
2023-07-02 10:33:37,239 [prior] Evaluating prior at array([0.33430723, 0.5081696 ])
2023-07-02 10:33:37,239 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:37,239 [model] Got input parameters: {'Omega_m': 0.33430723245825184, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:37,239 [classy] Got parameters {'Omega_m': 0.33430723245825184, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:37,239 [classy] Computing new state
2023-07-02 10:33:37,239 [classy] Setting parameters: {'Omega_m': 0.33430723245825184, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:37,283 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.7127290004227}
2023-07-02 10:33:37,283 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:37,285 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0278931
2023-07-02 10:33:37,285 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:37,285 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:37,304 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.21501
2023-07-02 10:33:37,304 [model] Computed derived parameters: {}
2023-07-02 10:33:37,304 [model] Posterior to be computed for parameters {'Omega_m': 0.32697971639747914, 'b1': 0.12312667819051804}
2023-07-02 10:33:37,304 [prior] Evaluating prior at array([0.32697972, 0.12312668])
2023-07-02 10:33:37,305 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:37,305 [model] Got input parameters: {'Omega_m': 0.32697971639747914, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.12312667819051804, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:37,305 [classy] Got parameters {'Omega_m': 0.32697971639747914, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:37,305 [classy] Re-using computed results
2023-07-02 10:33:37,305 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.55096424676256}
2023-07-02 10:33:37,305 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:37,305 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.12312667819051804, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:37,305 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:37,324 [fs_likelihood.fslikelihood] Computed log-likelihood = -234.415
2023-07-02 10:33:37,324 [model] Computed derived parameters: {}
2023-07-02 10:33:37,324 [model] Posterior to be computed for parameters {'Omega_m': 0.32193156491818914, 'b1': 0.5081695971600135}
2023-07-02 10:33:37,325 [prior] Evaluating prior at array([0.32193156, 0.5081696 ])
2023-07-02 10:33:37,325 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:37,325 [model] Got input parameters: {'Omega_m': 0.32193156491818914, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:37,325 [classy] Got parameters {'Omega_m': 0.32193156491818914, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:37,325 [classy] Computing new state
2023-07-02 10:33:37,325 [classy] Setting parameters: {'Omega_m': 0.32193156491818914, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:37,369 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.13836508112396}
2023-07-02 10:33:37,369 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:37,371 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00554919
2023-07-02 10:33:37,371 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:37,371 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:37,390 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.52591
2023-07-02 10:33:37,391 [model] Computed derived parameters: {}
2023-07-02 10:33:37,391 [mcmc] New sample, #125:
Omega_m:0.3269797, b1:0.5081696
2023-07-02 10:33:37,391 [model] Posterior to be computed for parameters {'Omega_m': 0.32193156491818914, 'b1': 1.3504724504965633}
2023-07-02 10:33:37,391 [prior] Evaluating prior at array([0.32193156, 1.35047245])
2023-07-02 10:33:37,391 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:37,391 [model] Got input parameters: {'Omega_m': 0.32193156491818914, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.3504724504965633, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:37,391 [classy] Got parameters {'Omega_m': 0.32193156491818914, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:37,391 [classy] Re-using computed results
2023-07-02 10:33:37,391 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.13836508112396}
2023-07-02 10:33:37,391 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:37,391 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.3504724504965633, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:37,391 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:37,411 [fs_likelihood.fslikelihood] Computed log-likelihood = -4310.46
2023-07-02 10:33:37,411 [model] Computed derived parameters: {}
2023-07-02 10:33:37,411 [model] Posterior to be computed for parameters {'Omega_m': 0.3210690439003122, 'b1': 0.5081695971600135}
2023-07-02 10:33:37,411 [prior] Evaluating prior at array([0.32106904, 0.5081696 ])
2023-07-02 10:33:37,411 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:37,411 [model] Got input parameters: {'Omega_m': 0.3210690439003122, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:37,411 [classy] Got parameters {'Omega_m': 0.3210690439003122, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:37,411 [classy] Computing new state
2023-07-02 10:33:37,412 [classy] Setting parameters: {'Omega_m': 0.3210690439003122, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:37,455 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.23955143743035}
2023-07-02 10:33:37,455 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:37,457 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00462674
2023-07-02 10:33:37,457 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:37,457 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:37,477 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.75699
2023-07-02 10:33:37,477 [model] Computed derived parameters: {}
2023-07-02 10:33:37,477 [mcmc] New sample, #126:
Omega_m:0.3219316, b1:0.5081696
2023-07-02 10:33:37,477 [model] Posterior to be computed for parameters {'Omega_m': 0.3210690439003122, 'b1': 0.4593580081508827}
2023-07-02 10:33:37,477 [prior] Evaluating prior at array([0.32106904, 0.45935801])
2023-07-02 10:33:37,478 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:37,478 [model] Got input parameters: {'Omega_m': 0.3210690439003122, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4593580081508827, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:37,478 [classy] Got parameters {'Omega_m': 0.3210690439003122, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:37,478 [classy] Re-using computed results
2023-07-02 10:33:37,478 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.23955143743035}
2023-07-02 10:33:37,478 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:37,478 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4593580081508827, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:37,478 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:37,497 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.373788
2023-07-02 10:33:37,498 [model] Computed derived parameters: {}
2023-07-02 10:33:37,498 [model] Posterior to be computed for parameters {'Omega_m': 0.3141022778514822, 'b1': 0.5081695971600135}
2023-07-02 10:33:37,498 [prior] Evaluating prior at array([0.31410228, 0.5081696 ])
2023-07-02 10:33:37,498 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:37,498 [model] Got input parameters: {'Omega_m': 0.3141022778514822, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:37,498 [classy] Got parameters {'Omega_m': 0.3141022778514822, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:37,498 [classy] Computing new state
2023-07-02 10:33:37,498 [classy] Setting parameters: {'Omega_m': 0.3141022778514822, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:37,542 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.06583579745725}
2023-07-02 10:33:37,542 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:37,544 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000362397
2023-07-02 10:33:37,544 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:37,544 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:37,564 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.81612
2023-07-02 10:33:37,564 [model] Computed derived parameters: {}
2023-07-02 10:33:37,564 [mcmc] New sample, #127:
Omega_m:0.321069, b1:0.5081696
2023-07-02 10:33:37,564 [model] Posterior to be computed for parameters {'Omega_m': 0.3141022778514822, 'b1': 1.9673070374974118}
2023-07-02 10:33:37,564 [prior] Evaluating prior at array([0.31410228, 1.96730704])
2023-07-02 10:33:37,564 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:37,564 [model] Got input parameters: {'Omega_m': 0.3141022778514822, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.9673070374974118, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:37,564 [classy] Got parameters {'Omega_m': 0.3141022778514822, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:37,564 [classy] Re-using computed results
2023-07-02 10:33:37,564 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.06583579745725}
2023-07-02 10:33:37,564 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:37,564 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.9673070374974118, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:37,564 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:37,584 [fs_likelihood.fslikelihood] Computed log-likelihood = -18627.9
2023-07-02 10:33:37,584 [model] Computed derived parameters: {}
2023-07-02 10:33:37,584 [model] Posterior to be computed for parameters {'Omega_m': 0.3251188279579224, 'b1': 0.5081695971600135}
2023-07-02 10:33:37,584 [prior] Evaluating prior at array([0.32511883, 0.5081696 ])
2023-07-02 10:33:37,585 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:37,585 [model] Got input parameters: {'Omega_m': 0.3251188279579224, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:37,585 [classy] Got parameters {'Omega_m': 0.3251188279579224, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:37,585 [classy] Computing new state
2023-07-02 10:33:37,585 [classy] Setting parameters: {'Omega_m': 0.3251188279579224, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:37,628 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.76654441451672}
2023-07-02 10:33:37,628 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:37,630 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00969179
2023-07-02 10:33:37,630 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:37,630 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:37,650 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.480892
2023-07-02 10:33:37,650 [model] Computed derived parameters: {}
2023-07-02 10:33:37,650 [model] Posterior to be computed for parameters {'Omega_m': 0.3141022778514822, 'b1': 1.0692039959281265}
2023-07-02 10:33:37,650 [prior] Evaluating prior at array([0.31410228, 1.069204 ])
2023-07-02 10:33:37,650 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:37,650 [model] Got input parameters: {'Omega_m': 0.3141022778514822, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.0692039959281265, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:37,650 [classy] Got parameters {'Omega_m': 0.3141022778514822, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:37,651 [classy] Re-using computed results
2023-07-02 10:33:37,651 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.06583579745725}
2023-07-02 10:33:37,651 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:37,651 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.0692039959281265, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:37,651 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:37,670 [fs_likelihood.fslikelihood] Computed log-likelihood = -1454.46
2023-07-02 10:33:37,670 [model] Computed derived parameters: {}
2023-07-02 10:33:37,670 [model] Posterior to be computed for parameters {'Omega_m': 0.32319048762567615, 'b1': 0.5081695971600135}
2023-07-02 10:33:37,670 [prior] Evaluating prior at array([0.32319049, 0.5081696 ])
2023-07-02 10:33:37,671 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:37,671 [model] Got input parameters: {'Omega_m': 0.32319048762567615, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:37,671 [classy] Got parameters {'Omega_m': 0.32319048762567615, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:37,671 [classy] Computing new state
2023-07-02 10:33:37,671 [classy] Setting parameters: {'Omega_m': 0.32319048762567615, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:37,714 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.99111118685556}
2023-07-02 10:33:37,714 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:37,716 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00704809
2023-07-02 10:33:37,716 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:37,716 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:37,736 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.14908
2023-07-02 10:33:37,736 [model] Computed derived parameters: {}
2023-07-02 10:33:37,736 [model] Posterior to be computed for parameters {'Omega_m': 0.3141022778514822, 'b1': 0.7709452780085824}
2023-07-02 10:33:37,736 [prior] Evaluating prior at array([0.31410228, 0.77094528])
2023-07-02 10:33:37,736 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:37,736 [model] Got input parameters: {'Omega_m': 0.3141022778514822, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.7709452780085824, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:37,736 [classy] Got parameters {'Omega_m': 0.3141022778514822, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:37,737 [classy] Re-using computed results
2023-07-02 10:33:37,737 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.06583579745725}
2023-07-02 10:33:37,737 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:37,737 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.7709452780085824, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:37,737 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:37,756 [fs_likelihood.fslikelihood] Computed log-likelihood = -249.461
2023-07-02 10:33:37,756 [model] Computed derived parameters: {}
2023-07-02 10:33:37,756 [model] Posterior to be computed for parameters {'Omega_m': 0.3078101188864791, 'b1': 0.5081695971600135}
2023-07-02 10:33:37,756 [prior] Evaluating prior at array([0.30781012, 0.5081696 ])
2023-07-02 10:33:37,756 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:37,756 [model] Got input parameters: {'Omega_m': 0.3078101188864791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:37,756 [classy] Got parameters {'Omega_m': 0.3078101188864791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:37,757 [classy] Computing new state
2023-07-02 10:33:37,757 [classy] Setting parameters: {'Omega_m': 0.3078101188864791, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:37,801 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.82629060786067}
2023-07-02 10:33:37,801 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:37,802 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00155778
2023-07-02 10:33:37,802 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:37,802 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:37,822 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.53772
2023-07-02 10:33:37,822 [model] Computed derived parameters: {}
2023-07-02 10:33:37,822 [model] Posterior to be computed for parameters {'Omega_m': 0.3141022778514822, 'b1': -0.10535079769791722}
2023-07-02 10:33:37,822 [prior] Evaluating prior at array([ 0.31410228, -0.1053508 ])
2023-07-02 10:33:37,822 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:37,822 [model] Posterior to be computed for parameters {'Omega_m': 0.301964460517499, 'b1': 0.5081695971600135}
2023-07-02 10:33:37,822 [prior] Evaluating prior at array([0.30196446, 0.5081696 ])
2023-07-02 10:33:37,822 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:37,822 [model] Got input parameters: {'Omega_m': 0.301964460517499, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:37,823 [classy] Got parameters {'Omega_m': 0.301964460517499, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:37,823 [classy] Computing new state
2023-07-02 10:33:37,823 [classy] Setting parameters: {'Omega_m': 0.301964460517499, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:37,867 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.54513882597197}
2023-07-02 10:33:37,867 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:37,868 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00716976
2023-07-02 10:33:37,869 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:37,869 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:37,889 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.22875
2023-07-02 10:33:37,889 [model] Computed derived parameters: {}
2023-07-02 10:33:37,889 [model] Posterior to be computed for parameters {'Omega_m': 0.3141022778514822, 'b1': -0.6016101930397859}
2023-07-02 10:33:37,889 [prior] Evaluating prior at array([ 0.31410228, -0.60161019])
2023-07-02 10:33:37,889 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:37,889 [model] Posterior to be computed for parameters {'Omega_m': 0.3162645903438519, 'b1': 0.5081695971600135}
2023-07-02 10:33:37,889 [prior] Evaluating prior at array([0.31626459, 0.5081696 ])
2023-07-02 10:33:37,889 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:37,889 [model] Got input parameters: {'Omega_m': 0.3162645903438519, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:37,889 [classy] Got parameters {'Omega_m': 0.3162645903438519, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:37,889 [classy] Computing new state
2023-07-02 10:33:37,889 [classy] Setting parameters: {'Omega_m': 0.3162645903438519, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:37,933 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.80764076933906}
2023-07-02 10:33:37,933 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:37,935 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00107071
2023-07-02 10:33:37,935 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:37,935 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:37,954 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.64118
2023-07-02 10:33:37,955 [model] Computed derived parameters: {}
2023-07-02 10:33:37,955 [mcmc] New sample, #128:
Omega_m:0.3141023, b1:0.5081696
2023-07-02 10:33:37,955 [model] Posterior to be computed for parameters {'Omega_m': 0.3162645903438519, 'b1': 0.15035292186360488}
2023-07-02 10:33:37,955 [prior] Evaluating prior at array([0.31626459, 0.15035292])
2023-07-02 10:33:37,955 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:37,955 [model] Got input parameters: {'Omega_m': 0.3162645903438519, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.15035292186360488, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:37,955 [classy] Got parameters {'Omega_m': 0.3162645903438519, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:37,955 [classy] Re-using computed results
2023-07-02 10:33:37,955 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.80764076933906}
2023-07-02 10:33:37,955 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:37,955 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.15035292186360488, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:37,955 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:37,975 [fs_likelihood.fslikelihood] Computed log-likelihood = -223.355
2023-07-02 10:33:37,975 [model] Computed derived parameters: {}
2023-07-02 10:33:37,975 [model] Posterior to be computed for parameters {'Omega_m': 0.3500947073394598, 'b1': 0.5081695971600135}
2023-07-02 10:33:37,975 [prior] Evaluating prior at array([0.35009471, 0.5081696 ])
2023-07-02 10:33:37,976 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:37,976 [model] Got input parameters: {'Omega_m': 0.3500947073394598, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:37,976 [classy] Got parameters {'Omega_m': 0.3500947073394598, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:37,976 [classy] Computing new state
2023-07-02 10:33:37,976 [classy] Setting parameters: {'Omega_m': 0.3500947073394598, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:38,020 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.9619451226792}
2023-07-02 10:33:38,020 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:38,021 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0794496
2023-07-02 10:33:38,021 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:38,021 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:38,042 [fs_likelihood.fslikelihood] Computed log-likelihood = -18.1204
2023-07-02 10:33:38,042 [model] Computed derived parameters: {}
2023-07-02 10:33:38,042 [model] Posterior to be computed for parameters {'Omega_m': 0.3162645903438519, 'b1': 0.42174943916464563}
2023-07-02 10:33:38,042 [prior] Evaluating prior at array([0.31626459, 0.42174944])
2023-07-02 10:33:38,042 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:38,042 [model] Got input parameters: {'Omega_m': 0.3162645903438519, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42174943916464563, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:38,042 [classy] Got parameters {'Omega_m': 0.3162645903438519, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:38,042 [classy] Re-using computed results
2023-07-02 10:33:38,042 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.80764076933906}
2023-07-02 10:33:38,042 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:38,042 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42174943916464563, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:38,042 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:38,062 [fs_likelihood.fslikelihood] Computed log-likelihood = -11.6232
2023-07-02 10:33:38,062 [model] Computed derived parameters: {}
2023-07-02 10:33:38,063 [model] Posterior to be computed for parameters {'Omega_m': 0.33005710934507876, 'b1': 0.5081695971600135}
2023-07-02 10:33:38,063 [prior] Evaluating prior at array([0.33005711, 0.5081696 ])
2023-07-02 10:33:38,063 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:38,063 [model] Got input parameters: {'Omega_m': 0.33005710934507876, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:38,063 [classy] Got parameters {'Omega_m': 0.33005710934507876, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:38,063 [classy] Computing new state
2023-07-02 10:33:38,063 [classy] Setting parameters: {'Omega_m': 0.33005710934507876, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:38,107 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.19686068462528}
2023-07-02 10:33:38,107 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:38,109 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0183424
2023-07-02 10:33:38,109 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:38,109 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:38,130 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.73222
2023-07-02 10:33:38,131 [model] Computed derived parameters: {}
2023-07-02 10:33:38,131 [model] Posterior to be computed for parameters {'Omega_m': 0.3162645903438519, 'b1': 0.24631095733441694}
2023-07-02 10:33:38,131 [prior] Evaluating prior at array([0.31626459, 0.24631096])
2023-07-02 10:33:38,131 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:38,131 [model] Got input parameters: {'Omega_m': 0.3162645903438519, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.24631095733441694, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:38,131 [classy] Got parameters {'Omega_m': 0.3162645903438519, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:38,131 [classy] Re-using computed results
2023-07-02 10:33:38,131 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.80764076933906}
2023-07-02 10:33:38,131 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:38,131 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.24631095733441694, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:38,131 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:38,152 [fs_likelihood.fslikelihood] Computed log-likelihood = -128.714
2023-07-02 10:33:38,152 [model] Computed derived parameters: {}
2023-07-02 10:33:38,152 [model] Posterior to be computed for parameters {'Omega_m': 0.3264083096838791, 'b1': 0.5081695971600135}
2023-07-02 10:33:38,152 [prior] Evaluating prior at array([0.32640831, 0.5081696 ])
2023-07-02 10:33:38,152 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:38,152 [model] Got input parameters: {'Omega_m': 0.3264083096838791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:38,153 [classy] Got parameters {'Omega_m': 0.3264083096838791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:38,153 [classy] Computing new state
2023-07-02 10:33:38,153 [classy] Setting parameters: {'Omega_m': 0.3264083096838791, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:38,197 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.61704318193253}
2023-07-02 10:33:38,197 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:38,198 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0116917
2023-07-02 10:33:38,199 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:38,199 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:38,218 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.0273453
2023-07-02 10:33:38,218 [model] Computed derived parameters: {}
2023-07-02 10:33:38,218 [model] Posterior to be computed for parameters {'Omega_m': 0.3162645903438519, 'b1': -2.232836064909481}
2023-07-02 10:33:38,218 [prior] Evaluating prior at array([ 0.31626459, -2.23283606])
2023-07-02 10:33:38,218 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:38,219 [model] Posterior to be computed for parameters {'Omega_m': 0.32213276231902993, 'b1': 0.5081695971600135}
2023-07-02 10:33:38,219 [prior] Evaluating prior at array([0.32213276, 0.5081696 ])
2023-07-02 10:33:38,219 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:38,219 [model] Got input parameters: {'Omega_m': 0.32213276231902993, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:38,219 [classy] Got parameters {'Omega_m': 0.32213276231902993, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:38,219 [classy] Computing new state
2023-07-02 10:33:38,219 [classy] Setting parameters: {'Omega_m': 0.32213276231902993, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:38,263 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.11479559218836}
2023-07-02 10:33:38,263 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:38,265 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00577664
2023-07-02 10:33:38,265 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:38,265 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:38,285 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.46883
2023-07-02 10:33:38,285 [model] Computed derived parameters: {}
2023-07-02 10:33:38,285 [mcmc] New sample, #129:
Omega_m:0.3162646, b1:0.5081696
2023-07-02 10:33:38,285 [model] Posterior to be computed for parameters {'Omega_m': 0.32213276231902993, 'b1': -0.044039184540138}
2023-07-02 10:33:38,285 [prior] Evaluating prior at array([ 0.32213276, -0.04403918])
2023-07-02 10:33:38,285 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:38,285 [model] Posterior to be computed for parameters {'Omega_m': 0.32557116465223335, 'b1': 0.5081695971600135}
2023-07-02 10:33:38,285 [prior] Evaluating prior at array([0.32557116, 0.5081696 ])
2023-07-02 10:33:38,285 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:38,285 [model] Got input parameters: {'Omega_m': 0.32557116465223335, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:38,285 [classy] Got parameters {'Omega_m': 0.32557116465223335, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:38,285 [classy] Computing new state
2023-07-02 10:33:38,286 [classy] Setting parameters: {'Omega_m': 0.32557116465223335, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:38,330 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.71404168934984}
2023-07-02 10:33:38,330 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:38,332 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0103723
2023-07-02 10:33:38,332 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:38,332 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:38,352 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.308213
2023-07-02 10:33:38,352 [model] Computed derived parameters: {}
2023-07-02 10:33:38,352 [model] Posterior to be computed for parameters {'Omega_m': 0.32213276231902993, 'b1': 0.6479281521144084}
2023-07-02 10:33:38,352 [prior] Evaluating prior at array([0.32213276, 0.64792815])
2023-07-02 10:33:38,352 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:38,352 [model] Got input parameters: {'Omega_m': 0.32213276231902993, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6479281521144084, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:38,352 [classy] Got parameters {'Omega_m': 0.32213276231902993, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:38,352 [classy] Re-using computed results
2023-07-02 10:33:38,353 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.11479559218836}
2023-07-02 10:33:38,353 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:38,353 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6479281521144084, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:38,353 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:38,372 [fs_likelihood.fslikelihood] Computed log-likelihood = -79.2235
2023-07-02 10:33:38,373 [model] Computed derived parameters: {}
2023-07-02 10:33:38,373 [model] Posterior to be computed for parameters {'Omega_m': 0.32911900299080266, 'b1': 0.5081695971600135}
2023-07-02 10:33:38,373 [prior] Evaluating prior at array([0.329119 , 0.5081696])
2023-07-02 10:33:38,373 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:38,373 [model] Got input parameters: {'Omega_m': 0.32911900299080266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:38,373 [classy] Got parameters {'Omega_m': 0.32911900299080266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:38,373 [classy] Computing new state
2023-07-02 10:33:38,373 [classy] Setting parameters: {'Omega_m': 0.32911900299080266, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:38,417 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.30448501866485}
2023-07-02 10:33:38,417 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:38,419 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0164941
2023-07-02 10:33:38,419 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:38,419 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:38,438 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.25625
2023-07-02 10:33:38,439 [model] Computed derived parameters: {}
2023-07-02 10:33:38,439 [model] Posterior to be computed for parameters {'Omega_m': 0.32213276231902993, 'b1': 0.9235474343775831}
2023-07-02 10:33:38,439 [prior] Evaluating prior at array([0.32213276, 0.92354743])
2023-07-02 10:33:38,439 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:38,439 [model] Got input parameters: {'Omega_m': 0.32213276231902993, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.9235474343775831, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:38,439 [classy] Got parameters {'Omega_m': 0.32213276231902993, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:38,439 [classy] Re-using computed results
2023-07-02 10:33:38,439 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.11479559218836}
2023-07-02 10:33:38,439 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:38,439 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.9235474343775831, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:38,439 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:38,459 [fs_likelihood.fslikelihood] Computed log-likelihood = -775.629
2023-07-02 10:33:38,459 [model] Computed derived parameters: {}
2023-07-02 10:33:38,459 [model] Posterior to be computed for parameters {'Omega_m': 0.3086859712810961, 'b1': 0.5081695971600135}
2023-07-02 10:33:38,460 [prior] Evaluating prior at array([0.30868597, 0.5081696 ])
2023-07-02 10:33:38,460 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:38,460 [model] Got input parameters: {'Omega_m': 0.3086859712810961, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:38,460 [classy] Got parameters {'Omega_m': 0.3086859712810961, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:38,460 [classy] Computing new state
2023-07-02 10:33:38,460 [classy] Setting parameters: {'Omega_m': 0.3086859712810961, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:38,503 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.71962048732}
2023-07-02 10:33:38,504 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:38,505 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00109543
2023-07-02 10:33:38,505 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:38,505 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:38,525 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.6467
2023-07-02 10:33:38,525 [model] Computed derived parameters: {}
2023-07-02 10:33:38,525 [mcmc] New sample, #130:
Omega_m:0.3221328, b1:0.5081696
2023-07-02 10:33:38,525 [model] Posterior to be computed for parameters {'Omega_m': 0.3086859712810961, 'b1': -0.49715929178209883}
2023-07-02 10:33:38,525 [prior] Evaluating prior at array([ 0.30868597, -0.49715929])
2023-07-02 10:33:38,525 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:38,525 [model] Posterior to be computed for parameters {'Omega_m': 0.3095545377429137, 'b1': 0.5081695971600135}
2023-07-02 10:33:38,525 [prior] Evaluating prior at array([0.30955454, 0.5081696 ])
2023-07-02 10:33:38,525 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:38,525 [model] Got input parameters: {'Omega_m': 0.3095545377429137, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:38,526 [classy] Got parameters {'Omega_m': 0.3095545377429137, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:38,526 [classy] Computing new state
2023-07-02 10:33:38,526 [classy] Setting parameters: {'Omega_m': 0.3095545377429137, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:38,570 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.6141006941818}
2023-07-02 10:33:38,570 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:38,572 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000732519
2023-07-02 10:33:38,572 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:38,572 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:38,591 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.73234
2023-07-02 10:33:38,591 [model] Computed derived parameters: {}
2023-07-02 10:33:38,591 [mcmc] New sample, #131:
Omega_m:0.308686, b1:0.5081696
2023-07-02 10:33:38,591 [model] Posterior to be computed for parameters {'Omega_m': 0.3095545377429137, 'b1': 1.059477949518619}
2023-07-02 10:33:38,591 [prior] Evaluating prior at array([0.30955454, 1.05947795])
2023-07-02 10:33:38,591 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:38,591 [model] Got input parameters: {'Omega_m': 0.3095545377429137, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.059477949518619, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:38,592 [classy] Got parameters {'Omega_m': 0.3095545377429137, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:38,592 [classy] Re-using computed results
2023-07-02 10:33:38,592 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.6141006941818}
2023-07-02 10:33:38,592 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:38,592 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.059477949518619, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:38,592 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:38,611 [fs_likelihood.fslikelihood] Computed log-likelihood = -1335.02
2023-07-02 10:33:38,612 [model] Computed derived parameters: {}
2023-07-02 10:33:38,612 [model] Posterior to be computed for parameters {'Omega_m': 0.2878591149458605, 'b1': 0.5081695971600135}
2023-07-02 10:33:38,612 [prior] Evaluating prior at array([0.28785911, 0.5081696 ])
2023-07-02 10:33:38,612 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:38,612 [model] Got input parameters: {'Omega_m': 0.2878591149458605, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:38,612 [classy] Got parameters {'Omega_m': 0.2878591149458605, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:38,612 [classy] Computing new state
2023-07-02 10:33:38,612 [classy] Setting parameters: {'Omega_m': 0.2878591149458605, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:38,656 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.3312412248245}
2023-07-02 10:33:38,656 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:38,658 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0397943
2023-07-02 10:33:38,658 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:38,658 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:38,677 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.09554
2023-07-02 10:33:38,678 [model] Computed derived parameters: {}
2023-07-02 10:33:38,678 [model] Posterior to be computed for parameters {'Omega_m': 0.3095545377429137, 'b1': 0.345972338253289}
2023-07-02 10:33:38,678 [prior] Evaluating prior at array([0.30955454, 0.34597234])
2023-07-02 10:33:38,678 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:38,678 [model] Got input parameters: {'Omega_m': 0.3095545377429137, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.345972338253289, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:38,678 [classy] Got parameters {'Omega_m': 0.3095545377429137, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:38,678 [classy] Re-using computed results
2023-07-02 10:33:38,678 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.6141006941818}
2023-07-02 10:33:38,678 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:38,678 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.345972338253289, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:38,678 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:38,698 [fs_likelihood.fslikelihood] Computed log-likelihood = -58.3994
2023-07-02 10:33:38,698 [model] Computed derived parameters: {}
2023-07-02 10:33:38,698 [model] Posterior to be computed for parameters {'Omega_m': 0.32639637491142215, 'b1': 0.5081695971600135}
2023-07-02 10:33:38,698 [prior] Evaluating prior at array([0.32639637, 0.5081696 ])
2023-07-02 10:33:38,698 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:38,698 [model] Got input parameters: {'Omega_m': 0.32639637491142215, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:38,698 [classy] Got parameters {'Omega_m': 0.32639637491142215, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:38,698 [classy] Computing new state
2023-07-02 10:33:38,698 [classy] Setting parameters: {'Omega_m': 0.32639637491142215, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:38,743 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.61842526522761}
2023-07-02 10:33:38,743 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:38,745 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0116724
2023-07-02 10:33:38,745 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:38,745 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:38,766 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.0224156
2023-07-02 10:33:38,766 [model] Computed derived parameters: {}
2023-07-02 10:33:38,766 [model] Posterior to be computed for parameters {'Omega_m': 0.3095545377429137, 'b1': -0.09852389063680334}
2023-07-02 10:33:38,766 [prior] Evaluating prior at array([ 0.30955454, -0.09852389])
2023-07-02 10:33:38,766 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:38,767 [model] Posterior to be computed for parameters {'Omega_m': 0.28604906547070286, 'b1': 0.5081695971600135}
2023-07-02 10:33:38,767 [prior] Evaluating prior at array([0.28604907, 0.5081696 ])
2023-07-02 10:33:38,767 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:38,767 [model] Got input parameters: {'Omega_m': 0.28604906547070286, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:38,767 [classy] Got parameters {'Omega_m': 0.28604906547070286, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:38,767 [classy] Computing new state
2023-07-02 10:33:38,767 [classy] Setting parameters: {'Omega_m': 0.28604906547070286, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:38,811 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.56590854782948}
2023-07-02 10:33:38,811 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:38,813 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0460448
2023-07-02 10:33:38,813 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:38,813 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:38,833 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.46186
2023-07-02 10:33:38,833 [model] Computed derived parameters: {}
2023-07-02 10:33:38,833 [model] Posterior to be computed for parameters {'Omega_m': 0.3095545377429137, 'b1': 0.4636689578458205}
2023-07-02 10:33:38,833 [prior] Evaluating prior at array([0.30955454, 0.46366896])
2023-07-02 10:33:38,834 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:38,834 [model] Got input parameters: {'Omega_m': 0.3095545377429137, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4636689578458205, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:38,834 [classy] Got parameters {'Omega_m': 0.3095545377429137, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:38,834 [classy] Re-using computed results
2023-07-02 10:33:38,834 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.6141006941818}
2023-07-02 10:33:38,834 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:38,834 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4636689578458205, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:38,834 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:38,854 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.80514
2023-07-02 10:33:38,854 [model] Computed derived parameters: {}
2023-07-02 10:33:38,855 [model] Posterior to be computed for parameters {'Omega_m': 0.31233281003720503, 'b1': 0.5081695971600135}
2023-07-02 10:33:38,855 [prior] Evaluating prior at array([0.31233281, 0.5081696 ])
2023-07-02 10:33:38,855 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:38,855 [model] Got input parameters: {'Omega_m': 0.31233281003720503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:38,855 [classy] Got parameters {'Omega_m': 0.31233281003720503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:38,855 [classy] Computing new state
2023-07-02 10:33:38,855 [classy] Setting parameters: {'Omega_m': 0.31233281003720503, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:38,899 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.2783221716335}
2023-07-02 10:33:38,899 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:38,901 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00020377
2023-07-02 10:33:38,901 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:38,901 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:38,920 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.8563
2023-07-02 10:33:38,920 [model] Computed derived parameters: {}
2023-07-02 10:33:38,920 [mcmc] New sample, #132:
Omega_m:0.3095545, b1:0.5081696
2023-07-02 10:33:38,921 [model] Posterior to be computed for parameters {'Omega_m': 0.31233281003720503, 'b1': -0.4138841267955299}
2023-07-02 10:33:38,921 [prior] Evaluating prior at array([ 0.31233281, -0.41388413])
2023-07-02 10:33:38,921 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:38,921 [model] Posterior to be computed for parameters {'Omega_m': 0.3250331638540951, 'b1': 0.5081695971600135}
2023-07-02 10:33:38,921 [prior] Evaluating prior at array([0.32503316, 0.5081696 ])
2023-07-02 10:33:38,921 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:38,921 [model] Got input parameters: {'Omega_m': 0.3250331638540951, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:38,921 [classy] Got parameters {'Omega_m': 0.3250331638540951, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:38,921 [classy] Computing new state
2023-07-02 10:33:38,921 [classy] Setting parameters: {'Omega_m': 0.3250331638540951, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:38,965 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.77649620786406}
2023-07-02 10:33:38,965 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:38,967 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00956546
2023-07-02 10:33:38,967 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:38,967 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:38,986 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.512912
2023-07-02 10:33:38,986 [model] Computed derived parameters: {}
2023-07-02 10:33:38,986 [model] Posterior to be computed for parameters {'Omega_m': 0.31233281003720503, 'b1': -0.9759185775155055}
2023-07-02 10:33:38,986 [prior] Evaluating prior at array([ 0.31233281, -0.97591858])
2023-07-02 10:33:38,987 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:38,987 [model] Posterior to be computed for parameters {'Omega_m': 0.31253600408907434, 'b1': 0.5081695971600135}
2023-07-02 10:33:38,987 [prior] Evaluating prior at array([0.312536 , 0.5081696])
2023-07-02 10:33:38,987 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:38,987 [model] Got input parameters: {'Omega_m': 0.31253600408907434, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:38,987 [classy] Got parameters {'Omega_m': 0.31253600408907434, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:38,987 [classy] Computing new state
2023-07-02 10:33:38,987 [classy] Setting parameters: {'Omega_m': 0.31253600408907434, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:39,031 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.2538679638761}
2023-07-02 10:33:39,031 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:39,033 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000202536
2023-07-02 10:33:39,033 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:39,033 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:39,053 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.85639
2023-07-02 10:33:39,053 [model] Computed derived parameters: {}
2023-07-02 10:33:39,053 [mcmc] New sample, #133:
Omega_m:0.3123328, b1:0.5081696
2023-07-02 10:33:39,053 [model] Posterior to be computed for parameters {'Omega_m': 0.31253600408907434, 'b1': 1.381038890979747}
2023-07-02 10:33:39,053 [prior] Evaluating prior at array([0.312536 , 1.38103889])
2023-07-02 10:33:39,053 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:39,053 [model] Got input parameters: {'Omega_m': 0.31253600408907434, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.381038890979747, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:39,053 [classy] Got parameters {'Omega_m': 0.31253600408907434, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:39,053 [classy] Re-using computed results
2023-07-02 10:33:39,053 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.2538679638761}
2023-07-02 10:33:39,053 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:39,053 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.381038890979747, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:39,053 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:39,073 [fs_likelihood.fslikelihood] Computed log-likelihood = -4427.54
2023-07-02 10:33:39,073 [model] Computed derived parameters: {}
2023-07-02 10:33:39,073 [model] Posterior to be computed for parameters {'Omega_m': 0.318499954929371, 'b1': 0.5081695971600135}
2023-07-02 10:33:39,073 [prior] Evaluating prior at array([0.31849995, 0.5081696 ])
2023-07-02 10:33:39,073 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:39,073 [model] Got input parameters: {'Omega_m': 0.318499954929371, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:39,073 [classy] Got parameters {'Omega_m': 0.318499954929371, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:39,073 [classy] Computing new state
2023-07-02 10:33:39,073 [classy] Setting parameters: {'Omega_m': 0.318499954929371, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:39,117 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.54237872727163}
2023-07-02 10:33:39,117 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:39,119 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00238873
2023-07-02 10:33:39,119 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:39,119 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:39,140 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.31481
2023-07-02 10:33:39,141 [model] Computed derived parameters: {}
2023-07-02 10:33:39,141 [mcmc] New sample, #134:
Omega_m:0.312536, b1:0.5081696
2023-07-02 10:33:39,141 [model] Posterior to be computed for parameters {'Omega_m': 0.318499954929371, 'b1': 1.3604718101567963}
2023-07-02 10:33:39,141 [prior] Evaluating prior at array([0.31849995, 1.36047181])
2023-07-02 10:33:39,141 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:39,141 [model] Got input parameters: {'Omega_m': 0.318499954929371, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.3604718101567963, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:39,141 [classy] Got parameters {'Omega_m': 0.318499954929371, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:39,141 [classy] Re-using computed results
2023-07-02 10:33:39,141 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.54237872727163}
2023-07-02 10:33:39,141 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:39,141 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.3604718101567963, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:39,141 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:39,161 [fs_likelihood.fslikelihood] Computed log-likelihood = -4337.96
2023-07-02 10:33:39,161 [model] Computed derived parameters: {}
2023-07-02 10:33:39,161 [model] Posterior to be computed for parameters {'Omega_m': 0.32164195609381807, 'b1': 0.5081695971600135}
2023-07-02 10:33:39,161 [prior] Evaluating prior at array([0.32164196, 0.5081696 ])
2023-07-02 10:33:39,161 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:39,161 [model] Got input parameters: {'Omega_m': 0.32164195609381807, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:39,161 [classy] Got parameters {'Omega_m': 0.32164195609381807, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:39,161 [classy] Computing new state
2023-07-02 10:33:39,161 [classy] Setting parameters: {'Omega_m': 0.32164195609381807, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:39,205 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.1723106357125}
2023-07-02 10:33:39,205 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:39,207 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00523
2023-07-02 10:33:39,207 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:39,207 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:39,227 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.60595
2023-07-02 10:33:39,227 [model] Computed derived parameters: {}
2023-07-02 10:33:39,227 [mcmc] New sample, #135:
Omega_m:0.3185, b1:0.5081696
2023-07-02 10:33:39,227 [model] Posterior to be computed for parameters {'Omega_m': 0.32164195609381807, 'b1': -0.6305434006022945}
2023-07-02 10:33:39,227 [prior] Evaluating prior at array([ 0.32164196, -0.6305434 ])
2023-07-02 10:33:39,227 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:39,227 [model] Posterior to be computed for parameters {'Omega_m': 0.321938908311099, 'b1': 0.5081695971600135}
2023-07-02 10:33:39,227 [prior] Evaluating prior at array([0.32193891, 0.5081696 ])
2023-07-02 10:33:39,227 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:39,227 [model] Got input parameters: {'Omega_m': 0.321938908311099, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:39,227 [classy] Got parameters {'Omega_m': 0.321938908311099, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:39,227 [classy] Computing new state
2023-07-02 10:33:39,227 [classy] Setting parameters: {'Omega_m': 0.321938908311099, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:39,271 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.13750518099943}
2023-07-02 10:33:39,271 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:39,273 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00555739
2023-07-02 10:33:39,273 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:39,273 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:39,292 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.52384
2023-07-02 10:33:39,292 [model] Computed derived parameters: {}
2023-07-02 10:33:39,292 [model] Posterior to be computed for parameters {'Omega_m': 0.32164195609381807, 'b1': 1.5048113395603688}
2023-07-02 10:33:39,293 [prior] Evaluating prior at array([0.32164196, 1.50481134])
2023-07-02 10:33:39,293 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:39,293 [model] Got input parameters: {'Omega_m': 0.32164195609381807, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.5048113395603688, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:39,293 [classy] Got parameters {'Omega_m': 0.32164195609381807, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:39,293 [classy] Re-using computed results
2023-07-02 10:33:39,293 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.1723106357125}
2023-07-02 10:33:39,293 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:39,293 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.5048113395603688, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:39,293 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:39,313 [fs_likelihood.fslikelihood] Computed log-likelihood = -6707.29
2023-07-02 10:33:39,313 [model] Computed derived parameters: {}
2023-07-02 10:33:39,313 [model] Posterior to be computed for parameters {'Omega_m': 0.3281183781296848, 'b1': 0.5081695971600135}
2023-07-02 10:33:39,313 [prior] Evaluating prior at array([0.32811838, 0.5081696 ])
2023-07-02 10:33:39,313 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:39,313 [model] Got input parameters: {'Omega_m': 0.3281183781296848, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:39,313 [classy] Got parameters {'Omega_m': 0.3281183781296848, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:39,313 [classy] Computing new state
2023-07-02 10:33:39,313 [classy] Setting parameters: {'Omega_m': 0.3281183781296848, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:39,357 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.41959431406062}
2023-07-02 10:33:39,357 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:39,359 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0146276
2023-07-02 10:33:39,359 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:39,359 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:39,379 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.777284
2023-07-02 10:33:39,379 [model] Computed derived parameters: {}
2023-07-02 10:33:39,379 [mcmc] New sample, #136:
Omega_m:0.321642, b1:0.5081696
2023-07-02 10:33:39,379 [model] Posterior to be computed for parameters {'Omega_m': 0.3281183781296848, 'b1': 1.293426731876872}
2023-07-02 10:33:39,379 [prior] Evaluating prior at array([0.32811838, 1.29342673])
2023-07-02 10:33:39,379 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:39,379 [model] Got input parameters: {'Omega_m': 0.3281183781296848, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.293426731876872, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:39,379 [classy] Got parameters {'Omega_m': 0.3281183781296848, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:39,379 [classy] Re-using computed results
2023-07-02 10:33:39,379 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.41959431406062}
2023-07-02 10:33:39,379 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:39,379 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.293426731876872, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:39,379 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:39,399 [fs_likelihood.fslikelihood] Computed log-likelihood = -3764.98
2023-07-02 10:33:39,399 [model] Computed derived parameters: {}
2023-07-02 10:33:39,399 [model] Posterior to be computed for parameters {'Omega_m': 0.341637542132764, 'b1': 0.5081695971600135}
2023-07-02 10:33:39,399 [prior] Evaluating prior at array([0.34163754, 0.5081696 ])
2023-07-02 10:33:39,399 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:39,399 [model] Got input parameters: {'Omega_m': 0.341637542132764, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:39,399 [classy] Got parameters {'Omega_m': 0.341637542132764, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:39,399 [classy] Computing new state
2023-07-02 10:33:39,399 [classy] Setting parameters: {'Omega_m': 0.341637542132764, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:39,443 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.89064278887176}
2023-07-02 10:33:39,443 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:39,445 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0487687
2023-07-02 10:33:39,445 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:39,445 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:39,465 [fs_likelihood.fslikelihood] Computed log-likelihood = -9.75376
2023-07-02 10:33:39,465 [model] Computed derived parameters: {}
2023-07-02 10:33:39,465 [model] Posterior to be computed for parameters {'Omega_m': 0.3281183781296848, 'b1': -0.26403411943648536}
2023-07-02 10:33:39,465 [prior] Evaluating prior at array([ 0.32811838, -0.26403412])
2023-07-02 10:33:39,465 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:39,465 [model] Posterior to be computed for parameters {'Omega_m': 0.3489203198548997, 'b1': 0.5081695971600135}
2023-07-02 10:33:39,465 [prior] Evaluating prior at array([0.34892032, 0.5081696 ])
2023-07-02 10:33:39,466 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:39,466 [model] Got input parameters: {'Omega_m': 0.3489203198548997, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:39,466 [classy] Got parameters {'Omega_m': 0.3489203198548997, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:39,466 [classy] Computing new state
2023-07-02 10:33:39,466 [classy] Setting parameters: {'Omega_m': 0.3489203198548997, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:39,509 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.08967002476282}
2023-07-02 10:33:39,510 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:39,511 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0747812
2023-07-02 10:33:39,511 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:39,511 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:39,531 [fs_likelihood.fslikelihood] Computed log-likelihood = -16.832
2023-07-02 10:33:39,531 [model] Computed derived parameters: {}
2023-07-02 10:33:39,531 [model] Posterior to be computed for parameters {'Omega_m': 0.3281183781296848, 'b1': 0.6946306697290726}
2023-07-02 10:33:39,531 [prior] Evaluating prior at array([0.32811838, 0.69463067])
2023-07-02 10:33:39,531 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:39,531 [model] Got input parameters: {'Omega_m': 0.3281183781296848, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6946306697290726, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:39,531 [classy] Got parameters {'Omega_m': 0.3281183781296848, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:39,531 [classy] Re-using computed results
2023-07-02 10:33:39,531 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.41959431406062}
2023-07-02 10:33:39,531 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:39,531 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6946306697290726, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:39,531 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:39,551 [fs_likelihood.fslikelihood] Computed log-likelihood = -158.553
2023-07-02 10:33:39,551 [model] Computed derived parameters: {}
2023-07-02 10:33:39,551 [model] Posterior to be computed for parameters {'Omega_m': 0.322841883425129, 'b1': 0.5081695971600135}
2023-07-02 10:33:39,551 [prior] Evaluating prior at array([0.32284188, 0.5081696 ])
2023-07-02 10:33:39,551 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:39,551 [model] Got input parameters: {'Omega_m': 0.322841883425129, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:39,551 [classy] Got parameters {'Omega_m': 0.322841883425129, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:39,551 [classy] Computing new state
2023-07-02 10:33:39,551 [classy] Setting parameters: {'Omega_m': 0.322841883425129, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:39,595 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.03183507914028}
2023-07-02 10:33:39,595 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:39,597 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00661499
2023-07-02 10:33:39,597 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:39,597 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:39,617 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.25812
2023-07-02 10:33:39,617 [model] Computed derived parameters: {}
2023-07-02 10:33:39,617 [mcmc] New sample, #137:
Omega_m:0.3281184, b1:0.5081696
2023-07-02 10:33:39,617 [model] Posterior to be computed for parameters {'Omega_m': 0.322841883425129, 'b1': 0.632018246526123}
2023-07-02 10:33:39,617 [prior] Evaluating prior at array([0.32284188, 0.63201825])
2023-07-02 10:33:39,617 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:39,617 [model] Got input parameters: {'Omega_m': 0.322841883425129, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.632018246526123, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:39,617 [classy] Got parameters {'Omega_m': 0.322841883425129, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:39,617 [classy] Re-using computed results
2023-07-02 10:33:39,617 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.03183507914028}
2023-07-02 10:33:39,617 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:39,617 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.632018246526123, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:39,617 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:39,637 [fs_likelihood.fslikelihood] Computed log-likelihood = -64.1411
2023-07-02 10:33:39,637 [model] Computed derived parameters: {}
2023-07-02 10:33:39,637 [model] Posterior to be computed for parameters {'Omega_m': 0.3312337538401237, 'b1': 0.5081695971600135}
2023-07-02 10:33:39,637 [prior] Evaluating prior at array([0.33123375, 0.5081696 ])
2023-07-02 10:33:39,637 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:39,637 [model] Got input parameters: {'Omega_m': 0.3312337538401237, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:39,637 [classy] Got parameters {'Omega_m': 0.3312337538401237, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:39,637 [classy] Computing new state
2023-07-02 10:33:39,637 [classy] Setting parameters: {'Omega_m': 0.3312337538401237, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:39,681 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.06226986422362}
2023-07-02 10:33:39,681 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:39,683 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0207942
2023-07-02 10:33:39,683 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:39,683 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:39,702 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.36605
2023-07-02 10:33:39,703 [model] Computed derived parameters: {}
2023-07-02 10:33:39,703 [model] Posterior to be computed for parameters {'Omega_m': 0.322841883425129, 'b1': 0.7016928514894645}
2023-07-02 10:33:39,703 [prior] Evaluating prior at array([0.32284188, 0.70169285])
2023-07-02 10:33:39,703 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:39,703 [model] Got input parameters: {'Omega_m': 0.322841883425129, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.7016928514894645, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:39,703 [classy] Got parameters {'Omega_m': 0.322841883425129, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:39,703 [classy] Re-using computed results
2023-07-02 10:33:39,703 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.03183507914028}
2023-07-02 10:33:39,703 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:39,703 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.7016928514894645, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:39,703 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:39,723 [fs_likelihood.fslikelihood] Computed log-likelihood = -153.121
2023-07-02 10:33:39,723 [model] Computed derived parameters: {}
2023-07-02 10:33:39,723 [model] Posterior to be computed for parameters {'Omega_m': 0.30950983653367176, 'b1': 0.5081695971600135}
2023-07-02 10:33:39,723 [prior] Evaluating prior at array([0.30950984, 0.5081696 ])
2023-07-02 10:33:39,723 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:39,723 [model] Got input parameters: {'Omega_m': 0.30950983653367176, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:39,723 [classy] Got parameters {'Omega_m': 0.30950983653367176, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:39,723 [classy] Computing new state
2023-07-02 10:33:39,723 [classy] Setting parameters: {'Omega_m': 0.30950983653367176, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:39,767 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.6195255902834}
2023-07-02 10:33:39,767 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:39,769 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000748885
2023-07-02 10:33:39,769 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:39,769 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:39,789 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.72848
2023-07-02 10:33:39,789 [model] Computed derived parameters: {}
2023-07-02 10:33:39,789 [mcmc] New sample, #138:
Omega_m:0.3228419, b1:0.5081696
2023-07-02 10:33:39,789 [model] Posterior to be computed for parameters {'Omega_m': 0.30950983653367176, 'b1': 1.5322481000144177}
2023-07-02 10:33:39,789 [prior] Evaluating prior at array([0.30950984, 1.5322481 ])
2023-07-02 10:33:39,789 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:39,789 [model] Got input parameters: {'Omega_m': 0.30950983653367176, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.5322481000144177, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:39,789 [classy] Got parameters {'Omega_m': 0.30950983653367176, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:39,789 [classy] Re-using computed results
2023-07-02 10:33:39,789 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.6195255902834}
2023-07-02 10:33:39,789 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:39,789 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.5322481000144177, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:39,789 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:39,808 [fs_likelihood.fslikelihood] Computed log-likelihood = -6670.33
2023-07-02 10:33:39,808 [model] Computed derived parameters: {}
2023-07-02 10:33:39,809 [model] Posterior to be computed for parameters {'Omega_m': 0.30647785218661006, 'b1': 0.5081695971600135}
2023-07-02 10:33:39,809 [prior] Evaluating prior at array([0.30647785, 0.5081696 ])
2023-07-02 10:33:39,809 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:39,809 [model] Got input parameters: {'Omega_m': 0.30647785218661006, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:39,809 [classy] Got parameters {'Omega_m': 0.30647785218661006, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:39,809 [classy] Computing new state
2023-07-02 10:33:39,809 [classy] Setting parameters: {'Omega_m': 0.30647785218661006, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:39,853 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.989059674482}
2023-07-02 10:33:39,853 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:39,855 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00244807
2023-07-02 10:33:39,855 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:39,855 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:39,874 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.32841
2023-07-02 10:33:39,874 [model] Computed derived parameters: {}
2023-07-02 10:33:39,875 [mcmc] New sample, #139:
Omega_m:0.3095098, b1:0.5081696
2023-07-02 10:33:39,875 [model] Posterior to be computed for parameters {'Omega_m': 0.30647785218661006, 'b1': 0.8202622832984243}
2023-07-02 10:33:39,875 [prior] Evaluating prior at array([0.30647785, 0.82026228])
2023-07-02 10:33:39,875 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:39,875 [model] Got input parameters: {'Omega_m': 0.30647785218661006, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8202622832984243, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:39,875 [classy] Got parameters {'Omega_m': 0.30647785218661006, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:39,875 [classy] Re-using computed results
2023-07-02 10:33:39,875 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.989059674482}
2023-07-02 10:33:39,875 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:39,875 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8202622832984243, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:39,875 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:39,894 [fs_likelihood.fslikelihood] Computed log-likelihood = -328.481
2023-07-02 10:33:39,894 [model] Computed derived parameters: {}
2023-07-02 10:33:39,895 [model] Posterior to be computed for parameters {'Omega_m': 0.30804902887269764, 'b1': 0.5081695971600135}
2023-07-02 10:33:39,895 [prior] Evaluating prior at array([0.30804903, 0.5081696 ])
2023-07-02 10:33:39,895 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:39,895 [model] Got input parameters: {'Omega_m': 0.30804902887269764, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:39,895 [classy] Got parameters {'Omega_m': 0.30804902887269764, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:39,895 [classy] Computing new state
2023-07-02 10:33:39,895 [classy] Setting parameters: {'Omega_m': 0.30804902887269764, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:39,939 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.79716537299896}
2023-07-02 10:33:39,939 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:39,941 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00142201
2023-07-02 10:33:39,941 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:39,941 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:39,960 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.5697
2023-07-02 10:33:39,960 [model] Computed derived parameters: {}
2023-07-02 10:33:39,960 [mcmc] New sample, #140:
Omega_m:0.3064779, b1:0.5081696
2023-07-02 10:33:39,960 [model] Posterior to be computed for parameters {'Omega_m': 0.30804902887269764, 'b1': -0.15055873698430333}
2023-07-02 10:33:39,960 [prior] Evaluating prior at array([ 0.30804903, -0.15055874])
2023-07-02 10:33:39,960 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:39,961 [model] Posterior to be computed for parameters {'Omega_m': 0.2853049395846005, 'b1': 0.5081695971600135}
2023-07-02 10:33:39,961 [prior] Evaluating prior at array([0.28530494, 0.5081696 ])
2023-07-02 10:33:39,961 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:39,961 [model] Got input parameters: {'Omega_m': 0.2853049395846005, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:39,961 [classy] Got parameters {'Omega_m': 0.2853049395846005, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:39,961 [classy] Computing new state
2023-07-02 10:33:39,961 [classy] Setting parameters: {'Omega_m': 0.2853049395846005, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:40,005 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.66276563523996}
2023-07-02 10:33:40,005 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:40,006 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0487572
2023-07-02 10:33:40,006 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:40,006 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:40,026 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.0517
2023-07-02 10:33:40,026 [model] Computed derived parameters: {}
2023-07-02 10:33:40,027 [model] Posterior to be computed for parameters {'Omega_m': 0.30804902887269764, 'b1': 1.1656813949788731}
2023-07-02 10:33:40,027 [prior] Evaluating prior at array([0.30804903, 1.16568139])
2023-07-02 10:33:40,027 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:40,027 [model] Got input parameters: {'Omega_m': 0.30804902887269764, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.1656813949788731, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:40,027 [classy] Got parameters {'Omega_m': 0.30804902887269764, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:40,027 [classy] Re-using computed results
2023-07-02 10:33:40,027 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.79716537299896}
2023-07-02 10:33:40,027 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:40,027 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.1656813949788731, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:40,027 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:40,046 [fs_likelihood.fslikelihood] Computed log-likelihood = -2049.43
2023-07-02 10:33:40,046 [model] Computed derived parameters: {}
2023-07-02 10:33:40,047 [model] Posterior to be computed for parameters {'Omega_m': 0.30144741904340266, 'b1': 0.5081695971600135}
2023-07-02 10:33:40,047 [prior] Evaluating prior at array([0.30144742, 0.5081696 ])
2023-07-02 10:33:40,047 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:40,047 [model] Got input parameters: {'Omega_m': 0.30144741904340266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:40,047 [classy] Got parameters {'Omega_m': 0.30144741904340266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:40,047 [classy] Computing new state
2023-07-02 10:33:40,047 [classy] Setting parameters: {'Omega_m': 0.30144741904340266, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:40,091 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.6093035816727}
2023-07-02 10:33:40,091 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:40,093 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00788145
2023-07-02 10:33:40,093 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5081695971600135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:40,093 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:40,112 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.06428
2023-07-02 10:33:40,112 [model] Computed derived parameters: {}
2023-07-02 10:33:40,112 [model] Posterior to be computed for parameters {'Omega_m': 0.30804902887269764, 'b1': 0.5038421282358159}
2023-07-02 10:33:40,112 [prior] Evaluating prior at array([0.30804903, 0.50384213])
2023-07-02 10:33:40,112 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:40,112 [model] Got input parameters: {'Omega_m': 0.30804902887269764, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5038421282358159, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:40,112 [classy] Got parameters {'Omega_m': 0.30804902887269764, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:40,112 [classy] Re-using computed results
2023-07-02 10:33:40,112 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.79716537299896}
2023-07-02 10:33:40,112 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:40,112 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5038421282358159, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:40,112 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:40,141 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.41002
2023-07-02 10:33:40,141 [model] Computed derived parameters: {}
2023-07-02 10:33:40,141 [mcmc] New sample, #141:
Omega_m:0.308049, b1:0.5081696
2023-07-02 10:33:40,141 [model] Posterior to be computed for parameters {'Omega_m': 0.3092239989748048, 'b1': 0.5038421282358159}
2023-07-02 10:33:40,141 [prior] Evaluating prior at array([0.309224 , 0.50384213])
2023-07-02 10:33:40,141 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:40,141 [model] Got input parameters: {'Omega_m': 0.3092239989748048, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5038421282358159, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:40,141 [classy] Got parameters {'Omega_m': 0.3092239989748048, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:40,141 [classy] Computing new state
2023-07-02 10:33:40,141 [classy] Setting parameters: {'Omega_m': 0.3092239989748048, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:40,186 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.6542257251065}
2023-07-02 10:33:40,186 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:40,188 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000859445
2023-07-02 10:33:40,188 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5038421282358159, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:40,188 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:40,207 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.59115
2023-07-02 10:33:40,208 [model] Computed derived parameters: {}
2023-07-02 10:33:40,208 [mcmc] New sample, #142:
Omega_m:0.308049, b1:0.5038421
2023-07-02 10:33:40,208 [model] Posterior to be computed for parameters {'Omega_m': 0.3092239989748048, 'b1': -0.22378354407501733}
2023-07-02 10:33:40,208 [prior] Evaluating prior at array([ 0.309224 , -0.22378354])
2023-07-02 10:33:40,208 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:40,208 [model] Posterior to be computed for parameters {'Omega_m': 0.32119730621870024, 'b1': 0.5038421282358159}
2023-07-02 10:33:40,208 [prior] Evaluating prior at array([0.32119731, 0.50384213])
2023-07-02 10:33:40,208 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:40,208 [model] Got input parameters: {'Omega_m': 0.32119730621870024, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5038421282358159, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:40,208 [classy] Got parameters {'Omega_m': 0.32119730621870024, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:40,208 [classy] Computing new state
2023-07-02 10:33:40,208 [classy] Setting parameters: {'Omega_m': 0.32119730621870024, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:40,252 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.22448742399084}
2023-07-02 10:33:40,252 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:40,254 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00475854
2023-07-02 10:33:40,254 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5038421282358159, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:40,254 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:40,274 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.13102
2023-07-02 10:33:40,274 [model] Computed derived parameters: {}
2023-07-02 10:33:40,275 [mcmc] New sample, #143:
Omega_m:0.309224, b1:0.5038421
2023-07-02 10:33:40,275 [model] Posterior to be computed for parameters {'Omega_m': 0.32119730621870024, 'b1': 0.5083995069720371}
2023-07-02 10:33:40,275 [prior] Evaluating prior at array([0.32119731, 0.50839951])
2023-07-02 10:33:40,275 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:40,275 [model] Got input parameters: {'Omega_m': 0.32119730621870024, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:40,275 [classy] Got parameters {'Omega_m': 0.32119730621870024, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:40,275 [classy] Re-using computed results
2023-07-02 10:33:40,275 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.22448742399084}
2023-07-02 10:33:40,275 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:40,275 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:40,275 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:40,294 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.69941
2023-07-02 10:33:40,295 [model] Computed derived parameters: {}
2023-07-02 10:33:40,295 [mcmc] New sample, #144:
Omega_m:0.3211973, b1:0.5038421
2023-07-02 10:33:40,295 [model] Posterior to be computed for parameters {'Omega_m': 0.29913903175634593, 'b1': 0.5083995069720371}
2023-07-02 10:33:40,295 [prior] Evaluating prior at array([0.29913903, 0.50839951])
2023-07-02 10:33:40,295 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:40,295 [model] Got input parameters: {'Omega_m': 0.29913903175634593, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:40,295 [classy] Got parameters {'Omega_m': 0.29913903175634593, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:40,295 [classy] Computing new state
2023-07-02 10:33:40,295 [classy] Setting parameters: {'Omega_m': 0.29913903175634593, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:40,339 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.89699225066107}
2023-07-02 10:33:40,339 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:40,341 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0114961
2023-07-02 10:33:40,341 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:40,341 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:40,360 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.258075
2023-07-02 10:33:40,360 [model] Computed derived parameters: {}
2023-07-02 10:33:40,361 [model] Posterior to be computed for parameters {'Omega_m': 0.32119730621870024, 'b1': 1.0812272564714172}
2023-07-02 10:33:40,361 [prior] Evaluating prior at array([0.32119731, 1.08122726])
2023-07-02 10:33:40,361 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:40,361 [model] Got input parameters: {'Omega_m': 0.32119730621870024, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.0812272564714172, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:40,361 [classy] Got parameters {'Omega_m': 0.32119730621870024, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:40,361 [classy] Re-using computed results
2023-07-02 10:33:40,361 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.22448742399084}
2023-07-02 10:33:40,361 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:40,361 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.0812272564714172, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:40,361 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:40,382 [fs_likelihood.fslikelihood] Computed log-likelihood = -1634.06
2023-07-02 10:33:40,382 [model] Computed derived parameters: {}
2023-07-02 10:33:40,382 [model] Posterior to be computed for parameters {'Omega_m': 0.34769066838834484, 'b1': 0.5083995069720371}
2023-07-02 10:33:40,382 [prior] Evaluating prior at array([0.34769067, 0.50839951])
2023-07-02 10:33:40,382 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:40,382 [model] Got input parameters: {'Omega_m': 0.34769066838834484, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:40,382 [classy] Got parameters {'Omega_m': 0.34769066838834484, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:40,382 [classy] Computing new state
2023-07-02 10:33:40,382 [classy] Setting parameters: {'Omega_m': 0.34769066838834484, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:40,426 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.22382506571012}
2023-07-02 10:33:40,426 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:40,428 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0700324
2023-07-02 10:33:40,428 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:40,428 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:40,447 [fs_likelihood.fslikelihood] Computed log-likelihood = -15.6212
2023-07-02 10:33:40,447 [model] Computed derived parameters: {}
2023-07-02 10:33:40,447 [model] Posterior to be computed for parameters {'Omega_m': 0.32119730621870024, 'b1': 0.8169005672647267}
2023-07-02 10:33:40,447 [prior] Evaluating prior at array([0.32119731, 0.81690057])
2023-07-02 10:33:40,448 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:40,448 [model] Got input parameters: {'Omega_m': 0.32119730621870024, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8169005672647267, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:40,448 [classy] Got parameters {'Omega_m': 0.32119730621870024, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:40,448 [classy] Re-using computed results
2023-07-02 10:33:40,448 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.22448742399084}
2023-07-02 10:33:40,448 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:40,448 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8169005672647267, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:40,448 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:40,467 [fs_likelihood.fslikelihood] Computed log-likelihood = -396.012
2023-07-02 10:33:40,467 [model] Computed derived parameters: {}
2023-07-02 10:33:40,467 [model] Posterior to be computed for parameters {'Omega_m': 0.33142017691773556, 'b1': 0.5083995069720371}
2023-07-02 10:33:40,467 [prior] Evaluating prior at array([0.33142018, 0.50839951])
2023-07-02 10:33:40,467 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:40,467 [model] Got input parameters: {'Omega_m': 0.33142017691773556, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:40,467 [classy] Got parameters {'Omega_m': 0.33142017691773556, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:40,467 [classy] Computing new state
2023-07-02 10:33:40,467 [classy] Setting parameters: {'Omega_m': 0.33142017691773556, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:40,511 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.04098393235012}
2023-07-02 10:33:40,511 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:40,513 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0211963
2023-07-02 10:33:40,513 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:40,513 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:40,533 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.52042
2023-07-02 10:33:40,533 [model] Computed derived parameters: {}
2023-07-02 10:33:40,533 [model] Posterior to be computed for parameters {'Omega_m': 0.32119730621870024, 'b1': 0.17365251849692215}
2023-07-02 10:33:40,533 [prior] Evaluating prior at array([0.32119731, 0.17365252])
2023-07-02 10:33:40,533 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:40,533 [model] Got input parameters: {'Omega_m': 0.32119730621870024, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.17365251849692215, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:40,534 [classy] Got parameters {'Omega_m': 0.32119730621870024, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:40,534 [classy] Re-using computed results
2023-07-02 10:33:40,534 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.22448742399084}
2023-07-02 10:33:40,534 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:40,534 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.17365251849692215, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:40,534 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:40,553 [fs_likelihood.fslikelihood] Computed log-likelihood = -190.986
2023-07-02 10:33:40,553 [model] Computed derived parameters: {}
2023-07-02 10:33:40,553 [model] Posterior to be computed for parameters {'Omega_m': 0.3499952494680272, 'b1': 0.5083995069720371}
2023-07-02 10:33:40,553 [prior] Evaluating prior at array([0.34999525, 0.50839951])
2023-07-02 10:33:40,554 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:40,554 [model] Got input parameters: {'Omega_m': 0.3499952494680272, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:40,554 [classy] Got parameters {'Omega_m': 0.3499952494680272, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:40,554 [classy] Computing new state
2023-07-02 10:33:40,554 [classy] Setting parameters: {'Omega_m': 0.3499952494680272, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:40,598 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.97274649337882}
2023-07-02 10:33:40,598 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:40,600 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0790493
2023-07-02 10:33:40,600 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:40,600 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:40,619 [fs_likelihood.fslikelihood] Computed log-likelihood = -18.1108
2023-07-02 10:33:40,620 [model] Computed derived parameters: {}
2023-07-02 10:33:40,620 [model] Posterior to be computed for parameters {'Omega_m': 0.32119730621870024, 'b1': 0.6691389895477349}
2023-07-02 10:33:40,620 [prior] Evaluating prior at array([0.32119731, 0.66913899])
2023-07-02 10:33:40,620 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:40,620 [model] Got input parameters: {'Omega_m': 0.32119730621870024, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6691389895477349, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:40,620 [classy] Got parameters {'Omega_m': 0.32119730621870024, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:40,620 [classy] Re-using computed results
2023-07-02 10:33:40,620 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.22448742399084}
2023-07-02 10:33:40,620 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:40,620 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6691389895477349, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:40,620 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:40,640 [fs_likelihood.fslikelihood] Computed log-likelihood = -102.117
2023-07-02 10:33:40,640 [model] Computed derived parameters: {}
2023-07-02 10:33:40,640 [model] Posterior to be computed for parameters {'Omega_m': 0.333706756258011, 'b1': 0.5083995069720371}
2023-07-02 10:33:40,640 [prior] Evaluating prior at array([0.33370676, 0.50839951])
2023-07-02 10:33:40,641 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:40,641 [model] Got input parameters: {'Omega_m': 0.333706756258011, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:40,641 [classy] Got parameters {'Omega_m': 0.333706756258011, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:40,641 [classy] Computing new state
2023-07-02 10:33:40,641 [classy] Setting parameters: {'Omega_m': 0.333706756258011, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:40,685 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.78079224172563}
2023-07-02 10:33:40,685 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:40,687 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0264278
2023-07-02 10:33:40,687 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:40,687 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:40,706 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.88794
2023-07-02 10:33:40,706 [model] Computed derived parameters: {}
2023-07-02 10:33:40,706 [model] Posterior to be computed for parameters {'Omega_m': 0.32119730621870024, 'b1': 1.7794815984096837}
2023-07-02 10:33:40,706 [prior] Evaluating prior at array([0.32119731, 1.7794816 ])
2023-07-02 10:33:40,706 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:40,706 [model] Got input parameters: {'Omega_m': 0.32119730621870024, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.7794815984096837, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:40,707 [classy] Got parameters {'Omega_m': 0.32119730621870024, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:40,707 [classy] Re-using computed results
2023-07-02 10:33:40,707 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.22448742399084}
2023-07-02 10:33:40,707 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:40,707 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.7794815984096837, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:40,707 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:40,727 [fs_likelihood.fslikelihood] Computed log-likelihood = -13067.1
2023-07-02 10:33:40,727 [model] Computed derived parameters: {}
2023-07-02 10:33:40,727 [model] Posterior to be computed for parameters {'Omega_m': 0.3132971929863268, 'b1': 0.5083995069720371}
2023-07-02 10:33:40,727 [prior] Evaluating prior at array([0.31329719, 0.50839951])
2023-07-02 10:33:40,727 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:40,727 [model] Got input parameters: {'Omega_m': 0.3132971929863268, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:40,727 [classy] Got parameters {'Omega_m': 0.3132971929863268, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:40,727 [classy] Computing new state
2023-07-02 10:33:40,727 [classy] Setting parameters: {'Omega_m': 0.3132971929863268, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:40,771 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.16238213420274}
2023-07-02 10:33:40,771 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:40,773 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000242868
2023-07-02 10:33:40,773 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:40,773 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:40,793 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.83986
2023-07-02 10:33:40,793 [model] Computed derived parameters: {}
2023-07-02 10:33:40,793 [mcmc] New sample, #145:
Omega_m:0.3211973, b1:0.5083995
2023-07-02 10:33:40,793 [model] Posterior to be computed for parameters {'Omega_m': 0.3132971929863268, 'b1': -0.09513429411065599}
2023-07-02 10:33:40,793 [prior] Evaluating prior at array([ 0.31329719, -0.09513429])
2023-07-02 10:33:40,793 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:40,793 [model] Posterior to be computed for parameters {'Omega_m': 0.3186140866614561, 'b1': 0.5083995069720371}
2023-07-02 10:33:40,794 [prior] Evaluating prior at array([0.31861409, 0.50839951])
2023-07-02 10:33:40,794 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:40,794 [model] Got input parameters: {'Omega_m': 0.3186140866614561, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:40,794 [classy] Got parameters {'Omega_m': 0.3186140866614561, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:40,794 [classy] Computing new state
2023-07-02 10:33:40,794 [classy] Setting parameters: {'Omega_m': 0.3186140866614561, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:40,838 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.52887842403229}
2023-07-02 10:33:40,838 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:40,840 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00247185
2023-07-02 10:33:40,840 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:40,840 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:40,859 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.27574
2023-07-02 10:33:40,859 [model] Computed derived parameters: {}
2023-07-02 10:33:40,859 [model] Posterior to be computed for parameters {'Omega_m': 0.3132971929863268, 'b1': 0.9591889722406497}
2023-07-02 10:33:40,860 [prior] Evaluating prior at array([0.31329719, 0.95918897])
2023-07-02 10:33:40,860 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:40,860 [model] Got input parameters: {'Omega_m': 0.3132971929863268, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.9591889722406497, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:40,860 [classy] Got parameters {'Omega_m': 0.3132971929863268, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:40,860 [classy] Re-using computed results
2023-07-02 10:33:40,860 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.16238213420274}
2023-07-02 10:33:40,860 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:40,860 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.9591889722406497, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:40,860 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:40,880 [fs_likelihood.fslikelihood] Computed log-likelihood = -852.158
2023-07-02 10:33:40,880 [model] Computed derived parameters: {}
2023-07-02 10:33:40,880 [model] Posterior to be computed for parameters {'Omega_m': 0.32971730302333524, 'b1': 0.5083995069720371}
2023-07-02 10:33:40,880 [prior] Evaluating prior at array([0.3297173 , 0.50839951])
2023-07-02 10:33:40,881 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:40,881 [model] Got input parameters: {'Omega_m': 0.32971730302333524, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:40,881 [classy] Got parameters {'Omega_m': 0.32971730302333524, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:40,881 [classy] Computing new state
2023-07-02 10:33:40,881 [classy] Setting parameters: {'Omega_m': 0.32971730302333524, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:40,924 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.2358093808039}
2023-07-02 10:33:40,925 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:40,927 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0176621
2023-07-02 10:33:40,927 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:40,927 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:40,946 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.60262
2023-07-02 10:33:40,946 [model] Computed derived parameters: {}
2023-07-02 10:33:40,946 [model] Posterior to be computed for parameters {'Omega_m': 0.3132971929863268, 'b1': 0.9383162136584628}
2023-07-02 10:33:40,946 [prior] Evaluating prior at array([0.31329719, 0.93831621])
2023-07-02 10:33:40,947 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:40,947 [model] Got input parameters: {'Omega_m': 0.3132971929863268, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.9383162136584628, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:40,947 [classy] Got parameters {'Omega_m': 0.3132971929863268, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:40,947 [classy] Re-using computed results
2023-07-02 10:33:40,947 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.16238213420274}
2023-07-02 10:33:40,947 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:40,947 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.9383162136584628, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:40,947 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:40,966 [fs_likelihood.fslikelihood] Computed log-likelihood = -761.674
2023-07-02 10:33:40,966 [model] Computed derived parameters: {}
2023-07-02 10:33:40,966 [model] Posterior to be computed for parameters {'Omega_m': 0.2925700401761634, 'b1': 0.5083995069720371}
2023-07-02 10:33:40,966 [prior] Evaluating prior at array([0.29257004, 0.50839951])
2023-07-02 10:33:40,966 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:40,966 [model] Got input parameters: {'Omega_m': 0.2925700401761634, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:40,966 [classy] Got parameters {'Omega_m': 0.2925700401761634, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:40,966 [classy] Computing new state
2023-07-02 10:33:40,966 [classy] Setting parameters: {'Omega_m': 0.2925700401761634, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:41,011 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.72642177302845}
2023-07-02 10:33:41,011 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:41,012 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0257805
2023-07-02 10:33:41,012 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:41,012 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:41,032 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.95645
2023-07-02 10:33:41,033 [model] Computed derived parameters: {}
2023-07-02 10:33:41,033 [model] Posterior to be computed for parameters {'Omega_m': 0.3132971929863268, 'b1': 1.1049067949901812}
2023-07-02 10:33:41,033 [prior] Evaluating prior at array([0.31329719, 1.10490679])
2023-07-02 10:33:41,033 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:41,033 [model] Got input parameters: {'Omega_m': 0.3132971929863268, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.1049067949901812, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:41,033 [classy] Got parameters {'Omega_m': 0.3132971929863268, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:41,033 [classy] Re-using computed results
2023-07-02 10:33:41,033 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.16238213420274}
2023-07-02 10:33:41,033 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:41,033 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.1049067949901812, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:41,033 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:41,053 [fs_likelihood.fslikelihood] Computed log-likelihood = -1680.98
2023-07-02 10:33:41,053 [model] Computed derived parameters: {}
2023-07-02 10:33:41,053 [model] Posterior to be computed for parameters {'Omega_m': 0.31654590483335854, 'b1': 0.5083995069720371}
2023-07-02 10:33:41,053 [prior] Evaluating prior at array([0.3165459 , 0.50839951])
2023-07-02 10:33:41,053 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:41,053 [model] Got input parameters: {'Omega_m': 0.31654590483335854, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:41,053 [classy] Got parameters {'Omega_m': 0.31654590483335854, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:41,053 [classy] Computing new state
2023-07-02 10:33:41,053 [classy] Setting parameters: {'Omega_m': 0.31654590483335854, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:41,100 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.77416695455352}
2023-07-02 10:33:41,100 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:41,102 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00120401
2023-07-02 10:33:41,102 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:41,102 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:41,126 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.59469
2023-07-02 10:33:41,127 [model] Computed derived parameters: {}
2023-07-02 10:33:41,127 [mcmc] New sample, #146:
Omega_m:0.3132972, b1:0.5083995
2023-07-02 10:33:41,127 [model] Posterior to be computed for parameters {'Omega_m': 0.31654590483335854, 'b1': 0.22505906937006553}
2023-07-02 10:33:41,127 [prior] Evaluating prior at array([0.3165459 , 0.22505907])
2023-07-02 10:33:41,127 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:41,127 [model] Got input parameters: {'Omega_m': 0.31654590483335854, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.22505906937006553, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:41,127 [classy] Got parameters {'Omega_m': 0.31654590483335854, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:41,127 [classy] Re-using computed results
2023-07-02 10:33:41,127 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.77416695455352}
2023-07-02 10:33:41,127 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:41,127 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.22505906937006553, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:41,128 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:41,156 [fs_likelihood.fslikelihood] Computed log-likelihood = -147.931
2023-07-02 10:33:41,156 [model] Computed derived parameters: {}
2023-07-02 10:33:41,156 [model] Posterior to be computed for parameters {'Omega_m': 0.3133330711121664, 'b1': 0.5083995069720371}
2023-07-02 10:33:41,156 [prior] Evaluating prior at array([0.31333307, 0.50839951])
2023-07-02 10:33:41,157 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:41,157 [model] Got input parameters: {'Omega_m': 0.3133330711121664, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:41,157 [classy] Got parameters {'Omega_m': 0.3133330711121664, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:41,157 [classy] Computing new state
2023-07-02 10:33:41,157 [classy] Setting parameters: {'Omega_m': 0.3133330711121664, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:41,208 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.15807323825592}
2023-07-02 10:33:41,208 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:41,210 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000246523
2023-07-02 10:33:41,210 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:41,210 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:41,233 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.83885
2023-07-02 10:33:41,233 [model] Computed derived parameters: {}
2023-07-02 10:33:41,233 [mcmc] New sample, #147:
Omega_m:0.3165459, b1:0.5083995
2023-07-02 10:33:41,233 [model] Posterior to be computed for parameters {'Omega_m': 0.3133330711121664, 'b1': 1.6851734476540072}
2023-07-02 10:33:41,233 [prior] Evaluating prior at array([0.31333307, 1.68517345])
2023-07-02 10:33:41,234 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:41,234 [model] Got input parameters: {'Omega_m': 0.3133330711121664, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.6851734476540072, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:41,234 [classy] Got parameters {'Omega_m': 0.3133330711121664, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:41,234 [classy] Re-using computed results
2023-07-02 10:33:41,234 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.15807323825592}
2023-07-02 10:33:41,234 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:41,234 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.6851734476540072, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:41,234 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:41,255 [fs_likelihood.fslikelihood] Computed log-likelihood = -10044
2023-07-02 10:33:41,255 [model] Computed derived parameters: {}
2023-07-02 10:33:41,255 [model] Posterior to be computed for parameters {'Omega_m': 0.33407482004466765, 'b1': 0.5083995069720371}
2023-07-02 10:33:41,255 [prior] Evaluating prior at array([0.33407482, 0.50839951])
2023-07-02 10:33:41,255 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:41,255 [model] Got input parameters: {'Omega_m': 0.33407482004466765, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:41,255 [classy] Got parameters {'Omega_m': 0.33407482004466765, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:41,255 [classy] Computing new state
2023-07-02 10:33:41,255 [classy] Setting parameters: {'Omega_m': 0.33407482004466765, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:41,304 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.73906020998206}
2023-07-02 10:33:41,304 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:41,306 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0273214
2023-07-02 10:33:41,306 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:41,306 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:41,326 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.12254
2023-07-02 10:33:41,326 [model] Computed derived parameters: {}
2023-07-02 10:33:41,326 [model] Posterior to be computed for parameters {'Omega_m': 0.3133330711121664, 'b1': -0.5370110503918133}
2023-07-02 10:33:41,326 [prior] Evaluating prior at array([ 0.31333307, -0.53701105])
2023-07-02 10:33:41,326 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:41,326 [model] Posterior to be computed for parameters {'Omega_m': 0.31532556961708574, 'b1': 0.5083995069720371}
2023-07-02 10:33:41,326 [prior] Evaluating prior at array([0.31532557, 0.50839951])
2023-07-02 10:33:41,327 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:41,327 [model] Got input parameters: {'Omega_m': 0.31532556961708574, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:41,327 [classy] Got parameters {'Omega_m': 0.31532556961708574, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:41,327 [classy] Computing new state
2023-07-02 10:33:41,327 [classy] Setting parameters: {'Omega_m': 0.31532556961708574, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:41,371 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.91956828541944}
2023-07-02 10:33:41,371 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:41,372 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000694146
2023-07-02 10:33:41,372 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:41,372 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:41,393 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.72345
2023-07-02 10:33:41,393 [model] Computed derived parameters: {}
2023-07-02 10:33:41,393 [mcmc] New sample, #148:
Omega_m:0.3133331, b1:0.5083995
2023-07-02 10:33:41,394 [model] Posterior to be computed for parameters {'Omega_m': 0.31532556961708574, 'b1': 1.4445425315185683}
2023-07-02 10:33:41,394 [prior] Evaluating prior at array([0.31532557, 1.44454253])
2023-07-02 10:33:41,394 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:41,394 [model] Got input parameters: {'Omega_m': 0.31532556961708574, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.4445425315185683, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:41,394 [classy] Got parameters {'Omega_m': 0.31532556961708574, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:41,394 [classy] Re-using computed results
2023-07-02 10:33:41,394 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.91956828541944}
2023-07-02 10:33:41,394 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:41,394 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.4445425315185683, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:41,394 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:41,414 [fs_likelihood.fslikelihood] Computed log-likelihood = -5441.92
2023-07-02 10:33:41,414 [model] Computed derived parameters: {}
2023-07-02 10:33:41,414 [model] Posterior to be computed for parameters {'Omega_m': 0.3315404286579993, 'b1': 0.5083995069720371}
2023-07-02 10:33:41,414 [prior] Evaluating prior at array([0.33154043, 0.50839951])
2023-07-02 10:33:41,414 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:41,414 [model] Got input parameters: {'Omega_m': 0.3315404286579993, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:41,414 [classy] Got parameters {'Omega_m': 0.3315404286579993, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:41,414 [classy] Computing new state
2023-07-02 10:33:41,414 [classy] Setting parameters: {'Omega_m': 0.3315404286579993, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:41,459 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.02726263921818}
2023-07-02 10:33:41,459 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:41,460 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0214575
2023-07-02 10:33:41,460 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:41,460 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:41,480 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.58848
2023-07-02 10:33:41,480 [model] Computed derived parameters: {}
2023-07-02 10:33:41,480 [model] Posterior to be computed for parameters {'Omega_m': 0.31532556961708574, 'b1': 0.6456473276969827}
2023-07-02 10:33:41,480 [prior] Evaluating prior at array([0.31532557, 0.64564733])
2023-07-02 10:33:41,480 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:41,480 [model] Got input parameters: {'Omega_m': 0.31532556961708574, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6456473276969827, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:41,480 [classy] Got parameters {'Omega_m': 0.31532556961708574, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:41,480 [classy] Re-using computed results
2023-07-02 10:33:41,480 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.91956828541944}
2023-07-02 10:33:41,480 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:41,480 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6456473276969827, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:41,480 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:41,501 [fs_likelihood.fslikelihood] Computed log-likelihood = -63.3082
2023-07-02 10:33:41,501 [model] Computed derived parameters: {}
2023-07-02 10:33:41,501 [model] Posterior to be computed for parameters {'Omega_m': 0.2995449599955176, 'b1': 0.5083995069720371}
2023-07-02 10:33:41,501 [prior] Evaluating prior at array([0.29954496, 0.50839951])
2023-07-02 10:33:41,501 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:41,501 [model] Got input parameters: {'Omega_m': 0.2995449599955176, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:41,501 [classy] Got parameters {'Omega_m': 0.2995449599955176, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:41,501 [classy] Computing new state
2023-07-02 10:33:41,501 [classy] Setting parameters: {'Omega_m': 0.2995449599955176, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:41,545 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.84626130589155}
2023-07-02 10:33:41,545 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:41,547 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0108085
2023-07-02 10:33:41,547 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:41,547 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:41,567 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.41478
2023-07-02 10:33:41,567 [model] Computed derived parameters: {}
2023-07-02 10:33:41,567 [model] Posterior to be computed for parameters {'Omega_m': 0.31532556961708574, 'b1': -0.2385144646084778}
2023-07-02 10:33:41,567 [prior] Evaluating prior at array([ 0.31532557, -0.23851446])
2023-07-02 10:33:41,567 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:41,567 [model] Posterior to be computed for parameters {'Omega_m': 0.3041229128029593, 'b1': 0.5083995069720371}
2023-07-02 10:33:41,567 [prior] Evaluating prior at array([0.30412291, 0.50839951])
2023-07-02 10:33:41,568 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:41,568 [model] Got input parameters: {'Omega_m': 0.3041229128029593, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:41,568 [classy] Got parameters {'Omega_m': 0.3041229128029593, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:41,568 [classy] Computing new state
2023-07-02 10:33:41,568 [classy] Setting parameters: {'Omega_m': 0.3041229128029593, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:41,612 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.27830137061872}
2023-07-02 10:33:41,612 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:41,614 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00458008
2023-07-02 10:33:41,614 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:41,614 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:41,634 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.84412
2023-07-02 10:33:41,634 [model] Computed derived parameters: {}
2023-07-02 10:33:41,634 [model] Posterior to be computed for parameters {'Omega_m': 0.31532556961708574, 'b1': 0.6825183886216427}
2023-07-02 10:33:41,634 [prior] Evaluating prior at array([0.31532557, 0.68251839])
2023-07-02 10:33:41,635 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:41,635 [model] Got input parameters: {'Omega_m': 0.31532556961708574, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6825183886216427, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:41,635 [classy] Got parameters {'Omega_m': 0.31532556961708574, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:41,635 [classy] Re-using computed results
2023-07-02 10:33:41,635 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.91956828541944}
2023-07-02 10:33:41,635 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:41,635 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6825183886216427, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:41,635 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:41,655 [fs_likelihood.fslikelihood] Computed log-likelihood = -104.735
2023-07-02 10:33:41,655 [model] Computed derived parameters: {}
2023-07-02 10:33:41,655 [model] Posterior to be computed for parameters {'Omega_m': 0.305204922886048, 'b1': 0.5083995069720371}
2023-07-02 10:33:41,655 [prior] Evaluating prior at array([0.30520492, 0.50839951])
2023-07-02 10:33:41,655 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:41,655 [model] Got input parameters: {'Omega_m': 0.305204922886048, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:41,655 [classy] Got parameters {'Omega_m': 0.305204922886048, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:41,655 [classy] Computing new state
2023-07-02 10:33:41,655 [classy] Setting parameters: {'Omega_m': 0.305204922886048, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:41,700 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.1451618973536}
2023-07-02 10:33:41,700 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:41,702 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00351136
2023-07-02 10:33:41,702 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:41,702 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:41,721 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.09125
2023-07-02 10:33:41,721 [model] Computed derived parameters: {}
2023-07-02 10:33:41,721 [model] Posterior to be computed for parameters {'Omega_m': 0.31532556961708574, 'b1': 0.8107538318824471}
2023-07-02 10:33:41,721 [prior] Evaluating prior at array([0.31532557, 0.81075383])
2023-07-02 10:33:41,721 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:41,721 [model] Got input parameters: {'Omega_m': 0.31532556961708574, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8107538318824471, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:41,721 [classy] Got parameters {'Omega_m': 0.31532556961708574, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:41,721 [classy] Re-using computed results
2023-07-02 10:33:41,722 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.91956828541944}
2023-07-02 10:33:41,722 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:41,722 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8107538318824471, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:41,722 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:41,742 [fs_likelihood.fslikelihood] Computed log-likelihood = -348.197
2023-07-02 10:33:41,742 [model] Computed derived parameters: {}
2023-07-02 10:33:41,742 [model] Posterior to be computed for parameters {'Omega_m': 0.3114754754656021, 'b1': 0.5083995069720371}
2023-07-02 10:33:41,742 [prior] Evaluating prior at array([0.31147548, 0.50839951])
2023-07-02 10:33:41,742 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:41,742 [model] Got input parameters: {'Omega_m': 0.3114754754656021, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:41,742 [classy] Got parameters {'Omega_m': 0.3114754754656021, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:41,742 [classy] Computing new state
2023-07-02 10:33:41,743 [classy] Setting parameters: {'Omega_m': 0.3114754754656021, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:41,787 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.38165688019052}
2023-07-02 10:33:41,787 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:41,789 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000264898
2023-07-02 10:33:41,789 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:41,789 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:41,809 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.84052
2023-07-02 10:33:41,809 [model] Computed derived parameters: {}
2023-07-02 10:33:41,809 [mcmc] New sample, #149:
Omega_m:0.3153256, b1:0.5083995
2023-07-02 10:33:41,809 [model] Posterior to be computed for parameters {'Omega_m': 0.3114754754656021, 'b1': 0.6988804167670525}
2023-07-02 10:33:41,809 [prior] Evaluating prior at array([0.31147548, 0.69888042])
2023-07-02 10:33:41,809 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:41,809 [model] Got input parameters: {'Omega_m': 0.3114754754656021, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6988804167670525, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:41,809 [classy] Got parameters {'Omega_m': 0.3114754754656021, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:41,809 [classy] Re-using computed results
2023-07-02 10:33:41,809 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.38165688019052}
2023-07-02 10:33:41,809 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:41,809 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6988804167670525, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:41,809 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:41,831 [fs_likelihood.fslikelihood] Computed log-likelihood = -116.695
2023-07-02 10:33:41,831 [model] Computed derived parameters: {}
2023-07-02 10:33:41,831 [model] Posterior to be computed for parameters {'Omega_m': 0.3168658773965015, 'b1': 0.5083995069720371}
2023-07-02 10:33:41,831 [prior] Evaluating prior at array([0.31686588, 0.50839951])
2023-07-02 10:33:41,832 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:41,832 [model] Got input parameters: {'Omega_m': 0.3168658773965015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:41,832 [classy] Got parameters {'Omega_m': 0.3168658773965015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:41,832 [classy] Computing new state
2023-07-02 10:33:41,832 [classy] Setting parameters: {'Omega_m': 0.3168658773965015, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:41,882 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.73612504876297}
2023-07-02 10:33:41,882 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:41,884 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00136708
2023-07-02 10:33:41,884 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:41,884 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:41,908 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.55363
2023-07-02 10:33:41,908 [model] Computed derived parameters: {}
2023-07-02 10:33:41,908 [mcmc] New sample, #150:
Omega_m:0.3114755, b1:0.5083995
2023-07-02 10:33:41,908 [model] Posterior to be computed for parameters {'Omega_m': 0.3168658773965015, 'b1': 0.8142053456510582}
2023-07-02 10:33:41,908 [prior] Evaluating prior at array([0.31686588, 0.81420535])
2023-07-02 10:33:41,908 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:41,908 [model] Got input parameters: {'Omega_m': 0.3168658773965015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8142053456510582, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:41,908 [classy] Got parameters {'Omega_m': 0.3168658773965015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:41,908 [classy] Re-using computed results
2023-07-02 10:33:41,908 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.73612504876297}
2023-07-02 10:33:41,908 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:41,908 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8142053456510582, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:41,908 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:41,930 [fs_likelihood.fslikelihood] Computed log-likelihood = -365.192
2023-07-02 10:33:41,930 [model] Computed derived parameters: {}
2023-07-02 10:33:41,931 [model] Posterior to be computed for parameters {'Omega_m': 0.32471598044951794, 'b1': 0.5083995069720371}
2023-07-02 10:33:41,931 [prior] Evaluating prior at array([0.32471598, 0.50839951])
2023-07-02 10:33:41,931 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:41,931 [model] Got input parameters: {'Omega_m': 0.32471598044951794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:41,931 [classy] Got parameters {'Omega_m': 0.32471598044951794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:41,931 [classy] Computing new state
2023-07-02 10:33:41,931 [classy] Setting parameters: {'Omega_m': 0.32471598044951794, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:41,982 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.81336166604964}
2023-07-02 10:33:41,982 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:41,985 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00910491
2023-07-02 10:33:41,985 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:41,985 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:42,007 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.596353
2023-07-02 10:33:42,007 [model] Computed derived parameters: {}
2023-07-02 10:33:42,007 [model] Posterior to be computed for parameters {'Omega_m': 0.3168658773965015, 'b1': 0.8186590456575431}
2023-07-02 10:33:42,008 [prior] Evaluating prior at array([0.31686588, 0.81865905])
2023-07-02 10:33:42,008 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:42,008 [model] Got input parameters: {'Omega_m': 0.3168658773965015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8186590456575431, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:42,008 [classy] Got parameters {'Omega_m': 0.3168658773965015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:42,008 [classy] Re-using computed results
2023-07-02 10:33:42,008 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.73612504876297}
2023-07-02 10:33:42,008 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:42,008 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8186590456575431, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:42,008 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:42,031 [fs_likelihood.fslikelihood] Computed log-likelihood = -377.131
2023-07-02 10:33:42,031 [model] Computed derived parameters: {}
2023-07-02 10:33:42,031 [model] Posterior to be computed for parameters {'Omega_m': 0.3147684261827027, 'b1': 0.5083995069720371}
2023-07-02 10:33:42,031 [prior] Evaluating prior at array([0.31476843, 0.50839951])
2023-07-02 10:33:42,031 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:42,031 [model] Got input parameters: {'Omega_m': 0.3147684261827027, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:42,032 [classy] Got parameters {'Omega_m': 0.3147684261827027, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:42,032 [classy] Computing new state
2023-07-02 10:33:42,032 [classy] Setting parameters: {'Omega_m': 0.3147684261827027, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:42,081 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.9861199244786}
2023-07-02 10:33:42,082 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:42,083 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000520692
2023-07-02 10:33:42,084 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:42,084 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:42,106 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.76756
2023-07-02 10:33:42,106 [model] Computed derived parameters: {}
2023-07-02 10:33:42,106 [mcmc] New sample, #151:
Omega_m:0.3168659, b1:0.5083995
2023-07-02 10:33:42,106 [model] Posterior to be computed for parameters {'Omega_m': 0.3147684261827027, 'b1': 0.4834219915736692}
2023-07-02 10:33:42,106 [prior] Evaluating prior at array([0.31476843, 0.48342199])
2023-07-02 10:33:42,106 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:42,106 [model] Got input parameters: {'Omega_m': 0.3147684261827027, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4834219915736692, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:42,106 [classy] Got parameters {'Omega_m': 0.3147684261827027, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:42,106 [classy] Re-using computed results
2023-07-02 10:33:42,106 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.9861199244786}
2023-07-02 10:33:42,106 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:42,106 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4834219915736692, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:42,106 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:42,131 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.12869
2023-07-02 10:33:42,131 [model] Computed derived parameters: {}
2023-07-02 10:33:42,132 [model] Posterior to be computed for parameters {'Omega_m': 0.31467659837433964, 'b1': 0.5083995069720371}
2023-07-02 10:33:42,132 [prior] Evaluating prior at array([0.3146766 , 0.50839951])
2023-07-02 10:33:42,132 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:42,132 [model] Got input parameters: {'Omega_m': 0.31467659837433964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:42,132 [classy] Got parameters {'Omega_m': 0.31467659837433964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:42,132 [classy] Computing new state
2023-07-02 10:33:42,132 [classy] Setting parameters: {'Omega_m': 0.31467659837433964, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:42,182 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.997100024559}
2023-07-02 10:33:42,182 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:42,184 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000495683
2023-07-02 10:33:42,184 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:42,184 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:42,205 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.77395
2023-07-02 10:33:42,205 [model] Computed derived parameters: {}
2023-07-02 10:33:42,205 [mcmc] New sample, #152:
Omega_m:0.3147684, b1:0.5083995
2023-07-02 10:33:42,206 [model] Posterior to be computed for parameters {'Omega_m': 0.31467659837433964, 'b1': 0.15950987113664045}
2023-07-02 10:33:42,206 [prior] Evaluating prior at array([0.3146766 , 0.15950987])
2023-07-02 10:33:42,206 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:42,206 [model] Got input parameters: {'Omega_m': 0.31467659837433964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.15950987113664045, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:42,206 [classy] Got parameters {'Omega_m': 0.31467659837433964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:42,206 [classy] Re-using computed results
2023-07-02 10:33:42,206 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.997100024559}
2023-07-02 10:33:42,206 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:42,206 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.15950987113664045, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:42,206 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:42,226 [fs_likelihood.fslikelihood] Computed log-likelihood = -216.464
2023-07-02 10:33:42,226 [model] Computed derived parameters: {}
2023-07-02 10:33:42,226 [model] Posterior to be computed for parameters {'Omega_m': 0.3254489108874341, 'b1': 0.5083995069720371}
2023-07-02 10:33:42,226 [prior] Evaluating prior at array([0.32544891, 0.50839951])
2023-07-02 10:33:42,227 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:42,227 [model] Got input parameters: {'Omega_m': 0.3254489108874341, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:42,227 [classy] Got parameters {'Omega_m': 0.3254489108874341, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:42,227 [classy] Computing new state
2023-07-02 10:33:42,227 [classy] Setting parameters: {'Omega_m': 0.3254489108874341, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:42,273 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.72822557366604}
2023-07-02 10:33:42,273 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:42,275 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0101861
2023-07-02 10:33:42,275 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:42,275 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:42,296 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.320436
2023-07-02 10:33:42,296 [model] Computed derived parameters: {}
2023-07-02 10:33:42,296 [model] Posterior to be computed for parameters {'Omega_m': 0.31467659837433964, 'b1': -0.7624827321094867}
2023-07-02 10:33:42,296 [prior] Evaluating prior at array([ 0.3146766 , -0.76248273])
2023-07-02 10:33:42,296 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:42,296 [model] Posterior to be computed for parameters {'Omega_m': 0.3153126945062122, 'b1': 0.5083995069720371}
2023-07-02 10:33:42,296 [prior] Evaluating prior at array([0.31531269, 0.50839951])
2023-07-02 10:33:42,297 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:42,297 [model] Got input parameters: {'Omega_m': 0.3153126945062122, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:42,297 [classy] Got parameters {'Omega_m': 0.3153126945062122, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:42,297 [classy] Computing new state
2023-07-02 10:33:42,297 [classy] Setting parameters: {'Omega_m': 0.3153126945062122, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:42,342 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.9211055838606}
2023-07-02 10:33:42,342 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:42,344 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000689712
2023-07-02 10:33:42,344 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:42,344 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:42,364 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.72457
2023-07-02 10:33:42,364 [model] Computed derived parameters: {}
2023-07-02 10:33:42,364 [model] Posterior to be computed for parameters {'Omega_m': 0.31467659837433964, 'b1': 0.18135163864203013}
2023-07-02 10:33:42,364 [prior] Evaluating prior at array([0.3146766 , 0.18135164])
2023-07-02 10:33:42,364 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:42,364 [model] Got input parameters: {'Omega_m': 0.31467659837433964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.18135163864203013, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:42,364 [classy] Got parameters {'Omega_m': 0.31467659837433964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:42,364 [classy] Re-using computed results
2023-07-02 10:33:42,364 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.997100024559}
2023-07-02 10:33:42,365 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:42,365 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.18135163864203013, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:42,365 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:42,384 [fs_likelihood.fslikelihood] Computed log-likelihood = -193.932
2023-07-02 10:33:42,384 [model] Computed derived parameters: {}
2023-07-02 10:33:42,384 [model] Posterior to be computed for parameters {'Omega_m': 0.33756082270622256, 'b1': 0.5083995069720371}
2023-07-02 10:33:42,384 [prior] Evaluating prior at array([0.33756082, 0.50839951])
2023-07-02 10:33:42,384 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:42,384 [model] Got input parameters: {'Omega_m': 0.33756082270622256, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:42,384 [classy] Got parameters {'Omega_m': 0.33756082270622256, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:42,384 [classy] Computing new state
2023-07-02 10:33:42,384 [classy] Setting parameters: {'Omega_m': 0.33756082270622256, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:42,429 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.34584754707868}
2023-07-02 10:33:42,429 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:42,431 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0364832
2023-07-02 10:33:42,431 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:42,431 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:42,451 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.54345
2023-07-02 10:33:42,451 [model] Computed derived parameters: {}
2023-07-02 10:33:42,451 [model] Posterior to be computed for parameters {'Omega_m': 0.31467659837433964, 'b1': 0.6612434972353614}
2023-07-02 10:33:42,452 [prior] Evaluating prior at array([0.3146766, 0.6612435])
2023-07-02 10:33:42,452 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:42,452 [model] Got input parameters: {'Omega_m': 0.31467659837433964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6612434972353614, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:42,452 [classy] Got parameters {'Omega_m': 0.31467659837433964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:42,452 [classy] Re-using computed results
2023-07-02 10:33:42,452 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.997100024559}
2023-07-02 10:33:42,452 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:42,452 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6612434972353614, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:42,452 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:42,471 [fs_likelihood.fslikelihood] Computed log-likelihood = -78.1031
2023-07-02 10:33:42,471 [model] Computed derived parameters: {}
2023-07-02 10:33:42,472 [model] Posterior to be computed for parameters {'Omega_m': 0.31329504702485694, 'b1': 0.5083995069720371}
2023-07-02 10:33:42,472 [prior] Evaluating prior at array([0.31329505, 0.50839951])
2023-07-02 10:33:42,472 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:42,472 [model] Got input parameters: {'Omega_m': 0.31329504702485694, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:42,472 [classy] Got parameters {'Omega_m': 0.31329504702485694, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:42,472 [classy] Computing new state
2023-07-02 10:33:42,472 [classy] Setting parameters: {'Omega_m': 0.31329504702485694, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:42,517 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.16264176106117}
2023-07-02 10:33:42,517 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:42,519 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000242646
2023-07-02 10:33:42,519 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:42,519 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:42,538 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.83991
2023-07-02 10:33:42,538 [model] Computed derived parameters: {}
2023-07-02 10:33:42,538 [mcmc] New sample, #153:
Omega_m:0.3146766, b1:0.5083995
2023-07-02 10:33:42,538 [model] Posterior to be computed for parameters {'Omega_m': 0.31329504702485694, 'b1': 0.12986138097374478}
2023-07-02 10:33:42,539 [prior] Evaluating prior at array([0.31329505, 0.12986138])
2023-07-02 10:33:42,539 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:42,539 [model] Got input parameters: {'Omega_m': 0.31329504702485694, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.12986138097374478, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:42,539 [classy] Got parameters {'Omega_m': 0.31329504702485694, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:42,539 [classy] Re-using computed results
2023-07-02 10:33:42,539 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.16264176106117}
2023-07-02 10:33:42,539 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:42,539 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.12986138097374478, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:42,539 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:42,559 [fs_likelihood.fslikelihood] Computed log-likelihood = -250.347
2023-07-02 10:33:42,559 [model] Computed derived parameters: {}
2023-07-02 10:33:42,559 [model] Posterior to be computed for parameters {'Omega_m': 0.31094639698655735, 'b1': 0.5083995069720371}
2023-07-02 10:33:42,560 [prior] Evaluating prior at array([0.3109464 , 0.50839951])
2023-07-02 10:33:42,560 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:42,560 [model] Got input parameters: {'Omega_m': 0.31094639698655735, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:42,560 [classy] Got parameters {'Omega_m': 0.31094639698655735, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:42,560 [classy] Computing new state
2023-07-02 10:33:42,560 [classy] Setting parameters: {'Omega_m': 0.31094639698655735, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:42,611 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.44555194214908}
2023-07-02 10:33:42,611 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:42,613 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000347912
2023-07-02 10:33:42,613 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:42,613 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:42,637 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.82229
2023-07-02 10:33:42,637 [model] Computed derived parameters: {}
2023-07-02 10:33:42,637 [mcmc] New sample, #154:
Omega_m:0.313295, b1:0.5083995
2023-07-02 10:33:42,637 [model] Posterior to be computed for parameters {'Omega_m': 0.31094639698655735, 'b1': -0.2155186563176278}
2023-07-02 10:33:42,637 [prior] Evaluating prior at array([ 0.3109464 , -0.21551866])
2023-07-02 10:33:42,637 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:42,637 [model] Posterior to be computed for parameters {'Omega_m': 0.3241053680582019, 'b1': 0.5083995069720371}
2023-07-02 10:33:42,637 [prior] Evaluating prior at array([0.32410537, 0.50839951])
2023-07-02 10:33:42,637 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:42,637 [model] Got input parameters: {'Omega_m': 0.3241053680582019, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:42,637 [classy] Got parameters {'Omega_m': 0.3241053680582019, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:42,638 [classy] Computing new state
2023-07-02 10:33:42,638 [classy] Setting parameters: {'Omega_m': 0.3241053680582019, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:42,693 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.8844211891672}
2023-07-02 10:33:42,693 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:42,695 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00825013
2023-07-02 10:33:42,695 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:42,695 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:42,723 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.814071
2023-07-02 10:33:42,723 [model] Computed derived parameters: {}
2023-07-02 10:33:42,723 [model] Posterior to be computed for parameters {'Omega_m': 0.31094639698655735, 'b1': 0.8237891926851358}
2023-07-02 10:33:42,723 [prior] Evaluating prior at array([0.3109464 , 0.82378919])
2023-07-02 10:33:42,723 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:42,723 [model] Got input parameters: {'Omega_m': 0.31094639698655735, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.8237891926851358, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:42,724 [classy] Got parameters {'Omega_m': 0.31094639698655735, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:42,724 [classy] Re-using computed results
2023-07-02 10:33:42,724 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.44555194214908}
2023-07-02 10:33:42,724 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:42,724 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.8237891926851358, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:42,724 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:42,749 [fs_likelihood.fslikelihood] Computed log-likelihood = -359.672
2023-07-02 10:33:42,749 [model] Computed derived parameters: {}
2023-07-02 10:33:42,750 [model] Posterior to be computed for parameters {'Omega_m': 0.3290164248720366, 'b1': 0.5083995069720371}
2023-07-02 10:33:42,750 [prior] Evaluating prior at array([0.32901642, 0.50839951])
2023-07-02 10:33:42,750 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:42,750 [model] Got input parameters: {'Omega_m': 0.3290164248720366, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:42,750 [classy] Got parameters {'Omega_m': 0.3290164248720366, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:42,750 [classy] Computing new state
2023-07-02 10:33:42,750 [classy] Setting parameters: {'Omega_m': 0.3290164248720366, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:42,807 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.31626900889293}
2023-07-02 10:33:42,807 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:42,810 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0162978
2023-07-02 10:33:42,810 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:42,810 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:42,833 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.24981
2023-07-02 10:33:42,833 [model] Computed derived parameters: {}
2023-07-02 10:33:42,834 [model] Posterior to be computed for parameters {'Omega_m': 0.31094639698655735, 'b1': 0.24609791895381977}
2023-07-02 10:33:42,834 [prior] Evaluating prior at array([0.3109464 , 0.24609792])
2023-07-02 10:33:42,834 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:42,834 [model] Got input parameters: {'Omega_m': 0.31094639698655735, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.24609791895381977, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:42,834 [classy] Got parameters {'Omega_m': 0.31094639698655735, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:42,834 [classy] Re-using computed results
2023-07-02 10:33:42,834 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.44555194214908}
2023-07-02 10:33:42,834 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:42,834 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.24609791895381977, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:42,834 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:42,858 [fs_likelihood.fslikelihood] Computed log-likelihood = -137.187
2023-07-02 10:33:42,858 [model] Computed derived parameters: {}
2023-07-02 10:33:42,858 [model] Posterior to be computed for parameters {'Omega_m': 0.3043396985082412, 'b1': 0.5083995069720371}
2023-07-02 10:33:42,858 [prior] Evaluating prior at array([0.3043397 , 0.50839951])
2023-07-02 10:33:42,858 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:42,859 [model] Got input parameters: {'Omega_m': 0.3043396985082412, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:42,859 [classy] Got parameters {'Omega_m': 0.3043396985082412, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:42,859 [classy] Computing new state
2023-07-02 10:33:42,859 [classy] Setting parameters: {'Omega_m': 0.3043396985082412, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:42,910 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2515933016373}
2023-07-02 10:33:42,911 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:42,913 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00435376
2023-07-02 10:33:42,913 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:42,913 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:42,935 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.89641
2023-07-02 10:33:42,935 [model] Computed derived parameters: {}
2023-07-02 10:33:42,935 [model] Posterior to be computed for parameters {'Omega_m': 0.31094639698655735, 'b1': 1.190385110524115}
2023-07-02 10:33:42,935 [prior] Evaluating prior at array([0.3109464 , 1.19038511])
2023-07-02 10:33:42,935 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:42,935 [model] Got input parameters: {'Omega_m': 0.31094639698655735, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.190385110524115, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:42,935 [classy] Got parameters {'Omega_m': 0.31094639698655735, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:42,935 [classy] Re-using computed results
2023-07-02 10:33:42,935 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.44555194214908}
2023-07-02 10:33:42,935 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:42,935 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.190385110524115, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:42,935 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:42,958 [fs_likelihood.fslikelihood] Computed log-likelihood = -2306.37
2023-07-02 10:33:42,958 [model] Computed derived parameters: {}
2023-07-02 10:33:42,958 [model] Posterior to be computed for parameters {'Omega_m': 0.3069555960819579, 'b1': 0.5083995069720371}
2023-07-02 10:33:42,958 [prior] Evaluating prior at array([0.3069556 , 0.50839951])
2023-07-02 10:33:42,958 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:42,958 [model] Got input parameters: {'Omega_m': 0.3069555960819579, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:42,958 [classy] Got parameters {'Omega_m': 0.3069555960819579, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:42,958 [classy] Computing new state
2023-07-02 10:33:42,958 [classy] Setting parameters: {'Omega_m': 0.3069555960819579, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:43,007 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.93061852761033}
2023-07-02 10:33:43,008 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:43,009 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00210274
2023-07-02 10:33:43,009 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:43,009 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:43,031 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.41764
2023-07-02 10:33:43,031 [model] Computed derived parameters: {}
2023-07-02 10:33:43,031 [mcmc] New sample, #155:
Omega_m:0.3109464, b1:0.5083995
2023-07-02 10:33:43,031 [model] Posterior to be computed for parameters {'Omega_m': 0.3069555960819579, 'b1': 0.15817117907705347}
2023-07-02 10:33:43,031 [prior] Evaluating prior at array([0.3069556 , 0.15817118])
2023-07-02 10:33:43,031 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:43,031 [model] Got input parameters: {'Omega_m': 0.3069555960819579, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.15817117907705347, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:43,031 [classy] Got parameters {'Omega_m': 0.3069555960819579, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:43,031 [classy] Re-using computed results
2023-07-02 10:33:43,031 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.93061852761033}
2023-07-02 10:33:43,031 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:43,031 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.15817117907705347, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:43,031 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:43,052 [fs_likelihood.fslikelihood] Computed log-likelihood = -231.442
2023-07-02 10:33:43,052 [model] Computed derived parameters: {}
2023-07-02 10:33:43,052 [model] Posterior to be computed for parameters {'Omega_m': 0.3190647991072347, 'b1': 0.5083995069720371}
2023-07-02 10:33:43,052 [prior] Evaluating prior at array([0.3190648 , 0.50839951])
2023-07-02 10:33:43,053 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:43,053 [model] Got input parameters: {'Omega_m': 0.3190647991072347, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:43,053 [classy] Got parameters {'Omega_m': 0.3190647991072347, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:43,053 [classy] Computing new state
2023-07-02 10:33:43,053 [classy] Setting parameters: {'Omega_m': 0.3190647991072347, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:43,100 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.47561356146335}
2023-07-02 10:33:43,101 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:43,102 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00281489
2023-07-02 10:33:43,103 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:43,103 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:43,127 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.18942
2023-07-02 10:33:43,127 [model] Computed derived parameters: {}
2023-07-02 10:33:43,127 [mcmc] New sample, #156:
Omega_m:0.3069556, b1:0.5083995
2023-07-02 10:33:43,127 [model] Posterior to be computed for parameters {'Omega_m': 0.3190647991072347, 'b1': -3.1786251557452827}
2023-07-02 10:33:43,127 [prior] Evaluating prior at array([ 0.3190648 , -3.17862516])
2023-07-02 10:33:43,128 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:43,128 [model] Posterior to be computed for parameters {'Omega_m': 0.317049612631892, 'b1': 0.5083995069720371}
2023-07-02 10:33:43,128 [prior] Evaluating prior at array([0.31704961, 0.50839951])
2023-07-02 10:33:43,128 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:43,128 [model] Got input parameters: {'Omega_m': 0.317049612631892, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:43,128 [classy] Got parameters {'Omega_m': 0.317049612631892, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:43,128 [classy] Computing new state
2023-07-02 10:33:43,128 [classy] Setting parameters: {'Omega_m': 0.317049612631892, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:43,177 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.714295501389}
2023-07-02 10:33:43,177 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:43,179 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00146622
2023-07-02 10:33:43,179 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:43,179 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:43,200 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.52868
2023-07-02 10:33:43,201 [model] Computed derived parameters: {}
2023-07-02 10:33:43,201 [mcmc] New sample, #157:
Omega_m:0.3190648, b1:0.5083995
2023-07-02 10:33:43,201 [model] Posterior to be computed for parameters {'Omega_m': 0.317049612631892, 'b1': 1.1934596823028492}
2023-07-02 10:33:43,201 [prior] Evaluating prior at array([0.31704961, 1.19345968])
2023-07-02 10:33:43,201 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:43,201 [model] Got input parameters: {'Omega_m': 0.317049612631892, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 1.1934596823028492, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:43,201 [classy] Got parameters {'Omega_m': 0.317049612631892, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:43,201 [classy] Re-using computed results
2023-07-02 10:33:43,201 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.714295501389}
2023-07-02 10:33:43,201 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:43,201 [fs_likelihood.fslikelihood] Got parameters {'b1': 1.1934596823028492, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:43,201 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:43,223 [fs_likelihood.fslikelihood] Computed log-likelihood = -2451.94
2023-07-02 10:33:43,223 [model] Computed derived parameters: {}
2023-07-02 10:33:43,223 [model] Posterior to be computed for parameters {'Omega_m': 0.3314450543964287, 'b1': 0.5083995069720371}
2023-07-02 10:33:43,223 [prior] Evaluating prior at array([0.33144505, 0.50839951])
2023-07-02 10:33:43,223 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:43,223 [model] Got input parameters: {'Omega_m': 0.3314450543964287, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:43,223 [classy] Got parameters {'Omega_m': 0.3314450543964287, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:43,223 [classy] Computing new state
2023-07-02 10:33:43,223 [classy] Setting parameters: {'Omega_m': 0.3314450543964287, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:43,271 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.03814689272636}
2023-07-02 10:33:43,271 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:43,272 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0212502
2023-07-02 10:33:43,273 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:43,273 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:43,293 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.53447
2023-07-02 10:33:43,293 [model] Computed derived parameters: {}
2023-07-02 10:33:43,293 [model] Posterior to be computed for parameters {'Omega_m': 0.317049612631892, 'b1': 0.28957844454413706}
2023-07-02 10:33:43,293 [prior] Evaluating prior at array([0.31704961, 0.28957844])
2023-07-02 10:33:43,293 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:43,293 [model] Got input parameters: {'Omega_m': 0.317049612631892, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.28957844454413706, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:43,293 [classy] Got parameters {'Omega_m': 0.317049612631892, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:43,293 [classy] Re-using computed results
2023-07-02 10:33:43,293 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.714295501389}
2023-07-02 10:33:43,293 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:43,293 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.28957844454413706, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:43,294 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:43,314 [fs_likelihood.fslikelihood] Computed log-likelihood = -90.5572
2023-07-02 10:33:43,314 [model] Computed derived parameters: {}
2023-07-02 10:33:43,314 [model] Posterior to be computed for parameters {'Omega_m': 0.31506985853788355, 'b1': 0.5083995069720371}
2023-07-02 10:33:43,314 [prior] Evaluating prior at array([0.31506986, 0.50839951])
2023-07-02 10:33:43,314 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:43,314 [model] Got input parameters: {'Omega_m': 0.31506985853788355, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:43,315 [classy] Got parameters {'Omega_m': 0.31506985853788355, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:43,315 [classy] Computing new state
2023-07-02 10:33:43,315 [classy] Setting parameters: {'Omega_m': 0.31506985853788355, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:43,360 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.9501002306261}
2023-07-02 10:33:43,361 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:43,362 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000609901
2023-07-02 10:33:43,362 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:43,362 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:43,382 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.74483
2023-07-02 10:33:43,382 [model] Computed derived parameters: {}
2023-07-02 10:33:43,382 [mcmc] New sample, #158:
Omega_m:0.3170496, b1:0.5083995
2023-07-02 10:33:43,382 [model] Posterior to be computed for parameters {'Omega_m': 0.31506985853788355, 'b1': 0.06995420839207989}
2023-07-02 10:33:43,382 [prior] Evaluating prior at array([0.31506986, 0.06995421])
2023-07-02 10:33:43,383 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:43,383 [model] Got input parameters: {'Omega_m': 0.31506985853788355, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.06995420839207989, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:43,383 [classy] Got parameters {'Omega_m': 0.31506985853788355, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:43,383 [classy] Re-using computed results
2023-07-02 10:33:43,383 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.9501002306261}
2023-07-02 10:33:43,383 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:43,383 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.06995420839207989, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:43,383 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:43,403 [fs_likelihood.fslikelihood] Computed log-likelihood = -313.113
2023-07-02 10:33:43,403 [model] Computed derived parameters: {}
2023-07-02 10:33:43,403 [model] Posterior to be computed for parameters {'Omega_m': 0.3163792243476926, 'b1': 0.5083995069720371}
2023-07-02 10:33:43,403 [prior] Evaluating prior at array([0.31637922, 0.50839951])
2023-07-02 10:33:43,403 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:43,403 [model] Got input parameters: {'Omega_m': 0.3163792243476926, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:43,403 [classy] Got parameters {'Omega_m': 0.3163792243476926, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:43,403 [classy] Computing new state
2023-07-02 10:33:43,403 [classy] Setting parameters: {'Omega_m': 0.3163792243476926, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:43,449 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.79399745211575}
2023-07-02 10:33:43,449 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:43,450 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00112389
2023-07-02 10:33:43,451 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:43,451 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:43,470 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.61488
2023-07-02 10:33:43,470 [model] Computed derived parameters: {}
2023-07-02 10:33:43,470 [mcmc] New sample, #159:
Omega_m:0.3150699, b1:0.5083995
2023-07-02 10:33:43,470 [model] Posterior to be computed for parameters {'Omega_m': 0.3163792243476926, 'b1': 0.21964820899395604}
2023-07-02 10:33:43,470 [prior] Evaluating prior at array([0.31637922, 0.21964821])
2023-07-02 10:33:43,470 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:43,471 [model] Got input parameters: {'Omega_m': 0.3163792243476926, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.21964820899395604, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:43,471 [classy] Got parameters {'Omega_m': 0.3163792243476926, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:43,471 [classy] Re-using computed results
2023-07-02 10:33:43,471 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.79399745211575}
2023-07-02 10:33:43,471 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:43,471 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.21964820899395604, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:43,471 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:43,490 [fs_likelihood.fslikelihood] Computed log-likelihood = -153.331
2023-07-02 10:33:43,490 [model] Computed derived parameters: {}
2023-07-02 10:33:43,490 [model] Posterior to be computed for parameters {'Omega_m': 0.3323390033146361, 'b1': 0.5083995069720371}
2023-07-02 10:33:43,490 [prior] Evaluating prior at array([0.332339 , 0.50839951])
2023-07-02 10:33:43,490 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:43,490 [model] Got input parameters: {'Omega_m': 0.3323390033146361, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:43,490 [classy] Got parameters {'Omega_m': 0.3323390033146361, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:43,491 [classy] Computing new state
2023-07-02 10:33:43,491 [classy] Setting parameters: {'Omega_m': 0.3323390033146361, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:43,535 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.93623813445927}
2023-07-02 10:33:43,535 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:43,537 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0232319
2023-07-02 10:33:43,537 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:43,537 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:43,556 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.05133
2023-07-02 10:33:43,556 [model] Computed derived parameters: {}
2023-07-02 10:33:43,556 [model] Posterior to be computed for parameters {'Omega_m': 0.3163792243476926, 'b1': -0.11038986594972411}
2023-07-02 10:33:43,556 [prior] Evaluating prior at array([ 0.31637922, -0.11038987])
2023-07-02 10:33:43,557 [prior] Got logpriors (internal) = -inf
2023-07-02 10:33:43,557 [model] Posterior to be computed for parameters {'Omega_m': 0.3024856187765864, 'b1': 0.5083995069720371}
2023-07-02 10:33:43,557 [prior] Evaluating prior at array([0.30248562, 0.50839951])
2023-07-02 10:33:43,557 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:43,557 [model] Got input parameters: {'Omega_m': 0.3024856187765864, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:43,557 [classy] Got parameters {'Omega_m': 0.3024856187765864, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:43,557 [classy] Computing new state
2023-07-02 10:33:43,557 [classy] Setting parameters: {'Omega_m': 0.3024856187765864, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:43,602 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.4805602396071}
2023-07-02 10:33:43,602 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:43,604 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00648829
2023-07-02 10:33:43,604 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:43,604 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:43,624 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.40423
2023-07-02 10:33:43,624 [model] Computed derived parameters: {}
2023-07-02 10:33:43,624 [model] Posterior to be computed for parameters {'Omega_m': 0.3163792243476926, 'b1': 2.01208020692284}
2023-07-02 10:33:43,624 [prior] Evaluating prior at array([0.31637922, 2.01208021])
2023-07-02 10:33:43,624 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:43,624 [model] Got input parameters: {'Omega_m': 0.3163792243476926, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 2.01208020692284, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:43,624 [classy] Got parameters {'Omega_m': 0.3163792243476926, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:43,624 [classy] Re-using computed results
2023-07-02 10:33:43,624 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.79399745211575}
2023-07-02 10:33:43,624 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:43,624 [fs_likelihood.fslikelihood] Got parameters {'b1': 2.01208020692284, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:43,624 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:43,644 [fs_likelihood.fslikelihood] Computed log-likelihood = -20601.1
2023-07-02 10:33:43,644 [model] Computed derived parameters: {}
2023-07-02 10:33:43,644 [model] Posterior to be computed for parameters {'Omega_m': 0.3136104366949477, 'b1': 0.5083995069720371}
2023-07-02 10:33:43,644 [prior] Evaluating prior at array([0.31361044, 0.50839951])
2023-07-02 10:33:43,644 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:43,644 [model] Got input parameters: {'Omega_m': 0.3136104366949477, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:43,644 [classy] Got parameters {'Omega_m': 0.3136104366949477, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:43,644 [classy] Computing new state
2023-07-02 10:33:43,644 [classy] Setting parameters: {'Omega_m': 0.3136104366949477, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:43,688 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.12479302532236}
2023-07-02 10:33:43,688 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:43,690 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00028
2023-07-02 10:33:43,690 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083995069720371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:43,690 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:43,710 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.82984
2023-07-02 10:33:43,710 [model] Computed derived parameters: {}
2023-07-02 10:33:43,710 [mcmc] New sample, #160:
Omega_m:0.3163792, b1:0.5083995
2023-07-02 10:33:43,710 [mcmc] Learn + convergence test @ 160 samples accepted.
2023-07-02 10:33:43,710 [mcmc] Ready to check convergence and learn a new proposal covmat
2023-07-02 10:33:43,715 [mcmc] - Acceptance rate: 0.232
2023-07-02 10:33:43,716 [mcmc] - Condition number = 12.6013
2023-07-02 10:33:43,716 [mcmc] - Eigenvalues = array([0.14963695, 1.88561463])
2023-07-02 10:33:43,716 [mcmc] - Convergence of means: R-1 = 1.885615 after 128 accepted steps
2023-07-02 10:33:43,716 [mcmc] - Updated covariance matrix of proposal pdf.
2023-07-02 10:33:43,716 [mcmc] array([[ 3.43794894e-05, -2.33629757e-05],
[-2.33629757e-05, 8.02724856e-05]])
2023-07-02 10:33:43,726 [mcmc] Dumped checkpoint and progress info, and current covmat.
2023-07-02 10:33:43,726 [model] Posterior to be computed for parameters {'Omega_m': 0.3136104366949477, 'b1': 0.5197917763701246}
2023-07-02 10:33:43,726 [prior] Evaluating prior at array([0.31361044, 0.51979178])
2023-07-02 10:33:43,726 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:43,726 [model] Got input parameters: {'Omega_m': 0.3136104366949477, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5197917763701246, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:43,726 [classy] Got parameters {'Omega_m': 0.3136104366949477, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:43,727 [classy] Re-using computed results
2023-07-02 10:33:43,727 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.12479302532236}
2023-07-02 10:33:43,727 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:43,727 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5197917763701246, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:43,727 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:43,747 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.12855
2023-07-02 10:33:43,747 [model] Computed derived parameters: {}
2023-07-02 10:33:43,747 [model] Posterior to be computed for parameters {'Omega_m': 0.2878657114872602, 'b1': 0.5258946298130794}
2023-07-02 10:33:43,747 [prior] Evaluating prior at array([0.28786571, 0.52589463])
2023-07-02 10:33:43,747 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:43,747 [model] Got input parameters: {'Omega_m': 0.2878657114872602, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5258946298130794, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:43,747 [classy] Got parameters {'Omega_m': 0.2878657114872602, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:43,747 [classy] Computing new state
2023-07-02 10:33:43,747 [classy] Setting parameters: {'Omega_m': 0.2878657114872602, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:43,794 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.33038859203214}
2023-07-02 10:33:43,794 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:43,795 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0397724
2023-07-02 10:33:43,796 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5258946298130794, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:43,796 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:43,816 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.21648
2023-07-02 10:33:43,816 [model] Computed derived parameters: {}
2023-07-02 10:33:43,816 [model] Posterior to be computed for parameters {'Omega_m': 0.3136104366949477, 'b1': 0.4906071623484306}
2023-07-02 10:33:43,816 [prior] Evaluating prior at array([0.31361044, 0.49060716])
2023-07-02 10:33:43,816 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:43,816 [model] Got input parameters: {'Omega_m': 0.3136104366949477, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4906071623484306, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:43,816 [classy] Got parameters {'Omega_m': 0.3136104366949477, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:43,816 [classy] Re-using computed results
2023-07-02 10:33:43,817 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.12479302532236}
2023-07-02 10:33:43,817 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:43,817 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4906071623484306, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:43,817 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:43,837 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.51259
2023-07-02 10:33:43,837 [model] Computed derived parameters: {}
2023-07-02 10:33:43,837 [mcmc] New sample, #161:
Omega_m:0.3136104, b1:0.5083995
2023-07-02 10:33:43,837 [model] Posterior to be computed for parameters {'Omega_m': 0.2900151599397835, 'b1': 0.5066416028782804}
2023-07-02 10:33:43,837 [prior] Evaluating prior at array([0.29001516, 0.5066416 ])
2023-07-02 10:33:43,837 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:43,837 [model] Got input parameters: {'Omega_m': 0.2900151599397835, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5066416028782804, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:43,837 [classy] Got parameters {'Omega_m': 0.2900151599397835, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:43,837 [classy] Computing new state
2023-07-02 10:33:43,837 [classy] Setting parameters: {'Omega_m': 0.2900151599397835, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:43,884 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.05338333616066}
2023-07-02 10:33:43,884 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:43,886 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0329808
2023-07-02 10:33:43,886 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5066416028782804, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:43,886 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:43,906 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.88462
2023-07-02 10:33:43,906 [model] Computed derived parameters: {}
2023-07-02 10:33:43,906 [mcmc] New sample, #162:
Omega_m:0.3136104, b1:0.4906072
2023-07-02 10:33:43,906 [model] Posterior to be computed for parameters {'Omega_m': 0.2900151599397835, 'b1': 0.5066198345083764}
2023-07-02 10:33:43,906 [prior] Evaluating prior at array([0.29001516, 0.50661983])
2023-07-02 10:33:43,906 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:43,906 [model] Got input parameters: {'Omega_m': 0.2900151599397835, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5066198345083764, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:43,906 [classy] Got parameters {'Omega_m': 0.2900151599397835, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:43,906 [classy] Re-using computed results
2023-07-02 10:33:43,906 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.05338333616066}
2023-07-02 10:33:43,906 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:43,906 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5066198345083764, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:43,907 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:43,927 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.88883
2023-07-02 10:33:43,927 [model] Computed derived parameters: {}
2023-07-02 10:33:43,927 [mcmc] New sample, #163:
Omega_m:0.2900152, b1:0.5066416
2023-07-02 10:33:43,927 [model] Posterior to be computed for parameters {'Omega_m': 0.2778878170618393, 'b1': 0.5148611092422671}
2023-07-02 10:33:43,927 [prior] Evaluating prior at array([0.27788782, 0.51486111])
2023-07-02 10:33:43,927 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:43,927 [model] Got input parameters: {'Omega_m': 0.2778878170618393, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5148611092422671, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:43,927 [classy] Got parameters {'Omega_m': 0.2778878170618393, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:43,927 [classy] Computing new state
2023-07-02 10:33:43,927 [classy] Setting parameters: {'Omega_m': 0.2778878170618393, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:43,973 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.64020303021948}
2023-07-02 10:33:43,973 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:43,974 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0804355
2023-07-02 10:33:43,975 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5148611092422671, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:43,975 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:43,995 [fs_likelihood.fslikelihood] Computed log-likelihood = -13.0431
2023-07-02 10:33:43,995 [model] Computed derived parameters: {}
2023-07-02 10:33:43,995 [model] Posterior to be computed for parameters {'Omega_m': 0.2900151599397835, 'b1': 0.5117476044977189}
2023-07-02 10:33:43,995 [prior] Evaluating prior at array([0.29001516, 0.5117476 ])
2023-07-02 10:33:43,995 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:43,995 [model] Got input parameters: {'Omega_m': 0.2900151599397835, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5117476044977189, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:43,995 [classy] Got parameters {'Omega_m': 0.2900151599397835, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:43,995 [classy] Re-using computed results
2023-07-02 10:33:43,995 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.05338333616066}
2023-07-02 10:33:43,995 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:43,995 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5117476044977189, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:43,995 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:44,015 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.95841
2023-07-02 10:33:44,015 [model] Computed derived parameters: {}
2023-07-02 10:33:44,015 [mcmc] New sample, #164:
Omega_m:0.2900152, b1:0.5066198
2023-07-02 10:33:44,015 [model] Posterior to be computed for parameters {'Omega_m': 0.30982317975064466, 'b1': 0.49828683779567867}
2023-07-02 10:33:44,015 [prior] Evaluating prior at array([0.30982318, 0.49828684])
2023-07-02 10:33:44,015 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:44,015 [model] Got input parameters: {'Omega_m': 0.30982317975064466, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49828683779567867, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:44,015 [classy] Got parameters {'Omega_m': 0.30982317975064466, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:44,015 [classy] Computing new state
2023-07-02 10:33:44,015 [classy] Setting parameters: {'Omega_m': 0.30982317975064466, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:44,060 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.58151616141933}
2023-07-02 10:33:44,060 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:44,062 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000639447
2023-07-02 10:33:44,062 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49828683779567867, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:44,062 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:44,082 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.4126
2023-07-02 10:33:44,082 [model] Computed derived parameters: {}
2023-07-02 10:33:44,082 [mcmc] New sample, #165:
Omega_m:0.2900152, b1:0.5117476
2023-07-02 10:33:44,082 [model] Posterior to be computed for parameters {'Omega_m': 0.30982317975064466, 'b1': 0.47652149315782333}
2023-07-02 10:33:44,082 [prior] Evaluating prior at array([0.30982318, 0.47652149])
2023-07-02 10:33:44,082 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:44,082 [model] Got input parameters: {'Omega_m': 0.30982317975064466, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47652149315782333, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:44,082 [classy] Got parameters {'Omega_m': 0.30982317975064466, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:44,082 [classy] Re-using computed results
2023-07-02 10:33:44,082 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.58151616141933}
2023-07-02 10:33:44,082 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:44,083 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47652149315782333, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:44,083 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:44,102 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.103254
2023-07-02 10:33:44,102 [model] Computed derived parameters: {}
2023-07-02 10:33:44,102 [model] Posterior to be computed for parameters {'Omega_m': 0.3378137036994859, 'b1': 0.4792655567014105}
2023-07-02 10:33:44,102 [prior] Evaluating prior at array([0.3378137 , 0.47926556])
2023-07-02 10:33:44,102 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:44,102 [model] Got input parameters: {'Omega_m': 0.3378137036994859, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4792655567014105, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:44,102 [classy] Got parameters {'Omega_m': 0.3378137036994859, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:44,102 [classy] Computing new state
2023-07-02 10:33:44,102 [classy] Setting parameters: {'Omega_m': 0.3378137036994859, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:44,149 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.31746913060147}
2023-07-02 10:33:44,149 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:44,150 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0371962
2023-07-02 10:33:44,150 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4792655567014105, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:44,150 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:44,170 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.8372
2023-07-02 10:33:44,170 [model] Computed derived parameters: {}
2023-07-02 10:33:44,171 [model] Posterior to be computed for parameters {'Omega_m': 0.30982317975064466, 'b1': 0.5015484195655898}
2023-07-02 10:33:44,171 [prior] Evaluating prior at array([0.30982318, 0.50154842])
2023-07-02 10:33:44,171 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:44,171 [model] Got input parameters: {'Omega_m': 0.30982317975064466, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5015484195655898, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:44,171 [classy] Got parameters {'Omega_m': 0.30982317975064466, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:44,171 [classy] Re-using computed results
2023-07-02 10:33:44,171 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.58151616141933}
2023-07-02 10:33:44,171 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:44,171 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5015484195655898, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:44,171 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:44,190 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.58208
2023-07-02 10:33:44,190 [model] Computed derived parameters: {}
2023-07-02 10:33:44,190 [mcmc] New sample, #166:
Omega_m:0.3098232, b1:0.4982868
2023-07-02 10:33:44,190 [model] Posterior to be computed for parameters {'Omega_m': 0.3203677009239971, 'b1': 0.4943827694473789}
2023-07-02 10:33:44,190 [prior] Evaluating prior at array([0.3203677 , 0.49438277])
2023-07-02 10:33:44,190 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:44,191 [model] Got input parameters: {'Omega_m': 0.3203677009239971, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4943827694473789, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:44,191 [classy] Got parameters {'Omega_m': 0.3203677009239971, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:44,191 [classy] Computing new state
2023-07-02 10:33:44,191 [classy] Setting parameters: {'Omega_m': 0.3203677009239971, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:44,236 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.32200360315457}
2023-07-02 10:33:44,236 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:44,237 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00393985
2023-07-02 10:33:44,237 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4943827694473789, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:44,237 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:44,257 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.74057
2023-07-02 10:33:44,257 [model] Computed derived parameters: {}
2023-07-02 10:33:44,257 [mcmc] New sample, #167:
Omega_m:0.3098232, b1:0.5015484
2023-07-02 10:33:44,257 [model] Posterior to be computed for parameters {'Omega_m': 0.3203677009239971, 'b1': 0.510781737072457}
2023-07-02 10:33:44,257 [prior] Evaluating prior at array([0.3203677 , 0.51078174])
2023-07-02 10:33:44,257 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:44,257 [model] Got input parameters: {'Omega_m': 0.3203677009239971, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510781737072457, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:44,257 [classy] Got parameters {'Omega_m': 0.3203677009239971, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:44,257 [classy] Re-using computed results
2023-07-02 10:33:44,257 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.32200360315457}
2023-07-02 10:33:44,257 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:44,257 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510781737072457, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:44,257 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:44,277 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.65387
2023-07-02 10:33:44,277 [model] Computed derived parameters: {}
2023-07-02 10:33:44,277 [model] Posterior to be computed for parameters {'Omega_m': 0.3389682897500448, 'b1': 0.4817425262984541}
2023-07-02 10:33:44,277 [prior] Evaluating prior at array([0.33896829, 0.48174253])
2023-07-02 10:33:44,277 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:44,277 [model] Got input parameters: {'Omega_m': 0.3389682897500448, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4817425262984541, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:44,278 [classy] Got parameters {'Omega_m': 0.3389682897500448, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:44,278 [classy] Computing new state
2023-07-02 10:33:44,278 [classy] Setting parameters: {'Omega_m': 0.3389682897500448, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:44,322 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.18813249827744}
2023-07-02 10:33:44,322 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:44,324 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0405352
2023-07-02 10:33:44,324 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4817425262984541, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:44,324 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:44,344 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.68274
2023-07-02 10:33:44,344 [model] Computed derived parameters: {}
2023-07-02 10:33:44,344 [model] Posterior to be computed for parameters {'Omega_m': 0.3203677009239971, 'b1': 0.48397660130391973}
2023-07-02 10:33:44,344 [prior] Evaluating prior at array([0.3203677, 0.4839766])
2023-07-02 10:33:44,344 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:44,344 [model] Got input parameters: {'Omega_m': 0.3203677009239971, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48397660130391973, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:44,344 [classy] Got parameters {'Omega_m': 0.3203677009239971, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:44,344 [classy] Re-using computed results
2023-07-02 10:33:44,344 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.32200360315457}
2023-07-02 10:33:44,344 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:44,344 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48397660130391973, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:44,344 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:44,363 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.66107
2023-07-02 10:33:44,363 [model] Computed derived parameters: {}
2023-07-02 10:33:44,364 [mcmc] New sample, #168:
Omega_m:0.3203677, b1:0.4943828
2023-07-02 10:33:44,364 [model] Posterior to be computed for parameters {'Omega_m': 0.30855563200350583, 'b1': 0.49200362800953573}
2023-07-02 10:33:44,364 [prior] Evaluating prior at array([0.30855563, 0.49200363])
2023-07-02 10:33:44,364 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:44,364 [model] Got input parameters: {'Omega_m': 0.30855563200350583, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49200362800953573, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:44,364 [classy] Got parameters {'Omega_m': 0.30855563200350583, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:44,364 [classy] Computing new state
2023-07-02 10:33:44,364 [classy] Setting parameters: {'Omega_m': 0.30855563200350583, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:44,408 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.73547777731642}
2023-07-02 10:33:44,409 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:44,410 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00115809
2023-07-02 10:33:44,410 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49200362800953573, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:44,410 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:44,430 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.61687
2023-07-02 10:33:44,430 [model] Computed derived parameters: {}
2023-07-02 10:33:44,431 [model] Posterior to be computed for parameters {'Omega_m': 0.3203677009239971, 'b1': 0.49544414984810053}
2023-07-02 10:33:44,431 [prior] Evaluating prior at array([0.3203677 , 0.49544415])
2023-07-02 10:33:44,431 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:44,431 [model] Got input parameters: {'Omega_m': 0.3203677009239971, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49544414984810053, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:44,431 [classy] Got parameters {'Omega_m': 0.3203677009239971, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:44,431 [classy] Re-using computed results
2023-07-02 10:33:44,431 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.32200360315457}
2023-07-02 10:33:44,431 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:44,431 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49544414984810053, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:44,431 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:44,450 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.71563
2023-07-02 10:33:44,450 [model] Computed derived parameters: {}
2023-07-02 10:33:44,450 [mcmc] New sample, #169:
Omega_m:0.3203677, b1:0.4839766
2023-07-02 10:33:44,450 [model] Posterior to be computed for parameters {'Omega_m': 0.3231909916045877, 'b1': 0.4935255503340473}
2023-07-02 10:33:44,451 [prior] Evaluating prior at array([0.32319099, 0.49352555])
2023-07-02 10:33:44,451 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:44,451 [model] Got input parameters: {'Omega_m': 0.3231909916045877, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4935255503340473, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:44,451 [classy] Got parameters {'Omega_m': 0.3231909916045877, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:44,451 [classy] Computing new state
2023-07-02 10:33:44,451 [classy] Setting parameters: {'Omega_m': 0.3231909916045877, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:44,495 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.99105140819117}
2023-07-02 10:33:44,495 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:44,497 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00704875
2023-07-02 10:33:44,497 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4935255503340473, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:44,497 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:44,516 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.4019
2023-07-02 10:33:44,516 [model] Computed derived parameters: {}
2023-07-02 10:33:44,516 [mcmc] New sample, #170:
Omega_m:0.3203677, b1:0.4954441
2023-07-02 10:33:44,516 [model] Posterior to be computed for parameters {'Omega_m': 0.3231909916045877, 'b1': 0.48343679506057297}
2023-07-02 10:33:44,516 [prior] Evaluating prior at array([0.32319099, 0.4834368 ])
2023-07-02 10:33:44,517 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:44,517 [model] Got input parameters: {'Omega_m': 0.3231909916045877, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48343679506057297, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:44,517 [classy] Got parameters {'Omega_m': 0.3231909916045877, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:44,517 [classy] Re-using computed results
2023-07-02 10:33:44,517 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.99105140819117}
2023-07-02 10:33:44,517 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:44,517 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48343679506057297, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:44,517 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:44,536 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.56754
2023-07-02 10:33:44,536 [model] Computed derived parameters: {}
2023-07-02 10:33:44,536 [mcmc] New sample, #171:
Omega_m:0.323191, b1:0.4935256
2023-07-02 10:33:44,537 [model] Posterior to be computed for parameters {'Omega_m': 0.3354184846828529, 'b1': 0.4751274621111435}
2023-07-02 10:33:44,537 [prior] Evaluating prior at array([0.33541848, 0.47512746])
2023-07-02 10:33:44,537 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:44,537 [model] Got input parameters: {'Omega_m': 0.3354184846828529, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4751274621111435, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:44,537 [classy] Got parameters {'Omega_m': 0.3354184846828529, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:44,537 [classy] Computing new state
2023-07-02 10:33:44,537 [classy] Setting parameters: {'Omega_m': 0.3354184846828529, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:44,581 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.58706332752652}
2023-07-02 10:33:44,581 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:44,583 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0307037
2023-07-02 10:33:44,583 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4751274621111435, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:44,583 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:44,603 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.430199
2023-07-02 10:33:44,603 [model] Computed derived parameters: {}
2023-07-02 10:33:44,603 [model] Posterior to be computed for parameters {'Omega_m': 0.3231909916045877, 'b1': 0.4951233870941862}
2023-07-02 10:33:44,603 [prior] Evaluating prior at array([0.32319099, 0.49512339])
2023-07-02 10:33:44,603 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:44,603 [model] Got input parameters: {'Omega_m': 0.3231909916045877, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4951233870941862, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:44,603 [classy] Got parameters {'Omega_m': 0.3231909916045877, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:44,603 [classy] Re-using computed results
2023-07-02 10:33:44,603 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.99105140819117}
2023-07-02 10:33:44,603 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:44,603 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4951233870941862, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:44,603 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:44,623 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.32414
2023-07-02 10:33:44,623 [model] Computed derived parameters: {}
2023-07-02 10:33:44,623 [mcmc] New sample, #172:
Omega_m:0.323191, b1:0.4834368
2023-07-02 10:33:44,623 [model] Posterior to be computed for parameters {'Omega_m': 0.28310417002271976, 'b1': 0.5223648457706341}
2023-07-02 10:33:44,623 [prior] Evaluating prior at array([0.28310417, 0.52236485])
2023-07-02 10:33:44,623 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:44,623 [model] Got input parameters: {'Omega_m': 0.28310417002271976, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5223648457706341, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:44,623 [classy] Got parameters {'Omega_m': 0.28310417002271976, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:44,623 [classy] Computing new state
2023-07-02 10:33:44,623 [classy] Setting parameters: {'Omega_m': 0.28310417002271976, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:44,667 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.95049170254995}
2023-07-02 10:33:44,667 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:44,669 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0572693
2023-07-02 10:33:44,669 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5223648457706341, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:44,669 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:44,688 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.91928
2023-07-02 10:33:44,688 [model] Computed derived parameters: {}
2023-07-02 10:33:44,688 [model] Posterior to be computed for parameters {'Omega_m': 0.3231909916045877, 'b1': 0.4838398183623971}
2023-07-02 10:33:44,689 [prior] Evaluating prior at array([0.32319099, 0.48383982])
2023-07-02 10:33:44,689 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:44,689 [model] Got input parameters: {'Omega_m': 0.3231909916045877, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4838398183623971, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:44,689 [classy] Got parameters {'Omega_m': 0.3231909916045877, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:44,689 [classy] Re-using computed results
2023-07-02 10:33:44,689 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.99105140819117}
2023-07-02 10:33:44,689 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:44,689 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4838398183623971, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:44,689 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:44,708 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.57158
2023-07-02 10:33:44,709 [model] Computed derived parameters: {}
2023-07-02 10:33:44,709 [mcmc] New sample, #173:
Omega_m:0.323191, b1:0.4951234
2023-07-02 10:33:44,709 [model] Posterior to be computed for parameters {'Omega_m': 0.323237478975147, 'b1': 0.48380822733736456}
2023-07-02 10:33:44,709 [prior] Evaluating prior at array([0.32323748, 0.48380823])
2023-07-02 10:33:44,709 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:44,709 [model] Got input parameters: {'Omega_m': 0.323237478975147, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48380822733736456, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:44,709 [classy] Got parameters {'Omega_m': 0.323237478975147, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:44,709 [classy] Computing new state
2023-07-02 10:33:44,709 [classy] Setting parameters: {'Omega_m': 0.323237478975147, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:44,753 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.98562394679985}
2023-07-02 10:33:44,753 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:44,755 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00710755
2023-07-02 10:33:44,755 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48380822733736456, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:44,755 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:44,774 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.56805
2023-07-02 10:33:44,774 [model] Computed derived parameters: {}
2023-07-02 10:33:44,774 [mcmc] New sample, #174:
Omega_m:0.323191, b1:0.4838398
2023-07-02 10:33:44,775 [model] Posterior to be computed for parameters {'Omega_m': 0.323237478975147, 'b1': 0.5096769039263478}
2023-07-02 10:33:44,775 [prior] Evaluating prior at array([0.32323748, 0.5096769 ])
2023-07-02 10:33:44,775 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:44,775 [model] Got input parameters: {'Omega_m': 0.323237478975147, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5096769039263478, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:44,775 [classy] Got parameters {'Omega_m': 0.323237478975147, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:44,775 [classy] Re-using computed results
2023-07-02 10:33:44,775 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.98562394679985}
2023-07-02 10:33:44,775 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:44,775 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5096769039263478, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:44,775 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:44,795 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.934541
2023-07-02 10:33:44,795 [model] Computed derived parameters: {}
2023-07-02 10:33:44,795 [model] Posterior to be computed for parameters {'Omega_m': 0.32403341564303106, 'b1': 0.4832673394597125}
2023-07-02 10:33:44,795 [prior] Evaluating prior at array([0.32403342, 0.48326734])
2023-07-02 10:33:44,795 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:44,795 [model] Got input parameters: {'Omega_m': 0.32403341564303106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4832673394597125, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:44,795 [classy] Got parameters {'Omega_m': 0.32403341564303106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:44,795 [classy] Computing new state
2023-07-02 10:33:44,795 [classy] Setting parameters: {'Omega_m': 0.32403341564303106, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:44,839 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.89280139973127}
2023-07-02 10:33:44,839 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:44,841 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00815219
2023-07-02 10:33:44,841 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4832673394597125, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:44,841 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:44,861 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.50202
2023-07-02 10:33:44,861 [model] Computed derived parameters: {}
2023-07-02 10:33:44,861 [mcmc] New sample, #175:
Omega_m:0.3232375, b1:0.4838082
2023-07-02 10:33:44,861 [model] Posterior to be computed for parameters {'Omega_m': 0.32403341564303106, 'b1': 0.4719045953670057}
2023-07-02 10:33:44,861 [prior] Evaluating prior at array([0.32403342, 0.4719046 ])
2023-07-02 10:33:44,861 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:44,861 [model] Got input parameters: {'Omega_m': 0.32403341564303106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4719045953670057, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:44,861 [classy] Got parameters {'Omega_m': 0.32403341564303106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:44,861 [classy] Re-using computed results
2023-07-02 10:33:44,861 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.89280139973127}
2023-07-02 10:33:44,861 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:44,861 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4719045953670057, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:44,861 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:44,881 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.11311
2023-07-02 10:33:44,881 [model] Computed derived parameters: {}
2023-07-02 10:33:44,881 [model] Posterior to be computed for parameters {'Omega_m': 0.29946886510556425, 'b1': 0.4999604610883577}
2023-07-02 10:33:44,881 [prior] Evaluating prior at array([0.29946887, 0.49996046])
2023-07-02 10:33:44,882 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:44,882 [model] Got input parameters: {'Omega_m': 0.29946886510556425, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4999604610883577, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:44,882 [classy] Got parameters {'Omega_m': 0.29946886510556425, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:44,882 [classy] Computing new state
2023-07-02 10:33:44,882 [classy] Setting parameters: {'Omega_m': 0.29946886510556425, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:44,925 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.85576364630327}
2023-07-02 10:33:44,926 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:44,927 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0109356
2023-07-02 10:33:44,928 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4999604610883577, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:44,928 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:44,947 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.666096
2023-07-02 10:33:44,947 [model] Computed derived parameters: {}
2023-07-02 10:33:44,947 [model] Posterior to be computed for parameters {'Omega_m': 0.32403341564303106, 'b1': 0.45745856973171317}
2023-07-02 10:33:44,947 [prior] Evaluating prior at array([0.32403342, 0.45745857])
2023-07-02 10:33:44,947 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:44,947 [model] Got input parameters: {'Omega_m': 0.32403341564303106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45745856973171317, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:44,947 [classy] Got parameters {'Omega_m': 0.32403341564303106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:44,947 [classy] Re-using computed results
2023-07-02 10:33:44,947 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.89280139973127}
2023-07-02 10:33:44,948 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:44,948 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45745856973171317, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:44,948 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:44,967 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.644804
2023-07-02 10:33:44,967 [model] Computed derived parameters: {}
2023-07-02 10:33:44,967 [model] Posterior to be computed for parameters {'Omega_m': 0.33046017545727063, 'b1': 0.47889996122930045}
2023-07-02 10:33:44,967 [prior] Evaluating prior at array([0.33046018, 0.47889996])
2023-07-02 10:33:44,967 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:44,967 [model] Got input parameters: {'Omega_m': 0.33046017545727063, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47889996122930045, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:44,967 [classy] Got parameters {'Omega_m': 0.33046017545727063, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:44,967 [classy] Computing new state
2023-07-02 10:33:44,967 [classy] Setting parameters: {'Omega_m': 0.33046017545727063, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:45,011 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.15070897663594}
2023-07-02 10:33:45,011 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:45,013 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0191655
2023-07-02 10:33:45,013 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47889996122930045, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,013 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:45,033 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.57877
2023-07-02 10:33:45,033 [model] Computed derived parameters: {}
2023-07-02 10:33:45,033 [model] Posterior to be computed for parameters {'Omega_m': 0.32403341564303106, 'b1': 0.5014362653419473}
2023-07-02 10:33:45,033 [prior] Evaluating prior at array([0.32403342, 0.50143627])
2023-07-02 10:33:45,033 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:45,033 [model] Got input parameters: {'Omega_m': 0.32403341564303106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5014362653419473, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,033 [classy] Got parameters {'Omega_m': 0.32403341564303106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:45,033 [classy] Re-using computed results
2023-07-02 10:33:45,033 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.89280139973127}
2023-07-02 10:33:45,033 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:45,033 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5014362653419473, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,033 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:45,052 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.65816
2023-07-02 10:33:45,053 [model] Computed derived parameters: {}
2023-07-02 10:33:45,053 [model] Posterior to be computed for parameters {'Omega_m': 0.33653320567807354, 'b1': 0.4747729639949861}
2023-07-02 10:33:45,053 [prior] Evaluating prior at array([0.33653321, 0.47477296])
2023-07-02 10:33:45,053 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:45,053 [model] Got input parameters: {'Omega_m': 0.33653320567807354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4747729639949861, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,053 [classy] Got parameters {'Omega_m': 0.33653320567807354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:45,053 [classy] Computing new state
2023-07-02 10:33:45,053 [classy] Setting parameters: {'Omega_m': 0.33653320567807354, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:45,097 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.46138061245244}
2023-07-02 10:33:45,097 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:45,099 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0336519
2023-07-02 10:33:45,099 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4747729639949861, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,099 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:45,118 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.0847338
2023-07-02 10:33:45,118 [model] Computed derived parameters: {}
2023-07-02 10:33:45,119 [model] Posterior to be computed for parameters {'Omega_m': 0.32403341564303106, 'b1': 0.4655407750908936}
2023-07-02 10:33:45,119 [prior] Evaluating prior at array([0.32403342, 0.46554078])
2023-07-02 10:33:45,119 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:45,119 [model] Got input parameters: {'Omega_m': 0.32403341564303106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4655407750908936, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,119 [classy] Got parameters {'Omega_m': 0.32403341564303106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:45,119 [classy] Re-using computed results
2023-07-02 10:33:45,119 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.89280139973127}
2023-07-02 10:33:45,119 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:45,119 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4655407750908936, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,119 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:45,141 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.59819
2023-07-02 10:33:45,141 [model] Computed derived parameters: {}
2023-07-02 10:33:45,141 [mcmc] New sample, #176:
Omega_m:0.3240334, b1:0.4832673
2023-07-02 10:33:45,141 [model] Posterior to be computed for parameters {'Omega_m': 0.34264983332304466, 'b1': 0.4528897752629857}
2023-07-02 10:33:45,142 [prior] Evaluating prior at array([0.34264983, 0.45288978])
2023-07-02 10:33:45,142 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:45,142 [model] Got input parameters: {'Omega_m': 0.34264983332304466, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4528897752629857, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,142 [classy] Got parameters {'Omega_m': 0.34264983332304466, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:45,142 [classy] Computing new state
2023-07-02 10:33:45,142 [classy] Setting parameters: {'Omega_m': 0.34264983332304466, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:45,186 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.77837329621093}
2023-07-02 10:33:45,186 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:45,188 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0520767
2023-07-02 10:33:45,188 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4528897752629857, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,188 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:45,207 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.864896
2023-07-02 10:33:45,207 [model] Computed derived parameters: {}
2023-07-02 10:33:45,208 [model] Posterior to be computed for parameters {'Omega_m': 0.32403341564303106, 'b1': 0.46633338289153337}
2023-07-02 10:33:45,208 [prior] Evaluating prior at array([0.32403342, 0.46633338])
2023-07-02 10:33:45,208 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:45,208 [model] Got input parameters: {'Omega_m': 0.32403341564303106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46633338289153337, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,208 [classy] Got parameters {'Omega_m': 0.32403341564303106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:45,208 [classy] Re-using computed results
2023-07-02 10:33:45,208 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.89280139973127}
2023-07-02 10:33:45,208 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:45,208 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46633338289153337, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,208 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:45,227 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.67375
2023-07-02 10:33:45,227 [model] Computed derived parameters: {}
2023-07-02 10:33:45,227 [mcmc] New sample, #177:
Omega_m:0.3240334, b1:0.4655408
2023-07-02 10:33:45,227 [model] Posterior to be computed for parameters {'Omega_m': 0.349705053466263, 'b1': 0.4488879274195876}
2023-07-02 10:33:45,227 [prior] Evaluating prior at array([0.34970505, 0.44888793])
2023-07-02 10:33:45,227 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:45,227 [model] Got input parameters: {'Omega_m': 0.349705053466263, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4488879274195876, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,227 [classy] Got parameters {'Omega_m': 0.349705053466263, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:45,227 [classy] Computing new state
2023-07-02 10:33:45,228 [classy] Setting parameters: {'Omega_m': 0.349705053466263, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:45,271 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.00427919243762}
2023-07-02 10:33:45,271 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:45,273 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0778864
2023-07-02 10:33:45,273 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4488879274195876, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,273 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:45,293 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.21381
2023-07-02 10:33:45,293 [model] Computed derived parameters: {}
2023-07-02 10:33:45,293 [model] Posterior to be computed for parameters {'Omega_m': 0.32403341564303106, 'b1': 0.4490166800245185}
2023-07-02 10:33:45,293 [prior] Evaluating prior at array([0.32403342, 0.44901668])
2023-07-02 10:33:45,293 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:45,293 [model] Got input parameters: {'Omega_m': 0.32403341564303106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4490166800245185, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,294 [classy] Got parameters {'Omega_m': 0.32403341564303106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:45,294 [classy] Re-using computed results
2023-07-02 10:33:45,294 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.89280139973127}
2023-07-02 10:33:45,294 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:45,294 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4490166800245185, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,294 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:45,313 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.700274
2023-07-02 10:33:45,313 [model] Computed derived parameters: {}
2023-07-02 10:33:45,313 [model] Posterior to be computed for parameters {'Omega_m': 0.30947067249780436, 'b1': 0.47622966176702947}
2023-07-02 10:33:45,313 [prior] Evaluating prior at array([0.30947067, 0.47622966])
2023-07-02 10:33:45,313 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:45,313 [model] Got input parameters: {'Omega_m': 0.30947067249780436, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47622966176702947, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,313 [classy] Got parameters {'Omega_m': 0.30947067249780436, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:45,313 [classy] Computing new state
2023-07-02 10:33:45,313 [classy] Setting parameters: {'Omega_m': 0.30947067249780436, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:45,357 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.6242783322645}
2023-07-02 10:33:45,357 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:45,359 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000763427
2023-07-02 10:33:45,359 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47622966176702947, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,359 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:45,378 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.28506
2023-07-02 10:33:45,378 [model] Computed derived parameters: {}
2023-07-02 10:33:45,378 [model] Posterior to be computed for parameters {'Omega_m': 0.32403341564303106, 'b1': 0.4926385457301699}
2023-07-02 10:33:45,378 [prior] Evaluating prior at array([0.32403342, 0.49263855])
2023-07-02 10:33:45,378 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:45,378 [model] Got input parameters: {'Omega_m': 0.32403341564303106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4926385457301699, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,378 [classy] Got parameters {'Omega_m': 0.32403341564303106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:45,378 [classy] Re-using computed results
2023-07-02 10:33:45,378 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.89280139973127}
2023-07-02 10:33:45,378 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:45,379 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4926385457301699, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,379 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:45,398 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.2967
2023-07-02 10:33:45,398 [model] Computed derived parameters: {}
2023-07-02 10:33:45,398 [mcmc] New sample, #178:
Omega_m:0.3240334, b1:0.4663334
2023-07-02 10:33:45,398 [model] Posterior to be computed for parameters {'Omega_m': 0.32379923045219844, 'b1': 0.4927976889584669}
2023-07-02 10:33:45,398 [prior] Evaluating prior at array([0.32379923, 0.49279769])
2023-07-02 10:33:45,399 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:45,399 [model] Got input parameters: {'Omega_m': 0.32379923045219844, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4927976889584669, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,399 [classy] Got parameters {'Omega_m': 0.32379923045219844, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:45,399 [classy] Computing new state
2023-07-02 10:33:45,399 [classy] Setting parameters: {'Omega_m': 0.32379923045219844, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:45,443 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.92008976230795}
2023-07-02 10:33:45,443 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:45,445 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00783744
2023-07-02 10:33:45,445 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4927976889584669, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,445 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:45,464 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.33096
2023-07-02 10:33:45,464 [model] Computed derived parameters: {}
2023-07-02 10:33:45,464 [mcmc] New sample, #179:
Omega_m:0.3240334, b1:0.4926385
2023-07-02 10:33:45,464 [model] Posterior to be computed for parameters {'Omega_m': 0.32379923045219844, 'b1': 0.5061427863789978}
2023-07-02 10:33:45,464 [prior] Evaluating prior at array([0.32379923, 0.50614279])
2023-07-02 10:33:45,465 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:45,465 [model] Got input parameters: {'Omega_m': 0.32379923045219844, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5061427863789978, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,465 [classy] Got parameters {'Omega_m': 0.32379923045219844, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:45,465 [classy] Re-using computed results
2023-07-02 10:33:45,465 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.92008976230795}
2023-07-02 10:33:45,465 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:45,465 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5061427863789978, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,465 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:45,484 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.20968
2023-07-02 10:33:45,484 [model] Computed derived parameters: {}
2023-07-02 10:33:45,484 [model] Posterior to be computed for parameters {'Omega_m': 0.3082416705365104, 'b1': 0.5033700069628775}
2023-07-02 10:33:45,484 [prior] Evaluating prior at array([0.30824167, 0.50337001])
2023-07-02 10:33:45,484 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:45,484 [model] Got input parameters: {'Omega_m': 0.3082416705365104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5033700069628775, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,484 [classy] Got parameters {'Omega_m': 0.3082416705365104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:45,484 [classy] Computing new state
2023-07-02 10:33:45,484 [classy] Setting parameters: {'Omega_m': 0.3082416705365104, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:45,528 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.77369700363604}
2023-07-02 10:33:45,528 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:45,530 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00131783
2023-07-02 10:33:45,530 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5033700069628775, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,530 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:45,549 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.42
2023-07-02 10:33:45,549 [model] Computed derived parameters: {}
2023-07-02 10:33:45,550 [mcmc] New sample, #180:
Omega_m:0.3237992, b1:0.4927977
2023-07-02 10:33:45,550 [model] Posterior to be computed for parameters {'Omega_m': 0.3082416705365104, 'b1': 0.5159399378558468}
2023-07-02 10:33:45,550 [prior] Evaluating prior at array([0.30824167, 0.51593994])
2023-07-02 10:33:45,550 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:45,550 [model] Got input parameters: {'Omega_m': 0.3082416705365104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5159399378558468, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,550 [classy] Got parameters {'Omega_m': 0.3082416705365104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:45,550 [classy] Re-using computed results
2023-07-02 10:33:45,550 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.77369700363604}
2023-07-02 10:33:45,550 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:45,550 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5159399378558468, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,550 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:45,569 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.61749
2023-07-02 10:33:45,570 [model] Computed derived parameters: {}
2023-07-02 10:33:45,570 [mcmc] New sample, #181:
Omega_m:0.3082417, b1:0.50337
2023-07-02 10:33:45,570 [model] Posterior to be computed for parameters {'Omega_m': 0.3015264522590826, 'b1': 0.5205033413383175}
2023-07-02 10:33:45,570 [prior] Evaluating prior at array([0.30152645, 0.52050334])
2023-07-02 10:33:45,570 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:45,570 [model] Got input parameters: {'Omega_m': 0.3015264522590826, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5205033413383175, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,570 [classy] Got parameters {'Omega_m': 0.3015264522590826, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:45,570 [classy] Computing new state
2023-07-02 10:33:45,570 [classy] Setting parameters: {'Omega_m': 0.3015264522590826, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:45,614 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.59949013639505}
2023-07-02 10:33:45,614 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:45,616 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00777038
2023-07-02 10:33:45,616 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5205033413383175, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,616 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:45,636 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.76545
2023-07-02 10:33:45,636 [model] Computed derived parameters: {}
2023-07-02 10:33:45,636 [model] Posterior to be computed for parameters {'Omega_m': 0.3082416705365104, 'b1': 0.5093262837330818}
2023-07-02 10:33:45,636 [prior] Evaluating prior at array([0.30824167, 0.50932628])
2023-07-02 10:33:45,636 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:45,636 [model] Got input parameters: {'Omega_m': 0.3082416705365104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5093262837330818, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,636 [classy] Got parameters {'Omega_m': 0.3082416705365104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:45,636 [classy] Re-using computed results
2023-07-02 10:33:45,636 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.77369700363604}
2023-07-02 10:33:45,636 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:45,636 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5093262837330818, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,636 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:45,656 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.61811
2023-07-02 10:33:45,656 [model] Computed derived parameters: {}
2023-07-02 10:33:45,656 [mcmc] New sample, #182:
Omega_m:0.3082417, b1:0.5159399
2023-07-02 10:33:45,656 [model] Posterior to be computed for parameters {'Omega_m': 0.33809722395202446, 'b1': 0.489037600506595}
2023-07-02 10:33:45,656 [prior] Evaluating prior at array([0.33809722, 0.4890376 ])
2023-07-02 10:33:45,657 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:45,657 [model] Got input parameters: {'Omega_m': 0.33809722395202446, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.489037600506595, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,657 [classy] Got parameters {'Omega_m': 0.33809722395202446, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:45,657 [classy] Computing new state
2023-07-02 10:33:45,657 [classy] Setting parameters: {'Omega_m': 0.33809722395202446, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:45,700 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.28567206494165}
2023-07-02 10:33:45,701 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:45,702 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0380036
2023-07-02 10:33:45,703 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.489037600506595, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,703 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:45,722 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.39295
2023-07-02 10:33:45,722 [model] Computed derived parameters: {}
2023-07-02 10:33:45,722 [model] Posterior to be computed for parameters {'Omega_m': 0.3082416705365104, 'b1': 0.5140481896305551}
2023-07-02 10:33:45,722 [prior] Evaluating prior at array([0.30824167, 0.51404819])
2023-07-02 10:33:45,722 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:45,722 [model] Got input parameters: {'Omega_m': 0.3082416705365104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5140481896305551, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,722 [classy] Got parameters {'Omega_m': 0.3082416705365104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:45,722 [classy] Re-using computed results
2023-07-02 10:33:45,722 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.77369700363604}
2023-07-02 10:33:45,722 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:45,723 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5140481896305551, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,723 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:45,742 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.64162
2023-07-02 10:33:45,742 [model] Computed derived parameters: {}
2023-07-02 10:33:45,742 [mcmc] New sample, #183:
Omega_m:0.3082417, b1:0.5093263
2023-07-02 10:33:45,742 [model] Posterior to be computed for parameters {'Omega_m': 0.297909171408322, 'b1': 0.5210697577399184}
2023-07-02 10:33:45,742 [prior] Evaluating prior at array([0.29790917, 0.52106976])
2023-07-02 10:33:45,743 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:45,743 [model] Got input parameters: {'Omega_m': 0.297909171408322, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5210697577399184, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,743 [classy] Got parameters {'Omega_m': 0.297909171408322, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:45,743 [classy] Computing new state
2023-07-02 10:33:45,743 [classy] Setting parameters: {'Omega_m': 0.297909171408322, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:45,786 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.05106662635163}
2023-07-02 10:33:45,786 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:45,788 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0137164
2023-07-02 10:33:45,788 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5210697577399184, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,788 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:45,808 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.842096
2023-07-02 10:33:45,808 [model] Computed derived parameters: {}
2023-07-02 10:33:45,809 [model] Posterior to be computed for parameters {'Omega_m': 0.3082416705365104, 'b1': 0.4909315276001731}
2023-07-02 10:33:45,809 [prior] Evaluating prior at array([0.30824167, 0.49093153])
2023-07-02 10:33:45,809 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:45,809 [model] Got input parameters: {'Omega_m': 0.3082416705365104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4909315276001731, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,809 [classy] Got parameters {'Omega_m': 0.3082416705365104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:45,809 [classy] Re-using computed results
2023-07-02 10:33:45,809 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.77369700363604}
2023-07-02 10:33:45,809 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:45,809 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4909315276001731, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,809 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:45,828 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.41428
2023-07-02 10:33:45,828 [model] Computed derived parameters: {}
2023-07-02 10:33:45,828 [mcmc] New sample, #184:
Omega_m:0.3082417, b1:0.5140482
2023-07-02 10:33:45,828 [model] Posterior to be computed for parameters {'Omega_m': 0.31559667768341493, 'b1': 0.4859333482646479}
2023-07-02 10:33:45,828 [prior] Evaluating prior at array([0.31559668, 0.48593335])
2023-07-02 10:33:45,828 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:45,828 [model] Got input parameters: {'Omega_m': 0.31559667768341493, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4859333482646479, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,828 [classy] Got parameters {'Omega_m': 0.31559667768341493, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:45,828 [classy] Computing new state
2023-07-02 10:33:45,828 [classy] Setting parameters: {'Omega_m': 0.31559667768341493, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:45,872 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.88722429362002}
2023-07-02 10:33:45,873 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:45,874 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000792015
2023-07-02 10:33:45,874 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4859333482646479, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,874 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:45,894 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.45277
2023-07-02 10:33:45,894 [model] Computed derived parameters: {}
2023-07-02 10:33:45,894 [mcmc] New sample, #185:
Omega_m:0.3082417, b1:0.4909315
2023-07-02 10:33:45,894 [model] Posterior to be computed for parameters {'Omega_m': 0.31559667768341493, 'b1': 0.4902753553894143}
2023-07-02 10:33:45,895 [prior] Evaluating prior at array([0.31559668, 0.49027536])
2023-07-02 10:33:45,895 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:45,895 [model] Got input parameters: {'Omega_m': 0.31559667768341493, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4902753553894143, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,895 [classy] Got parameters {'Omega_m': 0.31559667768341493, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:45,895 [classy] Re-using computed results
2023-07-02 10:33:45,895 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.88722429362002}
2023-07-02 10:33:45,895 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:45,895 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4902753553894143, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,895 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:45,914 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.70978
2023-07-02 10:33:45,914 [model] Computed derived parameters: {}
2023-07-02 10:33:45,914 [mcmc] New sample, #186:
Omega_m:0.3155967, b1:0.4859333
2023-07-02 10:33:45,914 [model] Posterior to be computed for parameters {'Omega_m': 0.312544381408393, 'b1': 0.4923495782777137}
2023-07-02 10:33:45,914 [prior] Evaluating prior at array([0.31254438, 0.49234958])
2023-07-02 10:33:45,915 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:45,915 [model] Got input parameters: {'Omega_m': 0.312544381408393, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4923495782777137, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,915 [classy] Got parameters {'Omega_m': 0.312544381408393, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:45,915 [classy] Computing new state
2023-07-02 10:33:45,915 [classy] Setting parameters: {'Omega_m': 0.312544381408393, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:45,958 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.252858993582}
2023-07-02 10:33:45,959 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:45,960 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000202597
2023-07-02 10:33:45,960 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4923495782777137, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,960 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:45,980 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.47468
2023-07-02 10:33:45,980 [model] Computed derived parameters: {}
2023-07-02 10:33:45,980 [model] Posterior to be computed for parameters {'Omega_m': 0.31559667768341493, 'b1': 0.48223637573967726}
2023-07-02 10:33:45,980 [prior] Evaluating prior at array([0.31559668, 0.48223638])
2023-07-02 10:33:45,980 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:45,980 [model] Got input parameters: {'Omega_m': 0.31559667768341493, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48223637573967726, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,980 [classy] Got parameters {'Omega_m': 0.31559667768341493, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:45,980 [classy] Re-using computed results
2023-07-02 10:33:45,980 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.88722429362002}
2023-07-02 10:33:45,980 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:45,980 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48223637573967726, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:45,980 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:46,000 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.1569
2023-07-02 10:33:46,000 [model] Computed derived parameters: {}
2023-07-02 10:33:46,000 [model] Posterior to be computed for parameters {'Omega_m': 0.3245382177959482, 'b1': 0.4841990294082706}
2023-07-02 10:33:46,000 [prior] Evaluating prior at array([0.32453822, 0.48419903])
2023-07-02 10:33:46,001 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:46,001 [model] Got input parameters: {'Omega_m': 0.3245382177959482, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4841990294082706, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:46,001 [classy] Got parameters {'Omega_m': 0.3245382177959482, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:46,001 [classy] Computing new state
2023-07-02 10:33:46,001 [classy] Setting parameters: {'Omega_m': 0.3245382177959482, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:46,044 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.8340372743711}
2023-07-02 10:33:46,044 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:46,046 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00885172
2023-07-02 10:33:46,046 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4841990294082706, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:46,046 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:46,066 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.45096
2023-07-02 10:33:46,066 [model] Computed derived parameters: {}
2023-07-02 10:33:46,066 [mcmc] New sample, #187:
Omega_m:0.3155967, b1:0.4902754
2023-07-02 10:33:46,066 [model] Posterior to be computed for parameters {'Omega_m': 0.3245382177959482, 'b1': 0.48976878495546877}
2023-07-02 10:33:46,066 [prior] Evaluating prior at array([0.32453822, 0.48976878])
2023-07-02 10:33:46,066 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:46,066 [model] Got input parameters: {'Omega_m': 0.3245382177959482, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48976878495546877, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:46,066 [classy] Got parameters {'Omega_m': 0.3245382177959482, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:46,066 [classy] Re-using computed results
2023-07-02 10:33:46,066 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.8340372743711}
2023-07-02 10:33:46,066 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:46,066 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48976878495546877, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:46,066 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:46,086 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.33075
2023-07-02 10:33:46,086 [model] Computed derived parameters: {}
2023-07-02 10:33:46,086 [mcmc] New sample, #188:
Omega_m:0.3245382, b1:0.484199
2023-07-02 10:33:46,086 [model] Posterior to be computed for parameters {'Omega_m': 0.3317922807580645, 'b1': 0.48483920339671965}
2023-07-02 10:33:46,086 [prior] Evaluating prior at array([0.33179228, 0.4848392 ])
2023-07-02 10:33:46,086 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:46,086 [model] Got input parameters: {'Omega_m': 0.3317922807580645, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48483920339671965, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:46,086 [classy] Got parameters {'Omega_m': 0.3317922807580645, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:46,086 [classy] Computing new state
2023-07-02 10:33:46,086 [classy] Setting parameters: {'Omega_m': 0.3317922807580645, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:46,131 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.99853320467642}
2023-07-02 10:33:46,132 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:46,133 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0220099
2023-07-02 10:33:46,134 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48483920339671965, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:46,134 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:46,154 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.863038
2023-07-02 10:33:46,154 [model] Computed derived parameters: {}
2023-07-02 10:33:46,154 [mcmc] New sample, #189:
Omega_m:0.3245382, b1:0.4897688
2023-07-02 10:33:46,154 [model] Posterior to be computed for parameters {'Omega_m': 0.3317922807580645, 'b1': 0.4891198468501226}
2023-07-02 10:33:46,154 [prior] Evaluating prior at array([0.33179228, 0.48911985])
2023-07-02 10:33:46,155 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:46,155 [model] Got input parameters: {'Omega_m': 0.3317922807580645, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4891198468501226, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:46,155 [classy] Got parameters {'Omega_m': 0.3317922807580645, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:46,155 [classy] Re-using computed results
2023-07-02 10:33:46,155 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.99853320467642}
2023-07-02 10:33:46,155 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:46,155 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4891198468501226, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:46,155 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:46,174 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.452556
2023-07-02 10:33:46,174 [model] Computed derived parameters: {}
2023-07-02 10:33:46,175 [model] Posterior to be computed for parameters {'Omega_m': 0.315958994636781, 'b1': 0.4955988943017331}
2023-07-02 10:33:46,175 [prior] Evaluating prior at array([0.31595899, 0.49559889])
2023-07-02 10:33:46,175 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:46,175 [model] Got input parameters: {'Omega_m': 0.315958994636781, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4955988943017331, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:46,175 [classy] Got parameters {'Omega_m': 0.315958994636781, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:46,175 [classy] Computing new state
2023-07-02 10:33:46,175 [classy] Setting parameters: {'Omega_m': 0.315958994636781, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:46,219 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.84403458031568}
2023-07-02 10:33:46,219 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:46,221 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00093658
2023-07-02 10:33:46,221 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4955988943017331, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:46,221 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:46,240 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.89909
2023-07-02 10:33:46,241 [model] Computed derived parameters: {}
2023-07-02 10:33:46,241 [mcmc] New sample, #190:
Omega_m:0.3317923, b1:0.4848392
2023-07-02 10:33:46,241 [model] Posterior to be computed for parameters {'Omega_m': 0.315958994636781, 'b1': 0.5015973502325001}
2023-07-02 10:33:46,241 [prior] Evaluating prior at array([0.31595899, 0.50159735])
2023-07-02 10:33:46,241 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:46,241 [model] Got input parameters: {'Omega_m': 0.315958994636781, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5015973502325001, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:46,241 [classy] Got parameters {'Omega_m': 0.315958994636781, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:46,241 [classy] Re-using computed results
2023-07-02 10:33:46,241 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.84403458031568}
2023-07-02 10:33:46,241 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:46,241 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5015973502325001, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:46,241 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:46,261 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.89923
2023-07-02 10:33:46,261 [model] Computed derived parameters: {}
2023-07-02 10:33:46,261 [mcmc] New sample, #191:
Omega_m:0.315959, b1:0.4955989
2023-07-02 10:33:46,261 [model] Posterior to be computed for parameters {'Omega_m': 0.32333359787158017, 'b1': 0.4965858541510335}
2023-07-02 10:33:46,261 [prior] Evaluating prior at array([0.3233336 , 0.49658585])
2023-07-02 10:33:46,261 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:46,261 [model] Got input parameters: {'Omega_m': 0.32333359787158017, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4965858541510335, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:46,262 [classy] Got parameters {'Omega_m': 0.32333359787158017, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:46,262 [classy] Computing new state
2023-07-02 10:33:46,262 [classy] Setting parameters: {'Omega_m': 0.32333359787158017, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:46,305 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.97440418324368}
2023-07-02 10:33:46,306 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:46,307 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00722988
2023-07-02 10:33:46,307 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4965858541510335, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:46,307 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:46,327 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.21207
2023-07-02 10:33:46,327 [model] Computed derived parameters: {}
2023-07-02 10:33:46,327 [mcmc] New sample, #192:
Omega_m:0.315959, b1:0.5015974
2023-07-02 10:33:46,327 [model] Posterior to be computed for parameters {'Omega_m': 0.32333359787158017, 'b1': 0.5014256129697636}
2023-07-02 10:33:46,327 [prior] Evaluating prior at array([0.3233336 , 0.50142561])
2023-07-02 10:33:46,327 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:46,327 [model] Got input parameters: {'Omega_m': 0.32333359787158017, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5014256129697636, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:46,327 [classy] Got parameters {'Omega_m': 0.32333359787158017, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:46,327 [classy] Re-using computed results
2023-07-02 10:33:46,327 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.97440418324368}
2023-07-02 10:33:46,327 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:46,327 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5014256129697636, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:46,327 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:46,347 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.84205
2023-07-02 10:33:46,347 [model] Computed derived parameters: {}
2023-07-02 10:33:46,347 [mcmc] New sample, #193:
Omega_m:0.3233336, b1:0.4965859
2023-07-02 10:33:46,347 [model] Posterior to be computed for parameters {'Omega_m': 0.31243757375309117, 'b1': 0.5088301309397205}
2023-07-02 10:33:46,347 [prior] Evaluating prior at array([0.31243757, 0.50883013])
2023-07-02 10:33:46,347 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:46,347 [model] Got input parameters: {'Omega_m': 0.31243757375309117, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5088301309397205, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:46,347 [classy] Got parameters {'Omega_m': 0.31243757375309117, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:46,348 [classy] Computing new state
2023-07-02 10:33:46,348 [classy] Setting parameters: {'Omega_m': 0.31243757375309117, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:46,391 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.26571301428257}
2023-07-02 10:33:46,391 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:46,393 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000202499
2023-07-02 10:33:46,393 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5088301309397205, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:46,393 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:46,413 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.844
2023-07-02 10:33:46,413 [model] Computed derived parameters: {}
2023-07-02 10:33:46,413 [mcmc] New sample, #194:
Omega_m:0.3233336, b1:0.5014256
2023-07-02 10:33:46,414 [model] Posterior to be computed for parameters {'Omega_m': 0.31243757375309117, 'b1': 0.521968345890676}
2023-07-02 10:33:46,414 [prior] Evaluating prior at array([0.31243757, 0.52196835])
2023-07-02 10:33:46,414 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:46,414 [model] Got input parameters: {'Omega_m': 0.31243757375309117, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.521968345890676, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:46,414 [classy] Got parameters {'Omega_m': 0.31243757375309117, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:46,414 [classy] Re-using computed results
2023-07-02 10:33:46,414 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.26571301428257}
2023-07-02 10:33:46,414 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:46,414 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.521968345890676, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:46,414 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:46,433 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.09608
2023-07-02 10:33:46,433 [model] Computed derived parameters: {}
2023-07-02 10:33:46,433 [mcmc] New sample, #195:
Omega_m:0.3124376, b1:0.5088301
2023-07-02 10:33:46,434 [model] Posterior to be computed for parameters {'Omega_m': 0.3147140659322394, 'b1': 0.5204213295601626}
2023-07-02 10:33:46,434 [prior] Evaluating prior at array([0.31471407, 0.52042133])
2023-07-02 10:33:46,434 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:46,434 [model] Got input parameters: {'Omega_m': 0.3147140659322394, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5204213295601626, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:46,434 [classy] Got parameters {'Omega_m': 0.3147140659322394, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:46,434 [classy] Computing new state
2023-07-02 10:33:46,434 [classy] Setting parameters: {'Omega_m': 0.3147140659322394, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:46,478 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.99262014980707}
2023-07-02 10:33:46,478 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:46,480 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00050576
2023-07-02 10:33:46,480 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5204213295601626, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:46,480 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:46,499 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.87451
2023-07-02 10:33:46,500 [model] Computed derived parameters: {}
2023-07-02 10:33:46,500 [model] Posterior to be computed for parameters {'Omega_m': 0.31243757375309117, 'b1': 0.536920470219604}
2023-07-02 10:33:46,500 [prior] Evaluating prior at array([0.31243757, 0.53692047])
2023-07-02 10:33:46,500 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:46,500 [model] Got input parameters: {'Omega_m': 0.31243757375309117, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.536920470219604, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:46,500 [classy] Got parameters {'Omega_m': 0.31243757375309117, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:46,500 [classy] Re-using computed results
2023-07-02 10:33:46,500 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.26571301428257}
2023-07-02 10:33:46,500 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:46,500 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.536920470219604, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:46,500 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:46,520 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.0548508
2023-07-02 10:33:46,520 [model] Computed derived parameters: {}
2023-07-02 10:33:46,520 [model] Posterior to be computed for parameters {'Omega_m': 0.3003980538281571, 'b1': 0.5301499395311084}
2023-07-02 10:33:46,520 [prior] Evaluating prior at array([0.30039805, 0.53014994])
2023-07-02 10:33:46,520 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:46,520 [model] Got input parameters: {'Omega_m': 0.3003980538281571, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5301499395311084, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:46,520 [classy] Got parameters {'Omega_m': 0.3003980538281571, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:46,520 [classy] Computing new state
2023-07-02 10:33:46,520 [classy] Setting parameters: {'Omega_m': 0.3003980538281571, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:46,564 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.73983423792114}
2023-07-02 10:33:46,564 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:46,566 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00943565
2023-07-02 10:33:46,566 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5301499395311084, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:46,566 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:46,585 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.58847
2023-07-02 10:33:46,585 [model] Computed derived parameters: {}
2023-07-02 10:33:46,585 [model] Posterior to be computed for parameters {'Omega_m': 0.31243757375309117, 'b1': 0.5308510091750666}
2023-07-02 10:33:46,585 [prior] Evaluating prior at array([0.31243757, 0.53085101])
2023-07-02 10:33:46,586 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:46,586 [model] Got input parameters: {'Omega_m': 0.31243757375309117, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5308510091750666, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:46,586 [classy] Got parameters {'Omega_m': 0.31243757375309117, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:46,586 [classy] Re-using computed results
2023-07-02 10:33:46,586 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.26571301428257}
2023-07-02 10:33:46,586 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:46,586 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5308510091750666, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:46,586 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:46,605 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.03948
2023-07-02 10:33:46,605 [model] Computed derived parameters: {}
2023-07-02 10:33:46,606 [model] Posterior to be computed for parameters {'Omega_m': 0.30755889902258404, 'b1': 0.5252837051739138}
2023-07-02 10:33:46,606 [prior] Evaluating prior at array([0.3075589 , 0.52528371])
2023-07-02 10:33:46,606 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:46,606 [model] Got input parameters: {'Omega_m': 0.30755889902258404, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5252837051739138, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:46,606 [classy] Got parameters {'Omega_m': 0.30755889902258404, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:46,606 [classy] Computing new state
2023-07-02 10:33:46,606 [classy] Setting parameters: {'Omega_m': 0.30755889902258404, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:46,650 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.85693560003128}
2023-07-02 10:33:46,650 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:46,652 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00170834
2023-07-02 10:33:46,652 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5252837051739138, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:46,652 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:46,672 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.23526
2023-07-02 10:33:46,672 [model] Computed derived parameters: {}
2023-07-02 10:33:46,672 [mcmc] New sample, #196:
Omega_m:0.3124376, b1:0.5219683
2023-07-02 10:33:46,672 [model] Posterior to be computed for parameters {'Omega_m': 0.30755889902258404, 'b1': 0.537709837602294}
2023-07-02 10:33:46,672 [prior] Evaluating prior at array([0.3075589 , 0.53770984])
2023-07-02 10:33:46,672 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:46,672 [model] Got input parameters: {'Omega_m': 0.30755889902258404, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.537709837602294, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:46,672 [classy] Got parameters {'Omega_m': 0.30755889902258404, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:46,672 [classy] Re-using computed results
2023-07-02 10:33:46,672 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.85693560003128}
2023-07-02 10:33:46,672 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:46,672 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.537709837602294, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:46,672 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:46,691 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.02967
2023-07-02 10:33:46,691 [model] Computed derived parameters: {}
2023-07-02 10:33:46,692 [model] Posterior to be computed for parameters {'Omega_m': 0.3159705894659949, 'b1': 0.5195674446032105}
2023-07-02 10:33:46,692 [prior] Evaluating prior at array([0.31597059, 0.51956744])
2023-07-02 10:33:46,692 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:46,692 [model] Got input parameters: {'Omega_m': 0.3159705894659949, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195674446032105, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:46,692 [classy] Got parameters {'Omega_m': 0.3159705894659949, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:46,692 [classy] Computing new state
2023-07-02 10:33:46,692 [classy] Setting parameters: {'Omega_m': 0.3159705894659949, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:46,736 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.84265344702402}
2023-07-02 10:33:46,736 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:46,737 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000941463
2023-07-02 10:33:46,738 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195674446032105, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:46,738 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:46,757 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.71018
2023-07-02 10:33:46,757 [model] Computed derived parameters: {}
2023-07-02 10:33:46,758 [model] Posterior to be computed for parameters {'Omega_m': 0.30755889902258404, 'b1': 0.47877119370007204}
2023-07-02 10:33:46,758 [prior] Evaluating prior at array([0.3075589 , 0.47877119])
2023-07-02 10:33:46,758 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:46,758 [model] Got input parameters: {'Omega_m': 0.30755889902258404, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47877119370007204, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:46,758 [classy] Got parameters {'Omega_m': 0.30755889902258404, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:46,758 [classy] Re-using computed results
2023-07-02 10:33:46,758 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.85693560003128}
2023-07-02 10:33:46,758 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:46,758 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47877119370007204, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:46,758 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:46,777 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.592756
2023-07-02 10:33:46,777 [model] Computed derived parameters: {}
2023-07-02 10:33:46,777 [model] Posterior to be computed for parameters {'Omega_m': 0.3145855450493686, 'b1': 0.5205086673979266}
2023-07-02 10:33:46,778 [prior] Evaluating prior at array([0.31458555, 0.52050867])
2023-07-02 10:33:46,778 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:46,778 [model] Got input parameters: {'Omega_m': 0.3145855450493686, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5205086673979266, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:46,778 [classy] Got parameters {'Omega_m': 0.3145855450493686, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:46,778 [classy] Computing new state
2023-07-02 10:33:46,778 [classy] Setting parameters: {'Omega_m': 0.3145855450493686, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:46,822 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.00798939289882}
2023-07-02 10:33:46,822 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:46,824 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000471897
2023-07-02 10:33:46,824 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5205086673979266, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:46,824 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:46,843 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.88964
2023-07-02 10:33:46,843 [model] Computed derived parameters: {}
2023-07-02 10:33:46,843 [mcmc] New sample, #197:
Omega_m:0.3075589, b1:0.5252837
2023-07-02 10:33:46,843 [model] Posterior to be computed for parameters {'Omega_m': 0.3145855450493686, 'b1': 0.5282576984998295}
2023-07-02 10:33:46,843 [prior] Evaluating prior at array([0.31458555, 0.5282577 ])
2023-07-02 10:33:46,843 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:46,843 [model] Got input parameters: {'Omega_m': 0.3145855450493686, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5282576984998295, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:46,843 [classy] Got parameters {'Omega_m': 0.3145855450493686, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:46,843 [classy] Re-using computed results
2023-07-02 10:33:46,843 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.00798939289882}
2023-07-02 10:33:46,844 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:46,844 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5282576984998295, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:46,844 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:46,863 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.882426
2023-07-02 10:33:46,864 [model] Computed derived parameters: {}
2023-07-02 10:33:46,864 [mcmc] New sample, #198:
Omega_m:0.3145855, b1:0.5205087
2023-07-02 10:33:46,864 [model] Posterior to be computed for parameters {'Omega_m': 0.2912970619094546, 'b1': 0.5440836539150645}
2023-07-02 10:33:46,864 [prior] Evaluating prior at array([0.29129706, 0.54408365])
2023-07-02 10:33:46,864 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:46,864 [model] Got input parameters: {'Omega_m': 0.2912970619094546, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5440836539150645, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:46,864 [classy] Got parameters {'Omega_m': 0.2912970619094546, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:46,864 [classy] Computing new state
2023-07-02 10:33:46,864 [classy] Setting parameters: {'Omega_m': 0.2912970619094546, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:46,908 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.88902121025848}
2023-07-02 10:33:46,908 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:46,910 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0292506
2023-07-02 10:33:46,910 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5440836539150645, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:46,910 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:46,929 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.623573
2023-07-02 10:33:46,929 [model] Computed derived parameters: {}
2023-07-02 10:33:46,929 [model] Posterior to be computed for parameters {'Omega_m': 0.3145855450493686, 'b1': 0.5314675612698608}
2023-07-02 10:33:46,929 [prior] Evaluating prior at array([0.31458555, 0.53146756])
2023-07-02 10:33:46,930 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:46,930 [model] Got input parameters: {'Omega_m': 0.3145855450493686, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5314675612698608, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:46,930 [classy] Got parameters {'Omega_m': 0.3145855450493686, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:46,930 [classy] Re-using computed results
2023-07-02 10:33:46,930 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.00798939289882}
2023-07-02 10:33:46,930 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:46,930 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5314675612698608, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:46,930 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:46,949 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.362962
2023-07-02 10:33:46,949 [model] Computed derived parameters: {}
2023-07-02 10:33:46,949 [model] Posterior to be computed for parameters {'Omega_m': 0.34437280067575454, 'b1': 0.5080154278180846}
2023-07-02 10:33:46,949 [prior] Evaluating prior at array([0.3443728 , 0.50801543])
2023-07-02 10:33:46,949 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:46,949 [model] Got input parameters: {'Omega_m': 0.34437280067575454, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5080154278180846, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:46,949 [classy] Got parameters {'Omega_m': 0.34437280067575454, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:46,949 [classy] Computing new state
2023-07-02 10:33:46,949 [classy] Setting parameters: {'Omega_m': 0.34437280067575454, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:46,993 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.58797985775968}
2023-07-02 10:33:46,993 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:46,995 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0579384
2023-07-02 10:33:46,995 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5080154278180846, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:46,995 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:47,015 [fs_likelihood.fslikelihood] Computed log-likelihood = -12.1712
2023-07-02 10:33:47,015 [model] Computed derived parameters: {}
2023-07-02 10:33:47,015 [model] Posterior to be computed for parameters {'Omega_m': 0.3145855450493686, 'b1': 0.5852542050246913}
2023-07-02 10:33:47,016 [prior] Evaluating prior at array([0.31458555, 0.58525421])
2023-07-02 10:33:47,016 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:47,016 [model] Got input parameters: {'Omega_m': 0.3145855450493686, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5852542050246913, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:47,016 [classy] Got parameters {'Omega_m': 0.3145855450493686, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:47,016 [classy] Re-using computed results
2023-07-02 10:33:47,016 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.00798939289882}
2023-07-02 10:33:47,016 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:47,016 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5852542050246913, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:47,016 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:47,037 [fs_likelihood.fslikelihood] Computed log-likelihood = -17.8195
2023-07-02 10:33:47,037 [model] Computed derived parameters: {}
2023-07-02 10:33:47,037 [model] Posterior to be computed for parameters {'Omega_m': 0.3150821857730402, 'b1': 0.5279202006085758}
2023-07-02 10:33:47,037 [prior] Evaluating prior at array([0.31508219, 0.5279202 ])
2023-07-02 10:33:47,038 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:47,038 [model] Got input parameters: {'Omega_m': 0.3150821857730402, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5279202006085758, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:47,038 [classy] Got parameters {'Omega_m': 0.3150821857730402, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:47,038 [classy] Computing new state
2023-07-02 10:33:47,038 [classy] Setting parameters: {'Omega_m': 0.3150821857730402, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:47,082 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.948627650425}
2023-07-02 10:33:47,082 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:47,084 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000613784
2023-07-02 10:33:47,084 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5279202006085758, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:47,084 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:47,103 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.796471
2023-07-02 10:33:47,103 [model] Computed derived parameters: {}
2023-07-02 10:33:47,103 [model] Posterior to be computed for parameters {'Omega_m': 0.3145855450493686, 'b1': 0.521609772966243}
2023-07-02 10:33:47,103 [prior] Evaluating prior at array([0.31458555, 0.52160977])
2023-07-02 10:33:47,103 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:47,103 [model] Got input parameters: {'Omega_m': 0.3145855450493686, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.521609772966243, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:47,104 [classy] Got parameters {'Omega_m': 0.3145855450493686, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:47,104 [classy] Re-using computed results
2023-07-02 10:33:47,104 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.00798939289882}
2023-07-02 10:33:47,104 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:47,104 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.521609772966243, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:47,104 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:47,125 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.76759
2023-07-02 10:33:47,125 [model] Computed derived parameters: {}
2023-07-02 10:33:47,125 [mcmc] New sample, #199:
Omega_m:0.3145855, b1:0.5282577
2023-07-02 10:33:47,125 [model] Posterior to be computed for parameters {'Omega_m': 0.3299036991105662, 'b1': 0.5112001459519045}
2023-07-02 10:33:47,125 [prior] Evaluating prior at array([0.3299037 , 0.51120015])
2023-07-02 10:33:47,125 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:47,125 [model] Got input parameters: {'Omega_m': 0.3299036991105662, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5112001459519045, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:47,125 [classy] Got parameters {'Omega_m': 0.3299036991105662, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:47,125 [classy] Computing new state
2023-07-02 10:33:47,125 [classy] Setting parameters: {'Omega_m': 0.3299036991105662, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:47,175 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.21443943641063}
2023-07-02 10:33:47,176 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:47,178 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0180338
2023-07-02 10:33:47,178 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5112001459519045, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:47,178 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:47,202 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.28858
2023-07-02 10:33:47,203 [model] Computed derived parameters: {}
2023-07-02 10:33:47,203 [model] Posterior to be computed for parameters {'Omega_m': 0.3145855450493686, 'b1': 0.5230157272131382}
2023-07-02 10:33:47,203 [prior] Evaluating prior at array([0.31458555, 0.52301573])
2023-07-02 10:33:47,203 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:47,203 [model] Got input parameters: {'Omega_m': 0.3145855450493686, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5230157272131382, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:47,203 [classy] Got parameters {'Omega_m': 0.3145855450493686, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:47,203 [classy] Re-using computed results
2023-07-02 10:33:47,203 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.00798939289882}
2023-07-02 10:33:47,203 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:47,203 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5230157272131382, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:47,203 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:47,228 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.60166
2023-07-02 10:33:47,228 [model] Computed derived parameters: {}
2023-07-02 10:33:47,228 [mcmc] New sample, #200:
Omega_m:0.3145855, b1:0.5216098
2023-07-02 10:33:47,228 [model] Posterior to be computed for parameters {'Omega_m': 0.31839181004470785, 'b1': 0.5204291362465686}
2023-07-02 10:33:47,228 [prior] Evaluating prior at array([0.31839181, 0.52042914])
2023-07-02 10:33:47,228 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:47,228 [model] Got input parameters: {'Omega_m': 0.31839181004470785, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5204291362465686, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:47,228 [classy] Got parameters {'Omega_m': 0.31839181004470785, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:47,228 [classy] Computing new state
2023-07-02 10:33:47,228 [classy] Setting parameters: {'Omega_m': 0.31839181004470785, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:47,273 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.5551759235056}
2023-07-02 10:33:47,273 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:47,275 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00231137
2023-07-02 10:33:47,275 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5204291362465686, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:47,275 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:47,295 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.958418
2023-07-02 10:33:47,295 [model] Computed derived parameters: {}
2023-07-02 10:33:47,295 [mcmc] New sample, #201:
Omega_m:0.3145855, b1:0.5230157
2023-07-02 10:33:47,295 [model] Posterior to be computed for parameters {'Omega_m': 0.31839181004470785, 'b1': 0.518784933095138}
2023-07-02 10:33:47,295 [prior] Evaluating prior at array([0.31839181, 0.51878493])
2023-07-02 10:33:47,295 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:47,295 [model] Got input parameters: {'Omega_m': 0.31839181004470785, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.518784933095138, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:47,295 [classy] Got parameters {'Omega_m': 0.31839181004470785, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:47,295 [classy] Re-using computed results
2023-07-02 10:33:47,296 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.5551759235056}
2023-07-02 10:33:47,296 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:47,296 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.518784933095138, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:47,296 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:47,316 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.19324
2023-07-02 10:33:47,316 [model] Computed derived parameters: {}
2023-07-02 10:33:47,316 [mcmc] New sample, #202:
Omega_m:0.3183918, b1:0.5204291
2023-07-02 10:33:47,317 [model] Posterior to be computed for parameters {'Omega_m': 0.33039425861795846, 'b1': 0.5106285317162795}
2023-07-02 10:33:47,317 [prior] Evaluating prior at array([0.33039426, 0.51062853])
2023-07-02 10:33:47,317 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:47,317 [model] Got input parameters: {'Omega_m': 0.33039425861795846, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5106285317162795, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:47,317 [classy] Got parameters {'Omega_m': 0.33039425861795846, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:47,317 [classy] Computing new state
2023-07-02 10:33:47,317 [classy] Setting parameters: {'Omega_m': 0.33039425861795846, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:47,362 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.15825337803395}
2023-07-02 10:33:47,362 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:47,364 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0190297
2023-07-02 10:33:47,364 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5106285317162795, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:47,364 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:47,384 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.43489
2023-07-02 10:33:47,384 [model] Computed derived parameters: {}
2023-07-02 10:33:47,384 [model] Posterior to be computed for parameters {'Omega_m': 0.31839181004470785, 'b1': 0.5251480918402662}
2023-07-02 10:33:47,385 [prior] Evaluating prior at array([0.31839181, 0.52514809])
2023-07-02 10:33:47,385 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:47,385 [model] Got input parameters: {'Omega_m': 0.31839181004470785, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5251480918402662, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:47,385 [classy] Got parameters {'Omega_m': 0.31839181004470785, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:47,385 [classy] Re-using computed results
2023-07-02 10:33:47,385 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.5551759235056}
2023-07-02 10:33:47,385 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:47,385 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5251480918402662, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:47,385 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:47,405 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.196455
2023-07-02 10:33:47,405 [model] Computed derived parameters: {}
2023-07-02 10:33:47,405 [mcmc] New sample, #203:
Omega_m:0.3183918, b1:0.5187849
2023-07-02 10:33:47,405 [model] Posterior to be computed for parameters {'Omega_m': 0.3199697709779786, 'b1': 0.5240757704174027}
2023-07-02 10:33:47,405 [prior] Evaluating prior at array([0.31996977, 0.52407577])
2023-07-02 10:33:47,405 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:47,405 [model] Got input parameters: {'Omega_m': 0.3199697709779786, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5240757704174027, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:47,405 [classy] Got parameters {'Omega_m': 0.3199697709779786, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:47,405 [classy] Computing new state
2023-07-02 10:33:47,405 [classy] Setting parameters: {'Omega_m': 0.3199697709779786, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:47,454 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.36886004629972}
2023-07-02 10:33:47,454 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:47,456 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00357535
2023-07-02 10:33:47,456 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5240757704174027, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:47,456 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:47,476 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.200604
2023-07-02 10:33:47,476 [model] Computed derived parameters: {}
2023-07-02 10:33:47,476 [mcmc] New sample, #204:
Omega_m:0.3183918, b1:0.5251481
2023-07-02 10:33:47,477 [model] Posterior to be computed for parameters {'Omega_m': 0.3199697709779786, 'b1': 0.5099238262714798}
2023-07-02 10:33:47,477 [prior] Evaluating prior at array([0.31996977, 0.50992383])
2023-07-02 10:33:47,477 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:47,477 [model] Got input parameters: {'Omega_m': 0.3199697709779786, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5099238262714798, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:47,477 [classy] Got parameters {'Omega_m': 0.3199697709779786, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:47,477 [classy] Re-using computed results
2023-07-02 10:33:47,477 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.36886004629972}
2023-07-02 10:33:47,477 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:47,477 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5099238262714798, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:47,477 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:47,496 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.84667
2023-07-02 10:33:47,496 [model] Computed derived parameters: {}
2023-07-02 10:33:47,496 [mcmc] New sample, #205:
Omega_m:0.3199698, b1:0.5240758
2023-07-02 10:33:47,496 [model] Posterior to be computed for parameters {'Omega_m': 0.32083490541726734, 'b1': 0.5093359142558234}
2023-07-02 10:33:47,496 [prior] Evaluating prior at array([0.32083491, 0.50933591])
2023-07-02 10:33:47,496 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:47,496 [model] Got input parameters: {'Omega_m': 0.32083490541726734, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5093359142558234, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:47,497 [classy] Got parameters {'Omega_m': 0.32083490541726734, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:47,497 [classy] Computing new state
2023-07-02 10:33:47,497 [classy] Setting parameters: {'Omega_m': 0.32083490541726734, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:47,541 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.26705808246697}
2023-07-02 10:33:47,541 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:47,543 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00439115
2023-07-02 10:33:47,543 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5093359142558234, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:47,543 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:47,563 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.69235
2023-07-02 10:33:47,563 [model] Computed derived parameters: {}
2023-07-02 10:33:47,563 [mcmc] New sample, #206:
Omega_m:0.3199698, b1:0.5099238
2023-07-02 10:33:47,563 [model] Posterior to be computed for parameters {'Omega_m': 0.32083490541726734, 'b1': 0.5278993397793454}
2023-07-02 10:33:47,563 [prior] Evaluating prior at array([0.32083491, 0.52789934])
2023-07-02 10:33:47,564 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:47,564 [model] Got input parameters: {'Omega_m': 0.32083490541726734, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5278993397793454, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:47,564 [classy] Got parameters {'Omega_m': 0.32083490541726734, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:47,564 [classy] Re-using computed results
2023-07-02 10:33:47,564 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.26705808246697}
2023-07-02 10:33:47,564 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:47,564 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5278993397793454, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:47,564 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:47,583 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.34489
2023-07-02 10:33:47,583 [model] Computed derived parameters: {}
2023-07-02 10:33:47,583 [model] Posterior to be computed for parameters {'Omega_m': 0.3132794584049812, 'b1': 0.5144703047972871}
2023-07-02 10:33:47,584 [prior] Evaluating prior at array([0.31327946, 0.5144703 ])
2023-07-02 10:33:47,584 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:47,584 [model] Got input parameters: {'Omega_m': 0.3132794584049812, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5144703047972871, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:47,584 [classy] Got parameters {'Omega_m': 0.3132794584049812, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:47,584 [classy] Computing new state
2023-07-02 10:33:47,584 [classy] Setting parameters: {'Omega_m': 0.3132794584049812, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:47,628 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.16451229452576}
2023-07-02 10:33:47,628 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:47,630 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000241119
2023-07-02 10:33:47,630 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5144703047972871, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:47,630 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:47,650 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.57683
2023-07-02 10:33:47,650 [model] Computed derived parameters: {}
2023-07-02 10:33:47,650 [mcmc] New sample, #207:
Omega_m:0.3208349, b1:0.5093359
2023-07-02 10:33:47,650 [model] Posterior to be computed for parameters {'Omega_m': 0.3132794584049812, 'b1': 0.5013918815809042}
2023-07-02 10:33:47,650 [prior] Evaluating prior at array([0.31327946, 0.50139188])
2023-07-02 10:33:47,650 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:47,650 [model] Got input parameters: {'Omega_m': 0.3132794584049812, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5013918815809042, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:47,650 [classy] Got parameters {'Omega_m': 0.3132794584049812, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:47,650 [classy] Re-using computed results
2023-07-02 10:33:47,650 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.16451229452576}
2023-07-02 10:33:47,650 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:47,650 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5013918815809042, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:47,650 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:47,670 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.89439
2023-07-02 10:33:47,670 [model] Computed derived parameters: {}
2023-07-02 10:33:47,670 [mcmc] New sample, #208:
Omega_m:0.3132795, b1:0.5144703
2023-07-02 10:33:47,670 [model] Posterior to be computed for parameters {'Omega_m': 0.30605036779004235, 'b1': 0.5063044928951479}
2023-07-02 10:33:47,670 [prior] Evaluating prior at array([0.30605037, 0.50630449])
2023-07-02 10:33:47,670 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:47,670 [model] Got input parameters: {'Omega_m': 0.30605036779004235, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5063044928951479, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:47,670 [classy] Got parameters {'Omega_m': 0.30605036779004235, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:47,670 [classy] Computing new state
2023-07-02 10:33:47,670 [classy] Setting parameters: {'Omega_m': 0.30605036779004235, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:47,715 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.04141972644808}
2023-07-02 10:33:47,715 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:47,716 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00278188
2023-07-02 10:33:47,716 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5063044928951479, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:47,717 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:47,736 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.15808
2023-07-02 10:33:47,736 [model] Computed derived parameters: {}
2023-07-02 10:33:47,736 [model] Posterior to be computed for parameters {'Omega_m': 0.3132794584049812, 'b1': 0.4985827829275823}
2023-07-02 10:33:47,736 [prior] Evaluating prior at array([0.31327946, 0.49858278])
2023-07-02 10:33:47,736 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:47,736 [model] Got input parameters: {'Omega_m': 0.3132794584049812, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4985827829275823, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:47,736 [classy] Got parameters {'Omega_m': 0.3132794584049812, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:47,737 [classy] Re-using computed results
2023-07-02 10:33:47,737 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.16451229452576}
2023-07-02 10:33:47,737 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:47,737 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4985827829275823, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:47,737 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:47,756 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.84198
2023-07-02 10:33:47,756 [model] Computed derived parameters: {}
2023-07-02 10:33:47,756 [mcmc] New sample, #209:
Omega_m:0.3132795, b1:0.5013919
2023-07-02 10:33:47,756 [model] Posterior to be computed for parameters {'Omega_m': 0.3079158712041842, 'b1': 0.5022276700331774}
2023-07-02 10:33:47,756 [prior] Evaluating prior at array([0.30791587, 0.50222767])
2023-07-02 10:33:47,756 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:47,756 [model] Got input parameters: {'Omega_m': 0.3079158712041842, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5022276700331774, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:47,756 [classy] Got parameters {'Omega_m': 0.3079158712041842, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:47,756 [classy] Computing new state
2023-07-02 10:33:47,756 [classy] Setting parameters: {'Omega_m': 0.3079158712041842, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:47,801 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.81339363227545}
2023-07-02 10:33:47,801 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:47,803 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00149677
2023-07-02 10:33:47,803 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5022276700331774, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:47,803 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:47,823 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.30029
2023-07-02 10:33:47,823 [model] Computed derived parameters: {}
2023-07-02 10:33:47,823 [mcmc] New sample, #210:
Omega_m:0.3132795, b1:0.4985828
2023-07-02 10:33:47,823 [model] Posterior to be computed for parameters {'Omega_m': 0.3079158712041842, 'b1': 0.5037090939988291}
2023-07-02 10:33:47,823 [prior] Evaluating prior at array([0.30791587, 0.50370909])
2023-07-02 10:33:47,823 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:47,823 [model] Got input parameters: {'Omega_m': 0.3079158712041842, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5037090939988291, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:47,823 [classy] Got parameters {'Omega_m': 0.3079158712041842, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:47,823 [classy] Re-using computed results
2023-07-02 10:33:47,823 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.81339363227545}
2023-07-02 10:33:47,824 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:47,824 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5037090939988291, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:47,824 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:47,843 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.38031
2023-07-02 10:33:47,843 [model] Computed derived parameters: {}
2023-07-02 10:33:47,843 [mcmc] New sample, #211:
Omega_m:0.3079159, b1:0.5022277
2023-07-02 10:33:47,843 [model] Posterior to be computed for parameters {'Omega_m': 0.30929080340543824, 'b1': 0.5027747430758734}
2023-07-02 10:33:47,843 [prior] Evaluating prior at array([0.3092908 , 0.50277474])
2023-07-02 10:33:47,843 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:47,843 [model] Got input parameters: {'Omega_m': 0.30929080340543824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5027747430758734, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:47,843 [classy] Got parameters {'Omega_m': 0.30929080340543824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:47,843 [classy] Computing new state
2023-07-02 10:33:47,843 [classy] Setting parameters: {'Omega_m': 0.30929080340543824, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:47,888 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.64611402623362}
2023-07-02 10:33:47,888 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:47,890 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000832691
2023-07-02 10:33:47,890 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5027747430758734, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:47,890 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:47,909 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.55831
2023-07-02 10:33:47,909 [model] Computed derived parameters: {}
2023-07-02 10:33:47,909 [mcmc] New sample, #212:
Omega_m:0.3079159, b1:0.5037091
2023-07-02 10:33:47,909 [model] Posterior to be computed for parameters {'Omega_m': 0.30929080340543824, 'b1': 0.5183259710157854}
2023-07-02 10:33:47,909 [prior] Evaluating prior at array([0.3092908 , 0.51832597])
2023-07-02 10:33:47,910 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:47,910 [model] Got input parameters: {'Omega_m': 0.30929080340543824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5183259710157854, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:47,910 [classy] Got parameters {'Omega_m': 0.30929080340543824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:47,910 [classy] Re-using computed results
2023-07-02 10:33:47,910 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.64611402623362}
2023-07-02 10:33:47,910 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:47,910 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5183259710157854, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:47,910 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:47,930 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.56956
2023-07-02 10:33:47,930 [model] Computed derived parameters: {}
2023-07-02 10:33:47,930 [mcmc] New sample, #213:
Omega_m:0.3092908, b1:0.5027747
2023-07-02 10:33:47,930 [model] Posterior to be computed for parameters {'Omega_m': 0.32684718515277833, 'b1': 0.506395330745357}
2023-07-02 10:33:47,930 [prior] Evaluating prior at array([0.32684719, 0.50639533])
2023-07-02 10:33:47,930 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:47,930 [model] Got input parameters: {'Omega_m': 0.32684718515277833, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.506395330745357, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:47,930 [classy] Got parameters {'Omega_m': 0.32684718515277833, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:47,930 [classy] Computing new state
2023-07-02 10:33:47,930 [classy] Setting parameters: {'Omega_m': 0.32684718515277833, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:47,974 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.56628048370587}
2023-07-02 10:33:47,974 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:47,976 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0124145
2023-07-02 10:33:47,976 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.506395330745357, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:47,976 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:47,995 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.075312
2023-07-02 10:33:47,995 [model] Computed derived parameters: {}
2023-07-02 10:33:47,996 [model] Posterior to be computed for parameters {'Omega_m': 0.30929080340543824, 'b1': 0.5375783600707323}
2023-07-02 10:33:47,996 [prior] Evaluating prior at array([0.3092908 , 0.53757836])
2023-07-02 10:33:47,996 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:47,996 [model] Got input parameters: {'Omega_m': 0.30929080340543824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5375783600707323, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:47,996 [classy] Got parameters {'Omega_m': 0.30929080340543824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:47,996 [classy] Re-using computed results
2023-07-02 10:33:47,996 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.64611402623362}
2023-07-02 10:33:47,996 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:47,996 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5375783600707323, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:47,996 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:48,015 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.738898
2023-07-02 10:33:48,015 [model] Computed derived parameters: {}
2023-07-02 10:33:48,015 [model] Posterior to be computed for parameters {'Omega_m': 0.260666717629516, 'b1': 0.5513690253432451}
2023-07-02 10:33:48,015 [prior] Evaluating prior at array([0.26066672, 0.55136903])
2023-07-02 10:33:48,016 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:48,016 [model] Got input parameters: {'Omega_m': 0.260666717629516, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5513690253432451, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:48,016 [classy] Got parameters {'Omega_m': 0.260666717629516, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:48,016 [classy] Computing new state
2023-07-02 10:33:48,016 [classy] Setting parameters: {'Omega_m': 0.260666717629516, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:48,059 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.99819759562462}
2023-07-02 10:33:48,059 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:48,061 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.188808
2023-07-02 10:33:48,061 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5513690253432451, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:48,061 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:48,081 [fs_likelihood.fslikelihood] Computed log-likelihood = -23.3825
2023-07-02 10:33:48,081 [model] Computed derived parameters: {}
2023-07-02 10:33:48,082 [model] Posterior to be computed for parameters {'Omega_m': 0.30929080340543824, 'b1': 0.5049129415629607}
2023-07-02 10:33:48,082 [prior] Evaluating prior at array([0.3092908 , 0.50491294])
2023-07-02 10:33:48,082 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:48,082 [model] Got input parameters: {'Omega_m': 0.30929080340543824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5049129415629607, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:48,082 [classy] Got parameters {'Omega_m': 0.30929080340543824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:48,082 [classy] Re-using computed results
2023-07-02 10:33:48,082 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.64611402623362}
2023-07-02 10:33:48,082 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:48,082 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5049129415629607, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:48,082 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:48,101 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.63628
2023-07-02 10:33:48,101 [model] Computed derived parameters: {}
2023-07-02 10:33:48,101 [mcmc] New sample, #214:
Omega_m:0.3092908, b1:0.518326
2023-07-02 10:33:48,101 [model] Posterior to be computed for parameters {'Omega_m': 0.32773616619630447, 'b1': 0.49237818404387734}
2023-07-02 10:33:48,102 [prior] Evaluating prior at array([0.32773617, 0.49237818])
2023-07-02 10:33:48,102 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:48,102 [model] Got input parameters: {'Omega_m': 0.32773616619630447, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49237818404387734, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:48,102 [classy] Got parameters {'Omega_m': 0.32773616619630447, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:48,102 [classy] Computing new state
2023-07-02 10:33:48,102 [classy] Setting parameters: {'Omega_m': 0.32773616619630447, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:48,148 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.46364286228786}
2023-07-02 10:33:48,148 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:48,150 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0139436
2023-07-02 10:33:48,150 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49237818404387734, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:48,150 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:48,170 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.45386
2023-07-02 10:33:48,170 [model] Computed derived parameters: {}
2023-07-02 10:33:48,171 [model] Posterior to be computed for parameters {'Omega_m': 0.30929080340543824, 'b1': 0.5276538864123546}
2023-07-02 10:33:48,171 [prior] Evaluating prior at array([0.3092908 , 0.52765389])
2023-07-02 10:33:48,171 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:48,171 [model] Got input parameters: {'Omega_m': 0.30929080340543824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5276538864123546, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:48,171 [classy] Got parameters {'Omega_m': 0.30929080340543824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:48,171 [classy] Re-using computed results
2023-07-02 10:33:48,171 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.64611402623362}
2023-07-02 10:33:48,171 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:48,171 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5276538864123546, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:48,171 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:48,190 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.94371
2023-07-02 10:33:48,190 [model] Computed derived parameters: {}
2023-07-02 10:33:48,190 [mcmc] New sample, #215:
Omega_m:0.3092908, b1:0.5049129
2023-07-02 10:33:48,191 [model] Posterior to be computed for parameters {'Omega_m': 0.2837102899127549, 'b1': 0.5450374173019288}
2023-07-02 10:33:48,191 [prior] Evaluating prior at array([0.28371029, 0.54503742])
2023-07-02 10:33:48,191 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:48,191 [model] Got input parameters: {'Omega_m': 0.2837102899127549, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5450374173019288, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:48,191 [classy] Got parameters {'Omega_m': 0.2837102899127549, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:48,191 [classy] Computing new state
2023-07-02 10:33:48,191 [classy] Setting parameters: {'Omega_m': 0.2837102899127549, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:48,236 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.8710573594621}
2023-07-02 10:33:48,236 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:48,238 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0548514
2023-07-02 10:33:48,238 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5450374173019288, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:48,238 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:48,257 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.8058
2023-07-02 10:33:48,257 [model] Computed derived parameters: {}
2023-07-02 10:33:48,257 [model] Posterior to be computed for parameters {'Omega_m': 0.30929080340543824, 'b1': 0.549124949207475}
2023-07-02 10:33:48,257 [prior] Evaluating prior at array([0.3092908 , 0.54912495])
2023-07-02 10:33:48,257 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:48,257 [model] Got input parameters: {'Omega_m': 0.30929080340543824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.549124949207475, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:48,257 [classy] Got parameters {'Omega_m': 0.30929080340543824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:48,257 [classy] Re-using computed results
2023-07-02 10:33:48,257 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.64611402623362}
2023-07-02 10:33:48,257 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:48,257 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.549124949207475, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:48,257 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:48,277 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.38324
2023-07-02 10:33:48,277 [model] Computed derived parameters: {}
2023-07-02 10:33:48,277 [model] Posterior to be computed for parameters {'Omega_m': 0.28046606256753515, 'b1': 0.5472420691469576}
2023-07-02 10:33:48,277 [prior] Evaluating prior at array([0.28046606, 0.54724207])
2023-07-02 10:33:48,277 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:48,277 [model] Got input parameters: {'Omega_m': 0.28046606256753515, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5472420691469576, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:48,278 [classy] Got parameters {'Omega_m': 0.28046606256753515, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:48,278 [classy] Computing new state
2023-07-02 10:33:48,278 [classy] Setting parameters: {'Omega_m': 0.28046606256753515, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:48,322 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.29793596217513}
2023-07-02 10:33:48,322 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:48,324 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0684531
2023-07-02 10:33:48,324 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5472420691469576, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:48,324 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:48,343 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.54491
2023-07-02 10:33:48,343 [model] Computed derived parameters: {}
2023-07-02 10:33:48,343 [model] Posterior to be computed for parameters {'Omega_m': 0.30929080340543824, 'b1': 0.520638579663175}
2023-07-02 10:33:48,344 [prior] Evaluating prior at array([0.3092908 , 0.52063858])
2023-07-02 10:33:48,344 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:48,344 [model] Got input parameters: {'Omega_m': 0.30929080340543824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.520638579663175, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:48,344 [classy] Got parameters {'Omega_m': 0.30929080340543824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:48,344 [classy] Re-using computed results
2023-07-02 10:33:48,344 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.64611402623362}
2023-07-02 10:33:48,344 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:48,344 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.520638579663175, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:48,344 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:48,363 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.45941
2023-07-02 10:33:48,363 [model] Computed derived parameters: {}
2023-07-02 10:33:48,363 [mcmc] New sample, #216:
Omega_m:0.3092908, b1:0.5276539
2023-07-02 10:33:48,363 [model] Posterior to be computed for parameters {'Omega_m': 0.2995279194396347, 'b1': 0.5272730592657606}
2023-07-02 10:33:48,363 [prior] Evaluating prior at array([0.29952792, 0.52727306])
2023-07-02 10:33:48,363 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:48,363 [model] Got input parameters: {'Omega_m': 0.2995279194396347, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5272730592657606, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:48,363 [classy] Got parameters {'Omega_m': 0.2995279194396347, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:48,363 [classy] Computing new state
2023-07-02 10:33:48,364 [classy] Setting parameters: {'Omega_m': 0.2995279194396347, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:48,408 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.8483878984982}
2023-07-02 10:33:48,408 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:48,409 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0108368
2023-07-02 10:33:48,409 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5272730592657606, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:48,409 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:48,430 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.44969
2023-07-02 10:33:48,430 [model] Computed derived parameters: {}
2023-07-02 10:33:48,430 [mcmc] New sample, #217:
Omega_m:0.3092908, b1:0.5206386
2023-07-02 10:33:48,430 [model] Posterior to be computed for parameters {'Omega_m': 0.2995279194396347, 'b1': 0.520632928917912}
2023-07-02 10:33:48,430 [prior] Evaluating prior at array([0.29952792, 0.52063293])
2023-07-02 10:33:48,430 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:48,430 [model] Got input parameters: {'Omega_m': 0.2995279194396347, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.520632928917912, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:48,430 [classy] Got parameters {'Omega_m': 0.2995279194396347, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:48,431 [classy] Re-using computed results
2023-07-02 10:33:48,431 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.8483878984982}
2023-07-02 10:33:48,431 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:48,431 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.520632928917912, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:48,431 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:48,450 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.29271
2023-07-02 10:33:48,450 [model] Computed derived parameters: {}
2023-07-02 10:33:48,450 [mcmc] New sample, #218:
Omega_m:0.2995279, b1:0.5272731
2023-07-02 10:33:48,450 [model] Posterior to be computed for parameters {'Omega_m': 0.2885895918898879, 'b1': 0.528066194669035}
2023-07-02 10:33:48,450 [prior] Evaluating prior at array([0.28858959, 0.52806619])
2023-07-02 10:33:48,450 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:48,450 [model] Got input parameters: {'Omega_m': 0.2885895918898879, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.528066194669035, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:48,450 [classy] Got parameters {'Omega_m': 0.2885895918898879, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:48,450 [classy] Computing new state
2023-07-02 10:33:48,450 [classy] Setting parameters: {'Omega_m': 0.2885895918898879, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:48,495 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.23690185949303}
2023-07-02 10:33:48,495 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:48,496 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0374095
2023-07-02 10:33:48,496 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.528066194669035, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:48,496 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:48,516 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.5706
2023-07-02 10:33:48,516 [model] Computed derived parameters: {}
2023-07-02 10:33:48,516 [model] Posterior to be computed for parameters {'Omega_m': 0.2995279194396347, 'b1': 0.48429283709579285}
2023-07-02 10:33:48,516 [prior] Evaluating prior at array([0.29952792, 0.48429284])
2023-07-02 10:33:48,516 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:48,516 [model] Got input parameters: {'Omega_m': 0.2995279194396347, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48429283709579285, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:48,516 [classy] Got parameters {'Omega_m': 0.2995279194396347, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:48,516 [classy] Re-using computed results
2023-07-02 10:33:48,516 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.8483878984982}
2023-07-02 10:33:48,516 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:48,516 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48429283709579285, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:48,516 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:48,536 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.49582
2023-07-02 10:33:48,536 [model] Computed derived parameters: {}
2023-07-02 10:33:48,536 [model] Posterior to be computed for parameters {'Omega_m': 0.3183332228542055, 'b1': 0.5078535696259842}
2023-07-02 10:33:48,536 [prior] Evaluating prior at array([0.31833322, 0.50785357])
2023-07-02 10:33:48,536 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:48,536 [model] Got input parameters: {'Omega_m': 0.3183332228542055, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5078535696259842, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:48,536 [classy] Got parameters {'Omega_m': 0.3183332228542055, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:48,536 [classy] Computing new state
2023-07-02 10:33:48,536 [classy] Setting parameters: {'Omega_m': 0.3183332228542055, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:48,581 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.56210662844933}
2023-07-02 10:33:48,581 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:48,583 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00227009
2023-07-02 10:33:48,583 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5078535696259842, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:48,583 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:48,602 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.36819
2023-07-02 10:33:48,602 [model] Computed derived parameters: {}
2023-07-02 10:33:48,602 [mcmc] New sample, #219:
Omega_m:0.2995279, b1:0.5206329
2023-07-02 10:33:48,602 [model] Posterior to be computed for parameters {'Omega_m': 0.3183332228542055, 'b1': 0.5462994189438529}
2023-07-02 10:33:48,602 [prior] Evaluating prior at array([0.31833322, 0.54629942])
2023-07-02 10:33:48,602 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:48,602 [model] Got input parameters: {'Omega_m': 0.3183332228542055, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5462994189438529, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:48,603 [classy] Got parameters {'Omega_m': 0.3183332228542055, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:48,603 [classy] Re-using computed results
2023-07-02 10:33:48,603 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.56210662844933}
2023-07-02 10:33:48,603 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:48,603 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5462994189438529, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:48,603 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:48,622 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.83087
2023-07-02 10:33:48,622 [model] Computed derived parameters: {}
2023-07-02 10:33:48,622 [model] Posterior to be computed for parameters {'Omega_m': 0.29900780881540995, 'b1': 0.5209863760488616}
2023-07-02 10:33:48,622 [prior] Evaluating prior at array([0.29900781, 0.52098638])
2023-07-02 10:33:48,623 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:48,623 [model] Got input parameters: {'Omega_m': 0.29900780881540995, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5209863760488616, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:48,623 [classy] Got parameters {'Omega_m': 0.29900780881540995, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:48,623 [classy] Computing new state
2023-07-02 10:33:48,623 [classy] Setting parameters: {'Omega_m': 0.29900780881540995, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:48,667 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.91340568421296}
2023-07-02 10:33:48,667 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:48,669 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0117232
2023-07-02 10:33:48,669 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5209863760488616, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:48,669 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:48,689 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.16481
2023-07-02 10:33:48,689 [model] Computed derived parameters: {}
2023-07-02 10:33:48,689 [model] Posterior to be computed for parameters {'Omega_m': 0.3183332228542055, 'b1': 0.5031986233872454}
2023-07-02 10:33:48,689 [prior] Evaluating prior at array([0.31833322, 0.50319862])
2023-07-02 10:33:48,689 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:48,689 [model] Got input parameters: {'Omega_m': 0.3183332228542055, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5031986233872454, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:48,689 [classy] Got parameters {'Omega_m': 0.3183332228542055, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:48,689 [classy] Re-using computed results
2023-07-02 10:33:48,689 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.56210662844933}
2023-07-02 10:33:48,689 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:48,689 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5031986233872454, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:48,689 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:48,709 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.65579
2023-07-02 10:33:48,709 [model] Computed derived parameters: {}
2023-07-02 10:33:48,709 [mcmc] New sample, #220:
Omega_m:0.3183332, b1:0.5078536
2023-07-02 10:33:48,709 [model] Posterior to be computed for parameters {'Omega_m': 0.3197925788746206, 'b1': 0.5022069012911652}
2023-07-02 10:33:48,709 [prior] Evaluating prior at array([0.31979258, 0.5022069 ])
2023-07-02 10:33:48,709 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:48,709 [model] Got input parameters: {'Omega_m': 0.3197925788746206, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5022069012911652, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:48,709 [classy] Got parameters {'Omega_m': 0.3197925788746206, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:48,709 [classy] Computing new state
2023-07-02 10:33:48,709 [classy] Setting parameters: {'Omega_m': 0.3197925788746206, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:48,753 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.3897420806043}
2023-07-02 10:33:48,753 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:48,755 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00341893
2023-07-02 10:33:48,755 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5022069012911652, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:48,755 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:48,774 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.50495
2023-07-02 10:33:48,774 [model] Computed derived parameters: {}
2023-07-02 10:33:48,774 [model] Posterior to be computed for parameters {'Omega_m': 0.3183332228542055, 'b1': 0.5358416770493034}
2023-07-02 10:33:48,774 [prior] Evaluating prior at array([0.31833322, 0.53584168])
2023-07-02 10:33:48,774 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:48,774 [model] Got input parameters: {'Omega_m': 0.3183332228542055, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5358416770493034, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:48,774 [classy] Got parameters {'Omega_m': 0.3183332228542055, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:48,774 [classy] Re-using computed results
2023-07-02 10:33:48,774 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.56210662844933}
2023-07-02 10:33:48,774 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:48,774 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5358416770493034, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:48,774 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:48,794 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.99356
2023-07-02 10:33:48,794 [model] Computed derived parameters: {}
2023-07-02 10:33:48,794 [model] Posterior to be computed for parameters {'Omega_m': 0.3158407582257441, 'b1': 0.5048924062689856}
2023-07-02 10:33:48,794 [prior] Evaluating prior at array([0.31584076, 0.50489241])
2023-07-02 10:33:48,794 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:48,794 [model] Got input parameters: {'Omega_m': 0.3158407582257441, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5048924062689856, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:48,794 [classy] Got parameters {'Omega_m': 0.3158407582257441, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:48,794 [classy] Computing new state
2023-07-02 10:33:48,794 [classy] Setting parameters: {'Omega_m': 0.3158407582257441, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:48,838 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.85812140684394}
2023-07-02 10:33:48,839 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:48,840 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000887703
2023-07-02 10:33:48,840 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5048924062689856, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:48,840 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:48,860 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.82433
2023-07-02 10:33:48,860 [model] Computed derived parameters: {}
2023-07-02 10:33:48,860 [mcmc] New sample, #221:
Omega_m:0.3183332, b1:0.5031986
2023-07-02 10:33:48,860 [model] Posterior to be computed for parameters {'Omega_m': 0.3158407582257441, 'b1': 0.5083164458527899}
2023-07-02 10:33:48,860 [prior] Evaluating prior at array([0.31584076, 0.50831645])
2023-07-02 10:33:48,860 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:48,860 [model] Got input parameters: {'Omega_m': 0.3158407582257441, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083164458527899, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:48,860 [classy] Got parameters {'Omega_m': 0.3158407582257441, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:48,860 [classy] Re-using computed results
2023-07-02 10:33:48,860 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.85812140684394}
2023-07-02 10:33:48,860 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:48,860 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083164458527899, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:48,860 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:48,880 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.67881
2023-07-02 10:33:48,880 [model] Computed derived parameters: {}
2023-07-02 10:33:48,880 [mcmc] New sample, #222:
Omega_m:0.3158408, b1:0.5048924
2023-07-02 10:33:48,880 [model] Posterior to be computed for parameters {'Omega_m': 0.3162428082794476, 'b1': 0.5080432281345565}
2023-07-02 10:33:48,880 [prior] Evaluating prior at array([0.31624281, 0.50804323])
2023-07-02 10:33:48,880 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:48,880 [model] Got input parameters: {'Omega_m': 0.3162428082794476, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5080432281345565, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:48,880 [classy] Got parameters {'Omega_m': 0.3162428082794476, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:48,880 [classy] Computing new state
2023-07-02 10:33:48,880 [classy] Setting parameters: {'Omega_m': 0.3162428082794476, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:48,924 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.81023501004276}
2023-07-02 10:33:48,924 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:48,926 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00106076
2023-07-02 10:33:48,926 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5080432281345565, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:48,926 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:48,945 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.65057
2023-07-02 10:33:48,945 [model] Computed derived parameters: {}
2023-07-02 10:33:48,945 [mcmc] New sample, #223:
Omega_m:0.3158408, b1:0.5083164
2023-07-02 10:33:48,946 [model] Posterior to be computed for parameters {'Omega_m': 0.3162428082794476, 'b1': 0.5216074106776183}
2023-07-02 10:33:48,946 [prior] Evaluating prior at array([0.31624281, 0.52160741])
2023-07-02 10:33:48,946 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:48,946 [model] Got input parameters: {'Omega_m': 0.3162428082794476, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5216074106776183, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:48,946 [classy] Got parameters {'Omega_m': 0.3162428082794476, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:48,946 [classy] Re-using computed results
2023-07-02 10:33:48,946 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.81023501004276}
2023-07-02 10:33:48,946 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:48,946 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5216074106776183, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:48,946 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:48,965 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.39239
2023-07-02 10:33:48,965 [model] Computed derived parameters: {}
2023-07-02 10:33:48,965 [mcmc] New sample, #224:
Omega_m:0.3162428, b1:0.5080432
2023-07-02 10:33:48,965 [model] Posterior to be computed for parameters {'Omega_m': 0.3052770838808455, 'b1': 0.5290592942711271}
2023-07-02 10:33:48,965 [prior] Evaluating prior at array([0.30527708, 0.52905929])
2023-07-02 10:33:48,966 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:48,966 [model] Got input parameters: {'Omega_m': 0.3052770838808455, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5290592942711271, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:48,966 [classy] Got parameters {'Omega_m': 0.3052770838808455, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:48,966 [classy] Computing new state
2023-07-02 10:33:48,966 [classy] Setting parameters: {'Omega_m': 0.3052770838808455, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:49,009 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.13629762813025}
2023-07-02 10:33:49,010 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:49,011 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0034455
2023-07-02 10:33:49,011 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5290592942711271, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,011 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:49,031 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.0206
2023-07-02 10:33:49,032 [model] Computed derived parameters: {}
2023-07-02 10:33:49,032 [mcmc] New sample, #225:
Omega_m:0.3162428, b1:0.5216074
2023-07-02 10:33:49,032 [model] Posterior to be computed for parameters {'Omega_m': 0.3052770838808455, 'b1': 0.5182963940106264}
2023-07-02 10:33:49,032 [prior] Evaluating prior at array([0.30527708, 0.51829639])
2023-07-02 10:33:49,032 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:49,032 [model] Got input parameters: {'Omega_m': 0.3052770838808455, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5182963940106264, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,032 [classy] Got parameters {'Omega_m': 0.3052770838808455, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:49,032 [classy] Re-using computed results
2023-07-02 10:33:49,032 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.13629762813025}
2023-07-02 10:33:49,032 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:49,032 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5182963940106264, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,032 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:49,052 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.35027
2023-07-02 10:33:49,052 [model] Computed derived parameters: {}
2023-07-02 10:33:49,052 [mcmc] New sample, #226:
Omega_m:0.3052771, b1:0.5290593
2023-07-02 10:33:49,052 [model] Posterior to be computed for parameters {'Omega_m': 0.3159723928377348, 'b1': 0.5110282743273056}
2023-07-02 10:33:49,052 [prior] Evaluating prior at array([0.31597239, 0.51102827])
2023-07-02 10:33:49,052 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:49,052 [model] Got input parameters: {'Omega_m': 0.3159723928377348, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5110282743273056, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,052 [classy] Got parameters {'Omega_m': 0.3159723928377348, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:49,052 [classy] Computing new state
2023-07-02 10:33:49,052 [classy] Setting parameters: {'Omega_m': 0.3159723928377348, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:49,096 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.8424401880562}
2023-07-02 10:33:49,096 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:49,098 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000942208
2023-07-02 10:33:49,098 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5110282743273056, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,098 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:49,117 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.5001
2023-07-02 10:33:49,117 [model] Computed derived parameters: {}
2023-07-02 10:33:49,117 [mcmc] New sample, #227:
Omega_m:0.3052771, b1:0.5182964
2023-07-02 10:33:49,117 [model] Posterior to be computed for parameters {'Omega_m': 0.3159723928377348, 'b1': 0.5174522627693926}
2023-07-02 10:33:49,117 [prior] Evaluating prior at array([0.31597239, 0.51745226])
2023-07-02 10:33:49,118 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:49,118 [model] Got input parameters: {'Omega_m': 0.3159723928377348, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5174522627693926, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,118 [classy] Got parameters {'Omega_m': 0.3159723928377348, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:49,118 [classy] Re-using computed results
2023-07-02 10:33:49,118 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.8424401880562}
2023-07-02 10:33:49,118 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:49,118 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5174522627693926, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,118 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:49,140 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.94416
2023-07-02 10:33:49,140 [model] Computed derived parameters: {}
2023-07-02 10:33:49,140 [mcmc] New sample, #228:
Omega_m:0.3159724, b1:0.5110283
2023-07-02 10:33:49,140 [model] Posterior to be computed for parameters {'Omega_m': 0.31827635938422794, 'b1': 0.5158865759179162}
2023-07-02 10:33:49,140 [prior] Evaluating prior at array([0.31827636, 0.51588658])
2023-07-02 10:33:49,140 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:49,141 [model] Got input parameters: {'Omega_m': 0.31827635938422794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5158865759179162, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,141 [classy] Got parameters {'Omega_m': 0.31827635938422794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:49,141 [classy] Computing new state
2023-07-02 10:33:49,141 [classy] Setting parameters: {'Omega_m': 0.31827635938422794, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:49,184 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.568837706383}
2023-07-02 10:33:49,185 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:49,186 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00223036
2023-07-02 10:33:49,186 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5158865759179162, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,186 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:49,206 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.59833
2023-07-02 10:33:49,206 [model] Computed derived parameters: {}
2023-07-02 10:33:49,206 [mcmc] New sample, #229:
Omega_m:0.3159724, b1:0.5174523
2023-07-02 10:33:49,206 [model] Posterior to be computed for parameters {'Omega_m': 0.31827635938422794, 'b1': 0.5094458228165901}
2023-07-02 10:33:49,206 [prior] Evaluating prior at array([0.31827636, 0.50944582])
2023-07-02 10:33:49,206 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:49,206 [model] Got input parameters: {'Omega_m': 0.31827635938422794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5094458228165901, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,206 [classy] Got parameters {'Omega_m': 0.31827635938422794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:49,206 [classy] Re-using computed results
2023-07-02 10:33:49,206 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.568837706383}
2023-07-02 10:33:49,206 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:49,206 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5094458228165901, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,207 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:49,226 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.25249
2023-07-02 10:33:49,226 [model] Computed derived parameters: {}
2023-07-02 10:33:49,226 [mcmc] New sample, #230:
Omega_m:0.3182764, b1:0.5158866
2023-07-02 10:33:49,226 [model] Posterior to be computed for parameters {'Omega_m': 0.3277631378551154, 'b1': 0.5029989738650087}
2023-07-02 10:33:49,226 [prior] Evaluating prior at array([0.32776314, 0.50299897])
2023-07-02 10:33:49,227 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:49,227 [model] Got input parameters: {'Omega_m': 0.3277631378551154, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5029989738650087, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,227 [classy] Got parameters {'Omega_m': 0.3277631378551154, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:49,227 [classy] Computing new state
2023-07-02 10:33:49,227 [classy] Setting parameters: {'Omega_m': 0.3277631378551154, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:49,270 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.4605346942738}
2023-07-02 10:33:49,270 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:49,272 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0139913
2023-07-02 10:33:49,272 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5029989738650087, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,272 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:49,292 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.221182
2023-07-02 10:33:49,292 [model] Computed derived parameters: {}
2023-07-02 10:33:49,292 [model] Posterior to be computed for parameters {'Omega_m': 0.31827635938422794, 'b1': 0.5662847766367575}
2023-07-02 10:33:49,292 [prior] Evaluating prior at array([0.31827636, 0.56628478])
2023-07-02 10:33:49,292 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:49,292 [model] Got input parameters: {'Omega_m': 0.31827635938422794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5662847766367575, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,292 [classy] Got parameters {'Omega_m': 0.31827635938422794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:49,292 [classy] Re-using computed results
2023-07-02 10:33:49,292 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.568837706383}
2023-07-02 10:33:49,292 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:49,292 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5662847766367575, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,292 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:49,311 [fs_likelihood.fslikelihood] Computed log-likelihood = -12.1358
2023-07-02 10:33:49,312 [model] Computed derived parameters: {}
2023-07-02 10:33:49,312 [model] Posterior to be computed for parameters {'Omega_m': 0.2900484016656151, 'b1': 0.5286284547481757}
2023-07-02 10:33:49,312 [prior] Evaluating prior at array([0.2900484 , 0.52862845])
2023-07-02 10:33:49,312 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:49,312 [model] Got input parameters: {'Omega_m': 0.2900484016656151, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5286284547481757, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,312 [classy] Got parameters {'Omega_m': 0.2900484016656151, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:49,312 [classy] Computing new state
2023-07-02 10:33:49,312 [classy] Setting parameters: {'Omega_m': 0.2900484016656151, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:49,356 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.04911288589634}
2023-07-02 10:33:49,356 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:49,357 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.032881
2023-07-02 10:33:49,357 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5286284547481757, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,358 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:49,377 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.76947
2023-07-02 10:33:49,377 [model] Computed derived parameters: {}
2023-07-02 10:33:49,377 [model] Posterior to be computed for parameters {'Omega_m': 0.31827635938422794, 'b1': 0.5092265797852127}
2023-07-02 10:33:49,377 [prior] Evaluating prior at array([0.31827636, 0.50922658])
2023-07-02 10:33:49,377 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:49,377 [model] Got input parameters: {'Omega_m': 0.31827635938422794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5092265797852127, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,377 [classy] Got parameters {'Omega_m': 0.31827635938422794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:49,377 [classy] Re-using computed results
2023-07-02 10:33:49,377 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.568837706383}
2023-07-02 10:33:49,377 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:49,377 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5092265797852127, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,377 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:49,397 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.2706
2023-07-02 10:33:49,397 [model] Computed derived parameters: {}
2023-07-02 10:33:49,397 [mcmc] New sample, #231:
Omega_m:0.3182764, b1:0.5094458
2023-07-02 10:33:49,397 [model] Posterior to be computed for parameters {'Omega_m': 0.3282200456929302, 'b1': 0.5024692338799789}
2023-07-02 10:33:49,397 [prior] Evaluating prior at array([0.32822005, 0.50246923])
2023-07-02 10:33:49,398 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:49,398 [model] Got input parameters: {'Omega_m': 0.3282200456929302, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5024692338799789, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,398 [classy] Got parameters {'Omega_m': 0.3282200456929302, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:49,398 [classy] Computing new state
2023-07-02 10:33:49,398 [classy] Setting parameters: {'Omega_m': 0.3282200456929302, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:49,442 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.40788419294526}
2023-07-02 10:33:49,442 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:49,443 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0148123
2023-07-02 10:33:49,443 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5024692338799789, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,443 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:49,463 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.116006
2023-07-02 10:33:49,463 [model] Computed derived parameters: {}
2023-07-02 10:33:49,463 [model] Posterior to be computed for parameters {'Omega_m': 0.31827635938422794, 'b1': 0.5068114980934646}
2023-07-02 10:33:49,463 [prior] Evaluating prior at array([0.31827636, 0.5068115 ])
2023-07-02 10:33:49,463 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:49,463 [model] Got input parameters: {'Omega_m': 0.31827635938422794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5068114980934646, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,463 [classy] Got parameters {'Omega_m': 0.31827635938422794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:49,463 [classy] Re-using computed results
2023-07-02 10:33:49,463 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.568837706383}
2023-07-02 10:33:49,463 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:49,463 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5068114980934646, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,463 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:49,482 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.45217
2023-07-02 10:33:49,482 [model] Computed derived parameters: {}
2023-07-02 10:33:49,483 [mcmc] New sample, #232:
Omega_m:0.3182764, b1:0.5092266
2023-07-02 10:33:49,483 [model] Posterior to be computed for parameters {'Omega_m': 0.3109455218059237, 'b1': 0.5117932527218599}
2023-07-02 10:33:49,483 [prior] Evaluating prior at array([0.31094552, 0.51179325])
2023-07-02 10:33:49,483 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:49,483 [model] Got input parameters: {'Omega_m': 0.3109455218059237, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5117932527218599, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,483 [classy] Got parameters {'Omega_m': 0.3109455218059237, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:49,483 [classy] Computing new state
2023-07-02 10:33:49,483 [classy] Setting parameters: {'Omega_m': 0.3109455218059237, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:49,527 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.4456581783046}
2023-07-02 10:33:49,527 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:49,528 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000348079
2023-07-02 10:33:49,528 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5117932527218599, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,529 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:49,548 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.77858
2023-07-02 10:33:49,548 [model] Computed derived parameters: {}
2023-07-02 10:33:49,548 [mcmc] New sample, #233:
Omega_m:0.3182764, b1:0.5068115
2023-07-02 10:33:49,549 [model] Posterior to be computed for parameters {'Omega_m': 0.3109455218059237, 'b1': 0.5061447730998416}
2023-07-02 10:33:49,549 [prior] Evaluating prior at array([0.31094552, 0.50614477])
2023-07-02 10:33:49,549 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:49,549 [model] Got input parameters: {'Omega_m': 0.3109455218059237, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5061447730998416, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,549 [classy] Got parameters {'Omega_m': 0.3109455218059237, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:49,549 [classy] Re-using computed results
2023-07-02 10:33:49,549 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.4456581783046}
2023-07-02 10:33:49,549 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:49,549 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5061447730998416, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,549 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:49,568 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.81696
2023-07-02 10:33:49,568 [model] Computed derived parameters: {}
2023-07-02 10:33:49,568 [mcmc] New sample, #234:
Omega_m:0.3109455, b1:0.5117933
2023-07-02 10:33:49,569 [model] Posterior to be computed for parameters {'Omega_m': 0.2927909853804227, 'b1': 0.5184818962318251}
2023-07-02 10:33:49,569 [prior] Evaluating prior at array([0.29279099, 0.5184819 ])
2023-07-02 10:33:49,569 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:49,569 [model] Got input parameters: {'Omega_m': 0.2927909853804227, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5184818962318251, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,569 [classy] Got parameters {'Omega_m': 0.2927909853804227, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:49,569 [classy] Computing new state
2023-07-02 10:33:49,569 [classy] Setting parameters: {'Omega_m': 0.2927909853804227, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:49,613 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.6982631267611}
2023-07-02 10:33:49,613 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:49,614 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0252018
2023-07-02 10:33:49,615 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5184818962318251, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,615 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:49,634 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.44026
2023-07-02 10:33:49,634 [model] Computed derived parameters: {}
2023-07-02 10:33:49,635 [model] Posterior to be computed for parameters {'Omega_m': 0.3109455218059237, 'b1': 0.5052567977639995}
2023-07-02 10:33:49,635 [prior] Evaluating prior at array([0.31094552, 0.5052568 ])
2023-07-02 10:33:49,635 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:49,635 [model] Got input parameters: {'Omega_m': 0.3109455218059237, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5052567977639995, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,635 [classy] Got parameters {'Omega_m': 0.3109455218059237, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:49,635 [classy] Re-using computed results
2023-07-02 10:33:49,635 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.4456581783046}
2023-07-02 10:33:49,635 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:49,635 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5052567977639995, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,635 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:49,655 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.80741
2023-07-02 10:33:49,655 [model] Computed derived parameters: {}
2023-07-02 10:33:49,655 [mcmc] New sample, #235:
Omega_m:0.3109455, b1:0.5061448
2023-07-02 10:33:49,655 [model] Posterior to be computed for parameters {'Omega_m': 0.321569154386066, 'b1': 0.4980373865833282}
2023-07-02 10:33:49,655 [prior] Evaluating prior at array([0.32156915, 0.49803739])
2023-07-02 10:33:49,655 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:49,655 [model] Got input parameters: {'Omega_m': 0.321569154386066, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4980373865833282, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,655 [classy] Got parameters {'Omega_m': 0.321569154386066, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:49,655 [classy] Computing new state
2023-07-02 10:33:49,655 [classy] Setting parameters: {'Omega_m': 0.321569154386066, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:49,699 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.1808502939914}
2023-07-02 10:33:49,699 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:49,701 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00515123
2023-07-02 10:33:49,701 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4980373865833282, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,701 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:49,720 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.45117
2023-07-02 10:33:49,720 [model] Computed derived parameters: {}
2023-07-02 10:33:49,721 [mcmc] New sample, #236:
Omega_m:0.3109455, b1:0.5052568
2023-07-02 10:33:49,721 [model] Posterior to be computed for parameters {'Omega_m': 0.321569154386066, 'b1': 0.4982091241827604}
2023-07-02 10:33:49,721 [prior] Evaluating prior at array([0.32156915, 0.49820912])
2023-07-02 10:33:49,721 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:49,721 [model] Got input parameters: {'Omega_m': 0.321569154386066, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4982091241827604, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,721 [classy] Got parameters {'Omega_m': 0.321569154386066, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:49,721 [classy] Re-using computed results
2023-07-02 10:33:49,721 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.1808502939914}
2023-07-02 10:33:49,721 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:49,721 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4982091241827604, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,721 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:49,740 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.442
2023-07-02 10:33:49,740 [model] Computed derived parameters: {}
2023-07-02 10:33:49,740 [mcmc] New sample, #237:
Omega_m:0.3215692, b1:0.4980374
2023-07-02 10:33:49,741 [model] Posterior to be computed for parameters {'Omega_m': 0.312265859294416, 'b1': 0.5045312849027467}
2023-07-02 10:33:49,741 [prior] Evaluating prior at array([0.31226586, 0.50453128])
2023-07-02 10:33:49,741 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:49,741 [model] Got input parameters: {'Omega_m': 0.312265859294416, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5045312849027467, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,741 [classy] Got parameters {'Omega_m': 0.312265859294416, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:49,741 [classy] Computing new state
2023-07-02 10:33:49,741 [classy] Setting parameters: {'Omega_m': 0.312265859294416, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:49,784 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.2863815060963}
2023-07-02 10:33:49,784 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:49,786 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000205289
2023-07-02 10:33:49,786 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5045312849027467, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,786 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:49,806 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.87637
2023-07-02 10:33:49,806 [model] Computed derived parameters: {}
2023-07-02 10:33:49,806 [mcmc] New sample, #238:
Omega_m:0.3215692, b1:0.4982091
2023-07-02 10:33:49,806 [model] Posterior to be computed for parameters {'Omega_m': 0.312265859294416, 'b1': 0.43937782890161314}
2023-07-02 10:33:49,806 [prior] Evaluating prior at array([0.31226586, 0.43937783])
2023-07-02 10:33:49,806 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:49,807 [model] Got input parameters: {'Omega_m': 0.312265859294416, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.43937782890161314, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,807 [classy] Got parameters {'Omega_m': 0.312265859294416, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:49,807 [classy] Re-using computed results
2023-07-02 10:33:49,807 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.2863815060963}
2023-07-02 10:33:49,807 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:49,807 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.43937782890161314, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,807 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:49,827 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.05725
2023-07-02 10:33:49,827 [model] Computed derived parameters: {}
2023-07-02 10:33:49,827 [model] Posterior to be computed for parameters {'Omega_m': 0.33161555747267324, 'b1': 0.49138197591479843}
2023-07-02 10:33:49,827 [prior] Evaluating prior at array([0.33161556, 0.49138198])
2023-07-02 10:33:49,827 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:49,827 [model] Got input parameters: {'Omega_m': 0.33161555747267324, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49138197591479843, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,827 [classy] Got parameters {'Omega_m': 0.33161555747267324, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:49,827 [classy] Computing new state
2023-07-02 10:33:49,827 [classy] Setting parameters: {'Omega_m': 0.33161555747267324, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:49,871 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.01868928366534}
2023-07-02 10:33:49,871 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:49,872 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0216216
2023-07-02 10:33:49,873 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49138197591479843, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,873 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:49,892 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.261042
2023-07-02 10:33:49,892 [model] Computed derived parameters: {}
2023-07-02 10:33:49,892 [model] Posterior to be computed for parameters {'Omega_m': 0.312265859294416, 'b1': 0.5708744575215448}
2023-07-02 10:33:49,892 [prior] Evaluating prior at array([0.31226586, 0.57087446])
2023-07-02 10:33:49,893 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:49,893 [model] Got input parameters: {'Omega_m': 0.312265859294416, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5708744575215448, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,893 [classy] Got parameters {'Omega_m': 0.312265859294416, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:49,893 [classy] Re-using computed results
2023-07-02 10:33:49,893 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.2863815060963}
2023-07-02 10:33:49,893 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:49,893 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5708744575215448, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,893 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:49,912 [fs_likelihood.fslikelihood] Computed log-likelihood = -9.45656
2023-07-02 10:33:49,913 [model] Computed derived parameters: {}
2023-07-02 10:33:49,913 [model] Posterior to be computed for parameters {'Omega_m': 0.30800791597884786, 'b1': 0.5074248190444052}
2023-07-02 10:33:49,913 [prior] Evaluating prior at array([0.30800792, 0.50742482])
2023-07-02 10:33:49,913 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:49,913 [model] Got input parameters: {'Omega_m': 0.30800791597884786, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5074248190444052, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,913 [classy] Got parameters {'Omega_m': 0.30800791597884786, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:49,913 [classy] Computing new state
2023-07-02 10:33:49,913 [classy] Setting parameters: {'Omega_m': 0.30800791597884786, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:49,957 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.80217753036325}
2023-07-02 10:33:49,957 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:49,958 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00144487
2023-07-02 10:33:49,959 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5074248190444052, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,959 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:49,978 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.54355
2023-07-02 10:33:49,978 [model] Computed derived parameters: {}
2023-07-02 10:33:49,978 [model] Posterior to be computed for parameters {'Omega_m': 0.312265859294416, 'b1': 0.5372879803879943}
2023-07-02 10:33:49,978 [prior] Evaluating prior at array([0.31226586, 0.53728798])
2023-07-02 10:33:49,978 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:49,978 [model] Got input parameters: {'Omega_m': 0.312265859294416, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5372879803879943, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,978 [classy] Got parameters {'Omega_m': 0.312265859294416, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:49,978 [classy] Re-using computed results
2023-07-02 10:33:49,978 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.2863815060963}
2023-07-02 10:33:49,978 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:49,978 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5372879803879943, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,979 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:49,998 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.0397168
2023-07-02 10:33:49,998 [model] Computed derived parameters: {}
2023-07-02 10:33:49,998 [mcmc] New sample, #239:
Omega_m:0.3122659, b1:0.5045313
2023-07-02 10:33:49,998 [model] Posterior to be computed for parameters {'Omega_m': 0.3388729996660182, 'b1': 0.5192067934460168}
2023-07-02 10:33:49,998 [prior] Evaluating prior at array([0.338873 , 0.51920679])
2023-07-02 10:33:49,998 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:49,998 [model] Got input parameters: {'Omega_m': 0.3388729996660182, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5192067934460168, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:49,998 [classy] Got parameters {'Omega_m': 0.3388729996660182, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:49,998 [classy] Computing new state
2023-07-02 10:33:49,998 [classy] Setting parameters: {'Omega_m': 0.3388729996660182, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:50,042 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.198790172366}
2023-07-02 10:33:50,043 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:50,044 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0402547
2023-07-02 10:33:50,044 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5192067934460168, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:50,044 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:50,064 [fs_likelihood.fslikelihood] Computed log-likelihood = -11.2207
2023-07-02 10:33:50,064 [model] Computed derived parameters: {}
2023-07-02 10:33:50,064 [model] Posterior to be computed for parameters {'Omega_m': 0.312265859294416, 'b1': 0.518637203147961}
2023-07-02 10:33:50,064 [prior] Evaluating prior at array([0.31226586, 0.5186372 ])
2023-07-02 10:33:50,064 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:50,064 [model] Got input parameters: {'Omega_m': 0.312265859294416, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.518637203147961, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:50,064 [classy] Got parameters {'Omega_m': 0.312265859294416, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:50,064 [classy] Re-using computed results
2023-07-02 10:33:50,064 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.2863815060963}
2023-07-02 10:33:50,064 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:50,064 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.518637203147961, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:50,064 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:50,084 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.3942
2023-07-02 10:33:50,084 [model] Computed derived parameters: {}
2023-07-02 10:33:50,084 [mcmc] New sample, #240:
Omega_m:0.3122659, b1:0.537288
2023-07-02 10:33:50,084 [mcmc] Learn + convergence test @ 240 samples accepted.
2023-07-02 10:33:50,084 [mcmc] Ready to check convergence and learn a new proposal covmat
2023-07-02 10:33:50,089 [mcmc] - Acceptance rate: 0.298
2023-07-02 10:33:50,089 [mcmc] - Condition number = 5.34158
2023-07-02 10:33:50,089 [mcmc] - Eigenvalues = array([0.11773969, 0.62891615])
2023-07-02 10:33:50,089 [mcmc] - Convergence of means: R-1 = 0.628916 after 192 accepted steps
2023-07-02 10:33:50,090 [mcmc] - Updated covariance matrix of proposal pdf.
2023-07-02 10:33:50,090 [mcmc] array([[ 3.58509594e-05, -1.86866609e-05],
[-1.86866609e-05, 6.58047122e-05]])
2023-07-02 10:33:50,100 [mcmc] Dumped checkpoint and progress info, and current covmat.
2023-07-02 10:33:50,100 [model] Posterior to be computed for parameters {'Omega_m': 0.31990844627854803, 'b1': 0.5146536436049877}
2023-07-02 10:33:50,100 [prior] Evaluating prior at array([0.31990845, 0.51465364])
2023-07-02 10:33:50,100 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:50,100 [model] Got input parameters: {'Omega_m': 0.31990844627854803, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5146536436049877, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:50,100 [classy] Got parameters {'Omega_m': 0.31990844627854803, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:50,100 [classy] Computing new state
2023-07-02 10:33:50,100 [classy] Setting parameters: {'Omega_m': 0.31990844627854803, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:50,147 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.37608405371185}
2023-07-02 10:33:50,147 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:50,149 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00352083
2023-07-02 10:33:50,149 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5146536436049877, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:50,149 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:50,169 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.31016
2023-07-02 10:33:50,170 [model] Computed derived parameters: {}
2023-07-02 10:33:50,170 [model] Posterior to be computed for parameters {'Omega_m': 0.312265859294416, 'b1': 0.5278459261278375}
2023-07-02 10:33:50,170 [prior] Evaluating prior at array([0.31226586, 0.52784593])
2023-07-02 10:33:50,170 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:50,170 [model] Got input parameters: {'Omega_m': 0.312265859294416, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5278459261278375, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:50,170 [classy] Got parameters {'Omega_m': 0.312265859294416, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:50,170 [classy] Re-using computed results
2023-07-02 10:33:50,170 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.2863815060963}
2023-07-02 10:33:50,170 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:50,170 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5278459261278375, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:50,170 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:50,190 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.48164
2023-07-02 10:33:50,190 [model] Computed derived parameters: {}
2023-07-02 10:33:50,190 [model] Posterior to be computed for parameters {'Omega_m': 0.2846997088089088, 'b1': 0.5330055580070654}
2023-07-02 10:33:50,190 [prior] Evaluating prior at array([0.28469971, 0.53300556])
2023-07-02 10:33:50,190 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:50,190 [model] Got input parameters: {'Omega_m': 0.2846997088089088, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5330055580070654, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:50,190 [classy] Got parameters {'Omega_m': 0.2846997088089088, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:50,190 [classy] Computing new state
2023-07-02 10:33:50,190 [classy] Setting parameters: {'Omega_m': 0.2846997088089088, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:50,235 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.74170121702863}
2023-07-02 10:33:50,235 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:50,237 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0510247
2023-07-02 10:33:50,237 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5330055580070654, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:50,237 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:50,257 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.28239
2023-07-02 10:33:50,257 [model] Computed derived parameters: {}
2023-07-02 10:33:50,257 [model] Posterior to be computed for parameters {'Omega_m': 0.312265859294416, 'b1': 0.5692318241211897}
2023-07-02 10:33:50,257 [prior] Evaluating prior at array([0.31226586, 0.56923182])
2023-07-02 10:33:50,257 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:50,257 [model] Got input parameters: {'Omega_m': 0.312265859294416, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5692318241211897, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:50,257 [classy] Got parameters {'Omega_m': 0.312265859294416, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:50,257 [classy] Re-using computed results
2023-07-02 10:33:50,257 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.2863815060963}
2023-07-02 10:33:50,257 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:50,257 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5692318241211897, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:50,257 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:50,276 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.82733
2023-07-02 10:33:50,277 [model] Computed derived parameters: {}
2023-07-02 10:33:50,277 [model] Posterior to be computed for parameters {'Omega_m': 0.3104467493294811, 'b1': 0.5195853811504594}
2023-07-02 10:33:50,277 [prior] Evaluating prior at array([0.31044675, 0.51958538])
2023-07-02 10:33:50,277 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:50,277 [model] Got input parameters: {'Omega_m': 0.3104467493294811, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195853811504594, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:50,277 [classy] Got parameters {'Omega_m': 0.3104467493294811, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:50,277 [classy] Computing new state
2023-07-02 10:33:50,277 [classy] Setting parameters: {'Omega_m': 0.3104467493294811, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:50,322 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.50598010757898}
2023-07-02 10:33:50,322 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:50,324 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000458192
2023-07-02 10:33:50,324 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195853811504594, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:50,324 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:50,343 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.47107
2023-07-02 10:33:50,343 [model] Computed derived parameters: {}
2023-07-02 10:33:50,343 [mcmc] New sample, #241:
Omega_m:0.3122659, b1:0.5186372
2023-07-02 10:33:50,343 [model] Posterior to be computed for parameters {'Omega_m': 0.3104467493294811, 'b1': 0.49637575802326056}
2023-07-02 10:33:50,344 [prior] Evaluating prior at array([0.31044675, 0.49637576])
2023-07-02 10:33:50,344 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:50,344 [model] Got input parameters: {'Omega_m': 0.3104467493294811, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49637575802326056, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:50,344 [classy] Got parameters {'Omega_m': 0.3104467493294811, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:50,344 [classy] Re-using computed results
2023-07-02 10:33:50,344 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.50598010757898}
2023-07-02 10:33:50,344 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:50,344 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49637575802326056, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:50,344 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:50,364 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.40034
2023-07-02 10:33:50,364 [model] Computed derived parameters: {}
2023-07-02 10:33:50,364 [mcmc] New sample, #242:
Omega_m:0.3104467, b1:0.5195854
2023-07-02 10:33:50,364 [model] Posterior to be computed for parameters {'Omega_m': 0.2925248739989793, 'b1': 0.5057172097658483}
2023-07-02 10:33:50,364 [prior] Evaluating prior at array([0.29252487, 0.50571721])
2023-07-02 10:33:50,364 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:50,364 [model] Got input parameters: {'Omega_m': 0.2925248739989793, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5057172097658483, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:50,364 [classy] Got parameters {'Omega_m': 0.2925248739989793, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:50,364 [classy] Computing new state
2023-07-02 10:33:50,364 [classy] Setting parameters: {'Omega_m': 0.2925248739989793, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:50,409 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.7321800975787}
2023-07-02 10:33:50,409 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:50,410 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0258996
2023-07-02 10:33:50,410 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5057172097658483, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:50,411 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:50,431 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.44041
2023-07-02 10:33:50,431 [model] Computed derived parameters: {}
2023-07-02 10:33:50,431 [model] Posterior to be computed for parameters {'Omega_m': 0.3104467493294811, 'b1': 0.4987342841705211}
2023-07-02 10:33:50,431 [prior] Evaluating prior at array([0.31044675, 0.49873428])
2023-07-02 10:33:50,431 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:50,431 [model] Got input parameters: {'Omega_m': 0.3104467493294811, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4987342841705211, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:50,431 [classy] Got parameters {'Omega_m': 0.3104467493294811, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:50,431 [classy] Re-using computed results
2023-07-02 10:33:50,431 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.50598010757898}
2023-07-02 10:33:50,431 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:50,431 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4987342841705211, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:50,431 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:50,451 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.53806
2023-07-02 10:33:50,451 [model] Computed derived parameters: {}
2023-07-02 10:33:50,451 [mcmc] New sample, #243:
Omega_m:0.3104467, b1:0.4963758
2023-07-02 10:33:50,451 [model] Posterior to be computed for parameters {'Omega_m': 0.2850362418228118, 'b1': 0.5119790493109317}
2023-07-02 10:33:50,451 [prior] Evaluating prior at array([0.28503624, 0.51197905])
2023-07-02 10:33:50,451 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:50,451 [model] Got input parameters: {'Omega_m': 0.2850362418228118, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5119790493109317, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:50,451 [classy] Got parameters {'Omega_m': 0.2850362418228118, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:50,451 [classy] Computing new state
2023-07-02 10:33:50,451 [classy] Setting parameters: {'Omega_m': 0.2850362418228118, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:50,495 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.69779080134344}
2023-07-02 10:33:50,495 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:50,496 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.049757
2023-07-02 10:33:50,497 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5119790493109317, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:50,497 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:50,516 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.43901
2023-07-02 10:33:50,516 [model] Computed derived parameters: {}
2023-07-02 10:33:50,517 [model] Posterior to be computed for parameters {'Omega_m': 0.3104467493294811, 'b1': 0.49630269103171}
2023-07-02 10:33:50,517 [prior] Evaluating prior at array([0.31044675, 0.49630269])
2023-07-02 10:33:50,517 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:50,517 [model] Got input parameters: {'Omega_m': 0.3104467493294811, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49630269103171, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:50,517 [classy] Got parameters {'Omega_m': 0.3104467493294811, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:50,517 [classy] Re-using computed results
2023-07-02 10:33:50,517 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.50598010757898}
2023-07-02 10:33:50,517 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:50,517 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49630269103171, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:50,517 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:50,536 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.39561
2023-07-02 10:33:50,536 [model] Computed derived parameters: {}
2023-07-02 10:33:50,537 [model] Posterior to be computed for parameters {'Omega_m': 0.3296439143958108, 'b1': 0.4887281108346089}
2023-07-02 10:33:50,537 [prior] Evaluating prior at array([0.32964391, 0.48872811])
2023-07-02 10:33:50,537 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:50,537 [model] Got input parameters: {'Omega_m': 0.3296439143958108, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4887281108346089, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:50,537 [classy] Got parameters {'Omega_m': 0.3296439143958108, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:50,537 [classy] Computing new state
2023-07-02 10:33:50,537 [classy] Setting parameters: {'Omega_m': 0.3296439143958108, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:50,581 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.2442271859258}
2023-07-02 10:33:50,581 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:50,583 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0175167
2023-07-02 10:33:50,583 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4887281108346089, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:50,583 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:50,602 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.20364
2023-07-02 10:33:50,602 [model] Computed derived parameters: {}
2023-07-02 10:33:50,602 [mcmc] New sample, #244:
Omega_m:0.3104467, b1:0.4987343
2023-07-02 10:33:50,603 [model] Posterior to be computed for parameters {'Omega_m': 0.3296439143958108, 'b1': 0.49681951733074364}
2023-07-02 10:33:50,603 [prior] Evaluating prior at array([0.32964391, 0.49681952])
2023-07-02 10:33:50,603 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:50,603 [model] Got input parameters: {'Omega_m': 0.3296439143958108, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49681951733074364, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:50,603 [classy] Got parameters {'Omega_m': 0.3296439143958108, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:50,603 [classy] Re-using computed results
2023-07-02 10:33:50,603 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.2442271859258}
2023-07-02 10:33:50,603 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:50,603 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49681951733074364, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:50,603 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:50,622 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.339908
2023-07-02 10:33:50,622 [model] Computed derived parameters: {}
2023-07-02 10:33:50,623 [mcmc] New sample, #245:
Omega_m:0.3296439, b1:0.4887281
2023-07-02 10:33:50,623 [model] Posterior to be computed for parameters {'Omega_m': 0.3350393187082103, 'b1': 0.49400726090743}
2023-07-02 10:33:50,623 [prior] Evaluating prior at array([0.33503932, 0.49400726])
2023-07-02 10:33:50,623 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:50,623 [model] Got input parameters: {'Omega_m': 0.3350393187082103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49400726090743, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:50,623 [classy] Got parameters {'Omega_m': 0.3350393187082103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:50,623 [classy] Computing new state
2023-07-02 10:33:50,623 [classy] Setting parameters: {'Omega_m': 0.3350393187082103, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:50,667 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.62989722291502}
2023-07-02 10:33:50,668 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:50,669 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0297304
2023-07-02 10:33:50,669 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49400726090743, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:50,670 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:50,689 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.64975
2023-07-02 10:33:50,689 [model] Computed derived parameters: {}
2023-07-02 10:33:50,689 [mcmc] New sample, #246:
Omega_m:0.3296439, b1:0.4968195
2023-07-02 10:33:50,689 [model] Posterior to be computed for parameters {'Omega_m': 0.3350393187082103, 'b1': 0.4673758432115313}
2023-07-02 10:33:50,689 [prior] Evaluating prior at array([0.33503932, 0.46737584])
2023-07-02 10:33:50,689 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:50,689 [model] Got input parameters: {'Omega_m': 0.3350393187082103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4673758432115313, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:50,689 [classy] Got parameters {'Omega_m': 0.3350393187082103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:50,689 [classy] Re-using computed results
2023-07-02 10:33:50,689 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.62989722291502}
2023-07-02 10:33:50,689 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:50,689 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4673758432115313, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:50,690 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:50,709 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.85974
2023-07-02 10:33:50,709 [model] Computed derived parameters: {}
2023-07-02 10:33:50,709 [mcmc] New sample, #247:
Omega_m:0.3350393, b1:0.4940073
2023-07-02 10:33:50,709 [model] Posterior to be computed for parameters {'Omega_m': 0.34527463262703534, 'b1': 0.46204087188293297}
2023-07-02 10:33:50,709 [prior] Evaluating prior at array([0.34527463, 0.46204087])
2023-07-02 10:33:50,710 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:50,710 [model] Got input parameters: {'Omega_m': 0.34527463262703534, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46204087188293297, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:50,710 [classy] Got parameters {'Omega_m': 0.34527463262703534, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:50,710 [classy] Computing new state
2023-07-02 10:33:50,710 [classy] Setting parameters: {'Omega_m': 0.34527463262703534, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:50,753 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.488679549445}
2023-07-02 10:33:50,753 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:50,755 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0611211
2023-07-02 10:33:50,755 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46204087188293297, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:50,755 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:50,775 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.31346
2023-07-02 10:33:50,775 [model] Computed derived parameters: {}
2023-07-02 10:33:50,775 [model] Posterior to be computed for parameters {'Omega_m': 0.3350393187082103, 'b1': 0.4531453533363623}
2023-07-02 10:33:50,775 [prior] Evaluating prior at array([0.33503932, 0.45314535])
2023-07-02 10:33:50,775 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:50,775 [model] Got input parameters: {'Omega_m': 0.3350393187082103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4531453533363623, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:50,775 [classy] Got parameters {'Omega_m': 0.3350393187082103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:50,775 [classy] Re-using computed results
2023-07-02 10:33:50,776 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.62989722291502}
2023-07-02 10:33:50,776 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:50,776 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4531453533363623, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:50,776 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:50,795 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.568389
2023-07-02 10:33:50,795 [model] Computed derived parameters: {}
2023-07-02 10:33:50,795 [mcmc] New sample, #248:
Omega_m:0.3350393, b1:0.4673758
2023-07-02 10:33:50,795 [model] Posterior to be computed for parameters {'Omega_m': 0.3148651931816438, 'b1': 0.46366074955355335}
2023-07-02 10:33:50,795 [prior] Evaluating prior at array([0.31486519, 0.46366075])
2023-07-02 10:33:50,795 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:50,795 [model] Got input parameters: {'Omega_m': 0.3148651931816438, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46366074955355335, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:50,795 [classy] Got parameters {'Omega_m': 0.3148651931816438, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:50,795 [classy] Computing new state
2023-07-02 10:33:50,795 [classy] Setting parameters: {'Omega_m': 0.3148651931816438, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:50,840 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.9745537903658}
2023-07-02 10:33:50,840 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:50,841 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000548134
2023-07-02 10:33:50,841 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46366074955355335, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:50,841 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:50,861 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.616224
2023-07-02 10:33:50,861 [model] Computed derived parameters: {}
2023-07-02 10:33:50,861 [model] Posterior to be computed for parameters {'Omega_m': 0.3350393187082103, 'b1': 0.47282944921484393}
2023-07-02 10:33:50,861 [prior] Evaluating prior at array([0.33503932, 0.47282945])
2023-07-02 10:33:50,862 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:50,862 [model] Got input parameters: {'Omega_m': 0.3350393187082103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47282944921484393, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:50,862 [classy] Got parameters {'Omega_m': 0.3350393187082103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:50,862 [classy] Re-using computed results
2023-07-02 10:33:50,862 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.62989722291502}
2023-07-02 10:33:50,862 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:50,862 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47282944921484393, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:50,862 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:50,881 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.676453
2023-07-02 10:33:50,882 [model] Computed derived parameters: {}
2023-07-02 10:33:50,882 [mcmc] New sample, #249:
Omega_m:0.3350393, b1:0.4531454
2023-07-02 10:33:50,882 [model] Posterior to be computed for parameters {'Omega_m': 0.3605098197317599, 'b1': 0.45955341354428675}
2023-07-02 10:33:50,882 [prior] Evaluating prior at array([0.36050982, 0.45955341])
2023-07-02 10:33:50,882 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:50,882 [model] Got input parameters: {'Omega_m': 0.3605098197317599, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45955341354428675, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:50,882 [classy] Got parameters {'Omega_m': 0.3605098197317599, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:50,882 [classy] Computing new state
2023-07-02 10:33:50,882 [classy] Setting parameters: {'Omega_m': 0.3605098197317599, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:50,926 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.8461063868818}
2023-07-02 10:33:50,926 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:50,928 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.126362
2023-07-02 10:33:50,928 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45955341354428675, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:50,928 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:50,947 [fs_likelihood.fslikelihood] Computed log-likelihood = -11.5591
2023-07-02 10:33:50,947 [model] Computed derived parameters: {}
2023-07-02 10:33:50,947 [model] Posterior to be computed for parameters {'Omega_m': 0.3350393187082103, 'b1': 0.46441434597773756}
2023-07-02 10:33:50,947 [prior] Evaluating prior at array([0.33503932, 0.46441435])
2023-07-02 10:33:50,947 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:50,947 [model] Got input parameters: {'Omega_m': 0.3350393187082103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46441434597773756, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:50,948 [classy] Got parameters {'Omega_m': 0.3350393187082103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:50,948 [classy] Re-using computed results
2023-07-02 10:33:50,948 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.62989722291502}
2023-07-02 10:33:50,948 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:50,948 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46441434597773756, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:50,948 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:50,967 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.890018
2023-07-02 10:33:50,967 [model] Computed derived parameters: {}
2023-07-02 10:33:50,968 [mcmc] New sample, #250:
Omega_m:0.3350393, b1:0.4728294
2023-07-02 10:33:50,968 [model] Posterior to be computed for parameters {'Omega_m': 0.316968585480722, 'b1': 0.47383338719327717}
2023-07-02 10:33:50,968 [prior] Evaluating prior at array([0.31696859, 0.47383339])
2023-07-02 10:33:50,968 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:50,968 [model] Got input parameters: {'Omega_m': 0.316968585480722, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47383338719327717, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:50,968 [classy] Got parameters {'Omega_m': 0.316968585480722, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:50,968 [classy] Computing new state
2023-07-02 10:33:50,968 [classy] Setting parameters: {'Omega_m': 0.316968585480722, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:51,012 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.72392161231042}
2023-07-02 10:33:51,012 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:51,013 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00142199
2023-07-02 10:33:51,013 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47383338719327717, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:51,013 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:51,033 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.52007
2023-07-02 10:33:51,033 [model] Computed derived parameters: {}
2023-07-02 10:33:51,033 [mcmc] New sample, #251:
Omega_m:0.3350393, b1:0.4644143
2023-07-02 10:33:51,033 [model] Posterior to be computed for parameters {'Omega_m': 0.316968585480722, 'b1': 0.43877750695983925}
2023-07-02 10:33:51,034 [prior] Evaluating prior at array([0.31696859, 0.43877751])
2023-07-02 10:33:51,034 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:51,034 [model] Got input parameters: {'Omega_m': 0.316968585480722, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.43877750695983925, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:51,034 [classy] Got parameters {'Omega_m': 0.316968585480722, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:51,034 [classy] Re-using computed results
2023-07-02 10:33:51,034 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.72392161231042}
2023-07-02 10:33:51,034 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:51,034 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.43877750695983925, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:51,034 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:51,054 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.6577
2023-07-02 10:33:51,054 [model] Computed derived parameters: {}
2023-07-02 10:33:51,054 [model] Posterior to be computed for parameters {'Omega_m': 0.3011351132781472, 'b1': 0.48208629676721154}
2023-07-02 10:33:51,054 [prior] Evaluating prior at array([0.30113511, 0.4820863 ])
2023-07-02 10:33:51,054 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:51,054 [model] Got input parameters: {'Omega_m': 0.3011351132781472, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48208629676721154, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:51,054 [classy] Got parameters {'Omega_m': 0.3011351132781472, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:51,054 [classy] Computing new state
2023-07-02 10:33:51,054 [classy] Setting parameters: {'Omega_m': 0.3011351132781472, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:51,098 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.64811168487412}
2023-07-02 10:33:51,098 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:51,100 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00832866
2023-07-02 10:33:51,100 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48208629676721154, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:51,100 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:51,120 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.05454
2023-07-02 10:33:51,121 [model] Computed derived parameters: {}
2023-07-02 10:33:51,121 [model] Posterior to be computed for parameters {'Omega_m': 0.316968585480722, 'b1': 0.4747005287375945}
2023-07-02 10:33:51,121 [prior] Evaluating prior at array([0.31696859, 0.47470053])
2023-07-02 10:33:51,122 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:51,122 [model] Got input parameters: {'Omega_m': 0.316968585480722, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4747005287375945, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:51,122 [classy] Got parameters {'Omega_m': 0.316968585480722, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:51,122 [classy] Re-using computed results
2023-07-02 10:33:51,122 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.72392161231042}
2023-07-02 10:33:51,122 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:51,122 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4747005287375945, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:51,122 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:51,150 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.62197
2023-07-02 10:33:51,150 [model] Computed derived parameters: {}
2023-07-02 10:33:51,150 [mcmc] New sample, #252:
Omega_m:0.3169686, b1:0.4738334
2023-07-02 10:33:51,150 [model] Posterior to be computed for parameters {'Omega_m': 0.31256139265984656, 'b1': 0.47699769788408547}
2023-07-02 10:33:51,150 [prior] Evaluating prior at array([0.31256139, 0.4769977 ])
2023-07-02 10:33:51,150 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:51,150 [model] Got input parameters: {'Omega_m': 0.31256139265984656, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47699769788408547, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:51,150 [classy] Got parameters {'Omega_m': 0.31256139265984656, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:51,150 [classy] Computing new state
2023-07-02 10:33:51,150 [classy] Setting parameters: {'Omega_m': 0.31256139265984656, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:51,196 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.25081219144346}
2023-07-02 10:33:51,196 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:51,198 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000202741
2023-07-02 10:33:51,198 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47699769788408547, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:51,198 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:51,217 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.869153
2023-07-02 10:33:51,218 [model] Computed derived parameters: {}
2023-07-02 10:33:51,218 [mcmc] New sample, #253:
Omega_m:0.3169686, b1:0.4747005
2023-07-02 10:33:51,218 [model] Posterior to be computed for parameters {'Omega_m': 0.31256139265984656, 'b1': 0.5074853598968554}
2023-07-02 10:33:51,218 [prior] Evaluating prior at array([0.31256139, 0.50748536])
2023-07-02 10:33:51,218 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:51,218 [model] Got input parameters: {'Omega_m': 0.31256139265984656, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5074853598968554, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:51,218 [classy] Got parameters {'Omega_m': 0.31256139265984656, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:51,218 [classy] Re-using computed results
2023-07-02 10:33:51,218 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.25081219144346}
2023-07-02 10:33:51,218 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:51,218 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5074853598968554, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:51,218 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:51,240 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.8676
2023-07-02 10:33:51,240 [model] Computed derived parameters: {}
2023-07-02 10:33:51,240 [mcmc] New sample, #254:
Omega_m:0.3125614, b1:0.4769977
2023-07-02 10:33:51,240 [model] Posterior to be computed for parameters {'Omega_m': 0.31793550913875046, 'b1': 0.5046841993697935}
2023-07-02 10:33:51,240 [prior] Evaluating prior at array([0.31793551, 0.5046842 ])
2023-07-02 10:33:51,240 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:51,240 [model] Got input parameters: {'Omega_m': 0.31793550913875046, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5046841993697935, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:51,240 [classy] Got parameters {'Omega_m': 0.31793550913875046, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:51,240 [classy] Computing new state
2023-07-02 10:33:51,240 [classy] Setting parameters: {'Omega_m': 0.31793550913875046, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:51,285 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.60920122997302}
2023-07-02 10:33:51,285 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:51,287 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00200026
2023-07-02 10:33:51,287 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5046841993697935, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:51,287 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:51,306 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.62991
2023-07-02 10:33:51,306 [model] Computed derived parameters: {}
2023-07-02 10:33:51,307 [mcmc] New sample, #255:
Omega_m:0.3125614, b1:0.5074854
2023-07-02 10:33:51,307 [model] Posterior to be computed for parameters {'Omega_m': 0.31793550913875046, 'b1': 0.5119266389463657}
2023-07-02 10:33:51,307 [prior] Evaluating prior at array([0.31793551, 0.51192664])
2023-07-02 10:33:51,307 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:51,307 [model] Got input parameters: {'Omega_m': 0.31793550913875046, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5119266389463657, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:51,307 [classy] Got parameters {'Omega_m': 0.31793550913875046, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:51,307 [classy] Re-using computed results
2023-07-02 10:33:51,307 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.60920122997302}
2023-07-02 10:33:51,307 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:51,307 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5119266389463657, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:51,307 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:51,327 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.09888
2023-07-02 10:33:51,327 [model] Computed derived parameters: {}
2023-07-02 10:33:51,327 [mcmc] New sample, #256:
Omega_m:0.3179355, b1:0.5046842
2023-07-02 10:33:51,327 [model] Posterior to be computed for parameters {'Omega_m': 0.3151987641590579, 'b1': 0.5133531175200704}
2023-07-02 10:33:51,327 [prior] Evaluating prior at array([0.31519876, 0.51335312])
2023-07-02 10:33:51,327 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:51,328 [model] Got input parameters: {'Omega_m': 0.3151987641590579, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5133531175200704, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:51,328 [classy] Got parameters {'Omega_m': 0.3151987641590579, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:51,328 [classy] Computing new state
2023-07-02 10:33:51,328 [classy] Setting parameters: {'Omega_m': 0.3151987641590579, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:51,371 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.9347050679899}
2023-07-02 10:33:51,371 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:51,373 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000651397
2023-07-02 10:33:51,373 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5133531175200704, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:51,373 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:51,392 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.43851
2023-07-02 10:33:51,392 [model] Computed derived parameters: {}
2023-07-02 10:33:51,392 [mcmc] New sample, #257:
Omega_m:0.3179355, b1:0.5119266
2023-07-02 10:33:51,393 [model] Posterior to be computed for parameters {'Omega_m': 0.3151987641590579, 'b1': 0.5060283679983525}
2023-07-02 10:33:51,393 [prior] Evaluating prior at array([0.31519876, 0.50602837])
2023-07-02 10:33:51,393 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:51,393 [model] Got input parameters: {'Omega_m': 0.3151987641590579, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5060283679983525, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:51,393 [classy] Got parameters {'Omega_m': 0.3151987641590579, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:51,393 [classy] Re-using computed results
2023-07-02 10:33:51,393 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.9347050679899}
2023-07-02 10:33:51,393 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:51,393 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5060283679983525, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:51,393 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:51,412 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.82773
2023-07-02 10:33:51,412 [model] Computed derived parameters: {}
2023-07-02 10:33:51,412 [mcmc] New sample, #258:
Omega_m:0.3151988, b1:0.5133531
2023-07-02 10:33:51,412 [model] Posterior to be computed for parameters {'Omega_m': 0.3034299824285535, 'b1': 0.5121626315493019}
2023-07-02 10:33:51,412 [prior] Evaluating prior at array([0.30342998, 0.51216263])
2023-07-02 10:33:51,412 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:51,413 [model] Got input parameters: {'Omega_m': 0.3034299824285535, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5121626315493019, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:51,413 [classy] Got parameters {'Omega_m': 0.3034299824285535, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:51,413 [classy] Computing new state
2023-07-02 10:33:51,413 [classy] Setting parameters: {'Omega_m': 0.3034299824285535, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:51,456 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.3637826342507}
2023-07-02 10:33:51,456 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:51,458 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00534468
2023-07-02 10:33:51,458 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5121626315493019, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:51,458 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:51,478 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.88614
2023-07-02 10:33:51,478 [model] Computed derived parameters: {}
2023-07-02 10:33:51,479 [mcmc] New sample, #259:
Omega_m:0.3151988, b1:0.5060284
2023-07-02 10:33:51,479 [model] Posterior to be computed for parameters {'Omega_m': 0.3034299824285535, 'b1': 0.5090286399546369}
2023-07-02 10:33:51,479 [prior] Evaluating prior at array([0.30342998, 0.50902864])
2023-07-02 10:33:51,479 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:51,479 [model] Got input parameters: {'Omega_m': 0.3034299824285535, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5090286399546369, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:51,479 [classy] Got parameters {'Omega_m': 0.3034299824285535, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:51,479 [classy] Re-using computed results
2023-07-02 10:33:51,479 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.3637826342507}
2023-07-02 10:33:51,479 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:51,479 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5090286399546369, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:51,479 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:51,499 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.70925
2023-07-02 10:33:51,499 [model] Computed derived parameters: {}
2023-07-02 10:33:51,499 [mcmc] New sample, #260:
Omega_m:0.30343, b1:0.5121626
2023-07-02 10:33:51,499 [model] Posterior to be computed for parameters {'Omega_m': 0.294686603893143, 'b1': 0.5135859670841649}
2023-07-02 10:33:51,499 [prior] Evaluating prior at array([0.2946866 , 0.51358597])
2023-07-02 10:33:51,499 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:51,500 [model] Got input parameters: {'Omega_m': 0.294686603893143, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5135859670841649, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:51,500 [classy] Got parameters {'Omega_m': 0.294686603893143, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:51,500 [classy] Computing new state
2023-07-02 10:33:51,500 [classy] Setting parameters: {'Omega_m': 0.294686603893143, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:51,545 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.4574244897901}
2023-07-02 10:33:51,545 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:51,546 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.020521
2023-07-02 10:33:51,547 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5135859670841649, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:51,547 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:51,566 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.09068
2023-07-02 10:33:51,566 [model] Computed derived parameters: {}
2023-07-02 10:33:51,567 [model] Posterior to be computed for parameters {'Omega_m': 0.3034299824285535, 'b1': 0.49951998768077804}
2023-07-02 10:33:51,567 [prior] Evaluating prior at array([0.30342998, 0.49951999])
2023-07-02 10:33:51,567 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:51,567 [model] Got input parameters: {'Omega_m': 0.3034299824285535, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49951998768077804, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:51,567 [classy] Got parameters {'Omega_m': 0.3034299824285535, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:51,567 [classy] Re-using computed results
2023-07-02 10:33:51,567 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.3637826342507}
2023-07-02 10:33:51,567 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:51,567 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49951998768077804, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:51,567 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:51,587 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.865897
2023-07-02 10:33:51,587 [model] Computed derived parameters: {}
2023-07-02 10:33:51,587 [model] Posterior to be computed for parameters {'Omega_m': 0.30470760507266326, 'b1': 0.5083627023752767}
2023-07-02 10:33:51,587 [prior] Evaluating prior at array([0.30470761, 0.5083627 ])
2023-07-02 10:33:51,587 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:51,587 [model] Got input parameters: {'Omega_m': 0.30470760507266326, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083627023752767, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:51,587 [classy] Got parameters {'Omega_m': 0.30470760507266326, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:51,588 [classy] Computing new state
2023-07-02 10:33:51,588 [classy] Setting parameters: {'Omega_m': 0.30470760507266326, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:51,632 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.20630427078024}
2023-07-02 10:33:51,632 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:51,634 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00398367
2023-07-02 10:33:51,634 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083627023752767, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:51,634 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:51,654 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.97991
2023-07-02 10:33:51,655 [model] Computed derived parameters: {}
2023-07-02 10:33:51,655 [mcmc] New sample, #261:
Omega_m:0.30343, b1:0.5090286
2023-07-02 10:33:51,655 [model] Posterior to be computed for parameters {'Omega_m': 0.30470760507266326, 'b1': 0.5061663527968823}
2023-07-02 10:33:51,655 [prior] Evaluating prior at array([0.30470761, 0.50616635])
2023-07-02 10:33:51,655 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:51,655 [model] Got input parameters: {'Omega_m': 0.30470760507266326, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5061663527968823, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:51,655 [classy] Got parameters {'Omega_m': 0.30470760507266326, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:51,655 [classy] Re-using computed results
2023-07-02 10:33:51,655 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.20630427078024}
2023-07-02 10:33:51,655 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:51,655 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5061663527968823, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:51,655 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:51,676 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.84431
2023-07-02 10:33:51,676 [model] Computed derived parameters: {}
2023-07-02 10:33:51,677 [mcmc] New sample, #262:
Omega_m:0.3047076, b1:0.5083627
2023-07-02 10:33:51,677 [model] Posterior to be computed for parameters {'Omega_m': 0.2991917314083716, 'b1': 0.5090414016800479}
2023-07-02 10:33:51,677 [prior] Evaluating prior at array([0.29919173, 0.5090414 ])
2023-07-02 10:33:51,677 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:51,677 [model] Got input parameters: {'Omega_m': 0.2991917314083716, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5090414016800479, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:51,677 [classy] Got parameters {'Omega_m': 0.2991917314083716, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:51,677 [classy] Computing new state
2023-07-02 10:33:51,677 [classy] Setting parameters: {'Omega_m': 0.2991917314083716, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:51,722 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.89040133711921}
2023-07-02 10:33:51,722 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:51,724 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0114056
2023-07-02 10:33:51,724 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5090414016800479, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:51,724 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:51,744 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.34586
2023-07-02 10:33:51,744 [model] Computed derived parameters: {}
2023-07-02 10:33:51,744 [model] Posterior to be computed for parameters {'Omega_m': 0.30470760507266326, 'b1': 0.5206023742577697}
2023-07-02 10:33:51,744 [prior] Evaluating prior at array([0.30470761, 0.52060237])
2023-07-02 10:33:51,745 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:51,745 [model] Got input parameters: {'Omega_m': 0.30470760507266326, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5206023742577697, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:51,745 [classy] Got parameters {'Omega_m': 0.30470760507266326, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:51,745 [classy] Re-using computed results
2023-07-02 10:33:51,745 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.20630427078024}
2023-07-02 10:33:51,745 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:51,745 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5206023742577697, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:51,745 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:51,764 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.27432
2023-07-02 10:33:51,765 [model] Computed derived parameters: {}
2023-07-02 10:33:51,765 [mcmc] New sample, #263:
Omega_m:0.3047076, b1:0.5061664
2023-07-02 10:33:51,765 [model] Posterior to be computed for parameters {'Omega_m': 0.3294451439792615, 'b1': 0.5077083817673139}
2023-07-02 10:33:51,765 [prior] Evaluating prior at array([0.32944514, 0.50770838])
2023-07-02 10:33:51,765 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:51,765 [model] Got input parameters: {'Omega_m': 0.3294451439792615, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5077083817673139, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:51,765 [classy] Got parameters {'Omega_m': 0.3294451439792615, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:51,765 [classy] Computing new state
2023-07-02 10:33:51,765 [classy] Setting parameters: {'Omega_m': 0.3294451439792615, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:51,810 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.26703386139386}
2023-07-02 10:33:51,810 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:51,811 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.017126
2023-07-02 10:33:51,812 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5077083817673139, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:51,812 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:51,831 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.32922
2023-07-02 10:33:51,832 [model] Computed derived parameters: {}
2023-07-02 10:33:51,832 [model] Posterior to be computed for parameters {'Omega_m': 0.30470760507266326, 'b1': 0.5005226842047796}
2023-07-02 10:33:51,832 [prior] Evaluating prior at array([0.30470761, 0.50052268])
2023-07-02 10:33:51,832 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:51,832 [model] Got input parameters: {'Omega_m': 0.30470760507266326, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5005226842047796, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:51,832 [classy] Got parameters {'Omega_m': 0.30470760507266326, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:51,832 [classy] Re-using computed results
2023-07-02 10:33:51,832 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.20630427078024}
2023-07-02 10:33:51,832 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:51,832 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5005226842047796, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:51,832 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:51,853 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.38272
2023-07-02 10:33:51,853 [model] Computed derived parameters: {}
2023-07-02 10:33:51,853 [mcmc] New sample, #264:
Omega_m:0.3047076, b1:0.5206024
2023-07-02 10:33:51,854 [model] Posterior to be computed for parameters {'Omega_m': 0.3239347229402879, 'b1': 0.49050089851565704}
2023-07-02 10:33:51,854 [prior] Evaluating prior at array([0.32393472, 0.4905009 ])
2023-07-02 10:33:51,854 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:51,854 [model] Got input parameters: {'Omega_m': 0.3239347229402879, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49050089851565704, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:51,854 [classy] Got parameters {'Omega_m': 0.3239347229402879, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:51,854 [classy] Computing new state
2023-07-02 10:33:51,854 [classy] Setting parameters: {'Omega_m': 0.3239347229402879, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:51,899 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.90429938749142}
2023-07-02 10:33:51,899 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:51,901 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00801879
2023-07-02 10:33:51,901 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49050089851565704, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:51,901 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:51,921 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.40176
2023-07-02 10:33:51,921 [model] Computed derived parameters: {}
2023-07-02 10:33:51,921 [mcmc] New sample, #265:
Omega_m:0.3047076, b1:0.5005227
2023-07-02 10:33:51,921 [model] Posterior to be computed for parameters {'Omega_m': 0.3239347229402879, 'b1': 0.5150284660701672}
2023-07-02 10:33:51,921 [prior] Evaluating prior at array([0.32393472, 0.51502847])
2023-07-02 10:33:51,921 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:51,921 [model] Got input parameters: {'Omega_m': 0.3239347229402879, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5150284660701672, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:51,921 [classy] Got parameters {'Omega_m': 0.3239347229402879, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:51,921 [classy] Re-using computed results
2023-07-02 10:33:51,921 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.90429938749142}
2023-07-02 10:33:51,921 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:51,921 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5150284660701672, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:51,921 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:51,942 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.16309
2023-07-02 10:33:51,942 [model] Computed derived parameters: {}
2023-07-02 10:33:51,942 [model] Posterior to be computed for parameters {'Omega_m': 0.33775322712757355, 'b1': 0.4832982543927743}
2023-07-02 10:33:51,942 [prior] Evaluating prior at array([0.33775323, 0.48329825])
2023-07-02 10:33:51,942 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:51,942 [model] Got input parameters: {'Omega_m': 0.33775322712757355, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4832982543927743, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:51,942 [classy] Got parameters {'Omega_m': 0.33775322712757355, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:51,942 [classy] Computing new state
2023-07-02 10:33:51,942 [classy] Setting parameters: {'Omega_m': 0.33775322712757355, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:51,987 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.32425508865623}
2023-07-02 10:33:51,987 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:51,989 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.037025
2023-07-02 10:33:51,989 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4832982543927743, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:51,989 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:52,008 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.31929
2023-07-02 10:33:52,008 [model] Computed derived parameters: {}
2023-07-02 10:33:52,008 [model] Posterior to be computed for parameters {'Omega_m': 0.3239347229402879, 'b1': 0.4766887309920851}
2023-07-02 10:33:52,008 [prior] Evaluating prior at array([0.32393472, 0.47668873])
2023-07-02 10:33:52,009 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:52,009 [model] Got input parameters: {'Omega_m': 0.3239347229402879, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4766887309920851, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,009 [classy] Got parameters {'Omega_m': 0.3239347229402879, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:52,009 [classy] Re-using computed results
2023-07-02 10:33:52,009 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.90429938749142}
2023-07-02 10:33:52,009 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:52,009 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4766887309920851, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,009 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:52,030 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.36286
2023-07-02 10:33:52,030 [model] Computed derived parameters: {}
2023-07-02 10:33:52,031 [mcmc] New sample, #266:
Omega_m:0.3239347, b1:0.4905009
2023-07-02 10:33:52,031 [model] Posterior to be computed for parameters {'Omega_m': 0.32678787981476004, 'b1': 0.4752015748342943}
2023-07-02 10:33:52,031 [prior] Evaluating prior at array([0.32678788, 0.47520157])
2023-07-02 10:33:52,031 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:52,031 [model] Got input parameters: {'Omega_m': 0.32678787981476004, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4752015748342943, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,031 [classy] Got parameters {'Omega_m': 0.32678787981476004, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:52,031 [classy] Computing new state
2023-07-02 10:33:52,031 [classy] Setting parameters: {'Omega_m': 0.32678787981476004, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:52,077 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.57313708182923}
2023-07-02 10:33:52,077 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:52,078 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0123156
2023-07-02 10:33:52,078 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4752015748342943, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,078 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:52,098 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.16836
2023-07-02 10:33:52,098 [model] Computed derived parameters: {}
2023-07-02 10:33:52,098 [mcmc] New sample, #267:
Omega_m:0.3239347, b1:0.4766887
2023-07-02 10:33:52,099 [model] Posterior to be computed for parameters {'Omega_m': 0.32678787981476004, 'b1': 0.4384108036318327}
2023-07-02 10:33:52,099 [prior] Evaluating prior at array([0.32678788, 0.4384108 ])
2023-07-02 10:33:52,099 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:52,099 [model] Got input parameters: {'Omega_m': 0.32678787981476004, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4384108036318327, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,099 [classy] Got parameters {'Omega_m': 0.32678787981476004, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:52,099 [classy] Re-using computed results
2023-07-02 10:33:52,099 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.57313708182923}
2023-07-02 10:33:52,099 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:52,099 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4384108036318327, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,099 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:52,119 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.09442
2023-07-02 10:33:52,119 [model] Computed derived parameters: {}
2023-07-02 10:33:52,119 [model] Posterior to be computed for parameters {'Omega_m': 0.3221961682150266, 'b1': 0.4775949210401899}
2023-07-02 10:33:52,119 [prior] Evaluating prior at array([0.32219617, 0.47759492])
2023-07-02 10:33:52,119 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:52,119 [model] Got input parameters: {'Omega_m': 0.3221961682150266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4775949210401899, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,119 [classy] Got parameters {'Omega_m': 0.3221961682150266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:52,119 [classy] Computing new state
2023-07-02 10:33:52,119 [classy] Setting parameters: {'Omega_m': 0.3221961682150266, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:52,165 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.10737138067196}
2023-07-02 10:33:52,165 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:52,167 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00584926
2023-07-02 10:33:52,167 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4775949210401899, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,167 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:52,187 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.40633
2023-07-02 10:33:52,187 [model] Computed derived parameters: {}
2023-07-02 10:33:52,188 [mcmc] New sample, #268:
Omega_m:0.3267879, b1:0.4752016
2023-07-02 10:33:52,188 [model] Posterior to be computed for parameters {'Omega_m': 0.3221961682150266, 'b1': 0.420251498500124}
2023-07-02 10:33:52,188 [prior] Evaluating prior at array([0.32219617, 0.4202515 ])
2023-07-02 10:33:52,188 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:52,188 [model] Got input parameters: {'Omega_m': 0.3221961682150266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.420251498500124, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,188 [classy] Got parameters {'Omega_m': 0.3221961682150266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:52,188 [classy] Re-using computed results
2023-07-02 10:33:52,188 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.10737138067196}
2023-07-02 10:33:52,188 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:52,188 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.420251498500124, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,188 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:52,207 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.73415
2023-07-02 10:33:52,207 [model] Computed derived parameters: {}
2023-07-02 10:33:52,208 [model] Posterior to be computed for parameters {'Omega_m': 0.3151207404439022, 'b1': 0.48128285915287367}
2023-07-02 10:33:52,208 [prior] Evaluating prior at array([0.31512074, 0.48128286])
2023-07-02 10:33:52,208 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:52,208 [model] Got input parameters: {'Omega_m': 0.3151207404439022, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48128285915287367, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,208 [classy] Got parameters {'Omega_m': 0.3151207404439022, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:52,208 [classy] Computing new state
2023-07-02 10:33:52,208 [classy] Setting parameters: {'Omega_m': 0.3151207404439022, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:52,254 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.94402197317447}
2023-07-02 10:33:52,254 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:52,255 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000626048
2023-07-02 10:33:52,255 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48128285915287367, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,255 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:52,275 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.98703
2023-07-02 10:33:52,275 [model] Computed derived parameters: {}
2023-07-02 10:33:52,275 [model] Posterior to be computed for parameters {'Omega_m': 0.3221961682150266, 'b1': 0.47325021735174155}
2023-07-02 10:33:52,275 [prior] Evaluating prior at array([0.32219617, 0.47325022])
2023-07-02 10:33:52,276 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:52,276 [model] Got input parameters: {'Omega_m': 0.3221961682150266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47325021735174155, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,276 [classy] Got parameters {'Omega_m': 0.3221961682150266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:52,276 [classy] Re-using computed results
2023-07-02 10:33:52,276 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.10737138067196}
2023-07-02 10:33:52,276 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:52,276 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47325021735174155, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,276 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:52,295 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.1315
2023-07-02 10:33:52,295 [model] Computed derived parameters: {}
2023-07-02 10:33:52,296 [model] Posterior to be computed for parameters {'Omega_m': 0.3388016961071284, 'b1': 0.4689395914720693}
2023-07-02 10:33:52,296 [prior] Evaluating prior at array([0.3388017 , 0.46893959])
2023-07-02 10:33:52,296 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:52,296 [model] Got input parameters: {'Omega_m': 0.3388016961071284, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4689395914720693, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,296 [classy] Got parameters {'Omega_m': 0.3388016961071284, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:52,296 [classy] Computing new state
2023-07-02 10:33:52,296 [classy] Setting parameters: {'Omega_m': 0.3388016961071284, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:52,341 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.20677032157133}
2023-07-02 10:33:52,341 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:52,343 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0400451
2023-07-02 10:33:52,343 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4689395914720693, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,343 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:52,362 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.289883
2023-07-02 10:33:52,362 [model] Computed derived parameters: {}
2023-07-02 10:33:52,362 [model] Posterior to be computed for parameters {'Omega_m': 0.3221961682150266, 'b1': 0.46871344119895875}
2023-07-02 10:33:52,362 [prior] Evaluating prior at array([0.32219617, 0.46871344])
2023-07-02 10:33:52,362 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:52,362 [model] Got input parameters: {'Omega_m': 0.3221961682150266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46871344119895875, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,362 [classy] Got parameters {'Omega_m': 0.3221961682150266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:52,362 [classy] Re-using computed results
2023-07-02 10:33:52,363 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.10737138067196}
2023-07-02 10:33:52,363 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:52,363 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46871344119895875, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,363 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:52,383 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.73979
2023-07-02 10:33:52,383 [model] Computed derived parameters: {}
2023-07-02 10:33:52,383 [mcmc] New sample, #269:
Omega_m:0.3221962, b1:0.4775949
2023-07-02 10:33:52,383 [model] Posterior to be computed for parameters {'Omega_m': 0.38406238523667957, 'b1': 0.436466800144568}
2023-07-02 10:33:52,383 [prior] Evaluating prior at array([0.38406239, 0.4364668 ])
2023-07-02 10:33:52,383 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:52,383 [model] Got input parameters: {'Omega_m': 0.38406238523667957, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.436466800144568, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,383 [classy] Got parameters {'Omega_m': 0.38406238523667957, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:52,383 [classy] Computing new state
2023-07-02 10:33:52,383 [classy] Setting parameters: {'Omega_m': 0.38406238523667957, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:52,428 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 139.4293326830357}
2023-07-02 10:33:52,428 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:52,430 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.266085
2023-07-02 10:33:52,430 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.436466800144568, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,430 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:52,451 [fs_likelihood.fslikelihood] Computed log-likelihood = -27.7362
2023-07-02 10:33:52,451 [model] Computed derived parameters: {}
2023-07-02 10:33:52,451 [model] Posterior to be computed for parameters {'Omega_m': 0.3221961682150266, 'b1': 0.46689188054913966}
2023-07-02 10:33:52,451 [prior] Evaluating prior at array([0.32219617, 0.46689188])
2023-07-02 10:33:52,452 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:52,452 [model] Got input parameters: {'Omega_m': 0.3221961682150266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46689188054913966, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,452 [classy] Got parameters {'Omega_m': 0.3221961682150266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:52,452 [classy] Re-using computed results
2023-07-02 10:33:52,452 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.10737138067196}
2023-07-02 10:33:52,452 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:52,452 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46689188054913966, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,452 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:52,471 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.55274
2023-07-02 10:33:52,471 [model] Computed derived parameters: {}
2023-07-02 10:33:52,471 [mcmc] New sample, #270:
Omega_m:0.3221962, b1:0.4687134
2023-07-02 10:33:52,471 [model] Posterior to be computed for parameters {'Omega_m': 0.3474133490134868, 'b1': 0.4537478834412025}
2023-07-02 10:33:52,471 [prior] Evaluating prior at array([0.34741335, 0.45374788])
2023-07-02 10:33:52,471 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:52,471 [model] Got input parameters: {'Omega_m': 0.3474133490134868, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4537478834412025, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,471 [classy] Got parameters {'Omega_m': 0.3474133490134868, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:52,471 [classy] Computing new state
2023-07-02 10:33:52,471 [classy] Setting parameters: {'Omega_m': 0.3474133490134868, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:52,516 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.2541400395014}
2023-07-02 10:33:52,516 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:52,517 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0689812
2023-07-02 10:33:52,517 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4537478834412025, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,517 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:52,538 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.56898
2023-07-02 10:33:52,538 [model] Computed derived parameters: {}
2023-07-02 10:33:52,538 [model] Posterior to be computed for parameters {'Omega_m': 0.3221961682150266, 'b1': 0.48387743862284194}
2023-07-02 10:33:52,538 [prior] Evaluating prior at array([0.32219617, 0.48387744])
2023-07-02 10:33:52,538 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:52,538 [model] Got input parameters: {'Omega_m': 0.3221961682150266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48387743862284194, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,538 [classy] Got parameters {'Omega_m': 0.3221961682150266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:52,538 [classy] Re-using computed results
2023-07-02 10:33:52,538 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.10737138067196}
2023-07-02 10:33:52,538 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:52,538 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48387743862284194, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,538 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:52,558 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.62744
2023-07-02 10:33:52,558 [model] Computed derived parameters: {}
2023-07-02 10:33:52,558 [mcmc] New sample, #271:
Omega_m:0.3221962, b1:0.4668919
2023-07-02 10:33:52,558 [model] Posterior to be computed for parameters {'Omega_m': 0.35777925040914815, 'b1': 0.4653304038377488}
2023-07-02 10:33:52,558 [prior] Evaluating prior at array([0.35777925, 0.4653304 ])
2023-07-02 10:33:52,559 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:52,559 [model] Got input parameters: {'Omega_m': 0.35777925040914815, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4653304038377488, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,559 [classy] Got parameters {'Omega_m': 0.35777925040914815, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:52,559 [classy] Computing new state
2023-07-02 10:33:52,559 [classy] Setting parameters: {'Omega_m': 0.35777925040914815, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:52,603 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.13574901602055}
2023-07-02 10:33:52,603 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:52,605 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.113125
2023-07-02 10:33:52,605 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4653304038377488, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,605 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:52,625 [fs_likelihood.fslikelihood] Computed log-likelihood = -10.7601
2023-07-02 10:33:52,625 [model] Computed derived parameters: {}
2023-07-02 10:33:52,625 [model] Posterior to be computed for parameters {'Omega_m': 0.3221961682150266, 'b1': 0.493659325340613}
2023-07-02 10:33:52,625 [prior] Evaluating prior at array([0.32219617, 0.49365933])
2023-07-02 10:33:52,625 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:52,625 [model] Got input parameters: {'Omega_m': 0.3221961682150266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.493659325340613, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,625 [classy] Got parameters {'Omega_m': 0.3221961682150266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:52,625 [classy] Re-using computed results
2023-07-02 10:33:52,625 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.10737138067196}
2023-07-02 10:33:52,625 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:52,625 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.493659325340613, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,625 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:52,647 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.5481
2023-07-02 10:33:52,647 [model] Computed derived parameters: {}
2023-07-02 10:33:52,647 [mcmc] New sample, #272:
Omega_m:0.3221962, b1:0.4838774
2023-07-02 10:33:52,647 [model] Posterior to be computed for parameters {'Omega_m': 0.33969278009441306, 'b1': 0.48453953444172726}
2023-07-02 10:33:52,647 [prior] Evaluating prior at array([0.33969278, 0.48453953])
2023-07-02 10:33:52,648 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:52,648 [model] Got input parameters: {'Omega_m': 0.33969278009441306, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48453953444172726, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,648 [classy] Got parameters {'Omega_m': 0.33969278009441306, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:52,648 [classy] Computing new state
2023-07-02 10:33:52,648 [classy] Setting parameters: {'Omega_m': 0.33969278009441306, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:52,692 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.1071784963586}
2023-07-02 10:33:52,692 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:52,694 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0426993
2023-07-02 10:33:52,694 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48453953444172726, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,694 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:52,713 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.48427
2023-07-02 10:33:52,713 [model] Computed derived parameters: {}
2023-07-02 10:33:52,713 [model] Posterior to be computed for parameters {'Omega_m': 0.3221961682150266, 'b1': 0.5047649480853185}
2023-07-02 10:33:52,714 [prior] Evaluating prior at array([0.32219617, 0.50476495])
2023-07-02 10:33:52,714 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:52,714 [model] Got input parameters: {'Omega_m': 0.3221961682150266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5047649480853185, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,714 [classy] Got parameters {'Omega_m': 0.3221961682150266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:52,714 [classy] Re-using computed results
2023-07-02 10:33:52,714 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.10737138067196}
2023-07-02 10:33:52,714 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:52,714 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5047649480853185, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,714 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:52,733 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.81541
2023-07-02 10:33:52,734 [model] Computed derived parameters: {}
2023-07-02 10:33:52,734 [model] Posterior to be computed for parameters {'Omega_m': 0.3506521754071579, 'b1': 0.4788271488484791}
2023-07-02 10:33:52,734 [prior] Evaluating prior at array([0.35065218, 0.47882715])
2023-07-02 10:33:52,734 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:52,734 [model] Got input parameters: {'Omega_m': 0.3506521754071579, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4788271488484791, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,734 [classy] Got parameters {'Omega_m': 0.3506521754071579, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:52,734 [classy] Computing new state
2023-07-02 10:33:52,734 [classy] Setting parameters: {'Omega_m': 0.3506521754071579, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:52,778 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.9014544066976}
2023-07-02 10:33:52,778 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:52,780 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0817106
2023-07-02 10:33:52,780 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4788271488484791, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,780 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:52,800 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.49312
2023-07-02 10:33:52,800 [model] Computed derived parameters: {}
2023-07-02 10:33:52,800 [model] Posterior to be computed for parameters {'Omega_m': 0.3221961682150266, 'b1': 0.5099723525119436}
2023-07-02 10:33:52,800 [prior] Evaluating prior at array([0.32219617, 0.50997235])
2023-07-02 10:33:52,800 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:52,800 [model] Got input parameters: {'Omega_m': 0.3221961682150266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5099723525119436, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,800 [classy] Got parameters {'Omega_m': 0.3221961682150266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:52,801 [classy] Re-using computed results
2023-07-02 10:33:52,801 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.10737138067196}
2023-07-02 10:33:52,801 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:52,801 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5099723525119436, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,801 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:52,820 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.23036
2023-07-02 10:33:52,820 [model] Computed derived parameters: {}
2023-07-02 10:33:52,820 [model] Posterior to be computed for parameters {'Omega_m': 0.32357066222357805, 'b1': 0.492942895323409}
2023-07-02 10:33:52,820 [prior] Evaluating prior at array([0.32357066, 0.4929429 ])
2023-07-02 10:33:52,820 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:52,820 [model] Got input parameters: {'Omega_m': 0.32357066222357805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.492942895323409, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,821 [classy] Got parameters {'Omega_m': 0.32357066222357805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:52,821 [classy] Computing new state
2023-07-02 10:33:52,821 [classy] Setting parameters: {'Omega_m': 0.32357066222357805, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:52,866 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.94674261028348}
2023-07-02 10:33:52,866 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:52,868 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00753615
2023-07-02 10:33:52,868 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.492942895323409, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,868 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:52,888 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.36395
2023-07-02 10:33:52,888 [model] Computed derived parameters: {}
2023-07-02 10:33:52,888 [mcmc] New sample, #273:
Omega_m:0.3221962, b1:0.4936593
2023-07-02 10:33:52,888 [model] Posterior to be computed for parameters {'Omega_m': 0.32357066222357805, 'b1': 0.5077432334076324}
2023-07-02 10:33:52,888 [prior] Evaluating prior at array([0.32357066, 0.50774323])
2023-07-02 10:33:52,888 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:52,888 [model] Got input parameters: {'Omega_m': 0.32357066222357805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5077432334076324, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,888 [classy] Got parameters {'Omega_m': 0.32357066222357805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:52,888 [classy] Re-using computed results
2023-07-02 10:33:52,888 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.94674261028348}
2023-07-02 10:33:52,888 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:52,888 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5077432334076324, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,888 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:52,908 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.08162
2023-07-02 10:33:52,908 [model] Computed derived parameters: {}
2023-07-02 10:33:52,908 [model] Posterior to be computed for parameters {'Omega_m': 0.3304213804879385, 'b1': 0.48937208295648715}
2023-07-02 10:33:52,908 [prior] Evaluating prior at array([0.33042138, 0.48937208])
2023-07-02 10:33:52,909 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:52,909 [model] Got input parameters: {'Omega_m': 0.3304213804879385, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48937208295648715, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,909 [classy] Got parameters {'Omega_m': 0.3304213804879385, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:52,909 [classy] Computing new state
2023-07-02 10:33:52,909 [classy] Setting parameters: {'Omega_m': 0.3304213804879385, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:52,953 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.15514703239165}
2023-07-02 10:33:52,953 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:52,954 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0190856
2023-07-02 10:33:52,955 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48937208295648715, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,955 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:52,974 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.901907
2023-07-02 10:33:52,974 [model] Computed derived parameters: {}
2023-07-02 10:33:52,974 [model] Posterior to be computed for parameters {'Omega_m': 0.32357066222357805, 'b1': 0.49237970773026063}
2023-07-02 10:33:52,974 [prior] Evaluating prior at array([0.32357066, 0.49237971])
2023-07-02 10:33:52,974 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:52,975 [model] Got input parameters: {'Omega_m': 0.32357066222357805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49237970773026063, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,975 [classy] Got parameters {'Omega_m': 0.32357066222357805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:52,975 [classy] Re-using computed results
2023-07-02 10:33:52,975 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.94674261028348}
2023-07-02 10:33:52,975 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:52,975 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49237970773026063, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,975 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:52,995 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.38831
2023-07-02 10:33:52,995 [model] Computed derived parameters: {}
2023-07-02 10:33:52,995 [mcmc] New sample, #274:
Omega_m:0.3235707, b1:0.4929429
2023-07-02 10:33:52,995 [model] Posterior to be computed for parameters {'Omega_m': 0.3034602817719684, 'b1': 0.5028618779858514}
2023-07-02 10:33:52,995 [prior] Evaluating prior at array([0.30346028, 0.50286188])
2023-07-02 10:33:52,995 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:52,995 [model] Got input parameters: {'Omega_m': 0.3034602817719684, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5028618779858514, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:52,995 [classy] Got parameters {'Omega_m': 0.3034602817719684, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:52,995 [classy] Computing new state
2023-07-02 10:33:52,995 [classy] Setting parameters: {'Omega_m': 0.3034602817719684, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:53,039 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.3600428845973}
2023-07-02 10:33:53,039 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:53,041 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00530996
2023-07-02 10:33:53,042 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5028618779858514, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:53,042 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:53,062 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.22392
2023-07-02 10:33:53,063 [model] Computed derived parameters: {}
2023-07-02 10:33:53,063 [model] Posterior to be computed for parameters {'Omega_m': 0.32357066222357805, 'b1': 0.4833014673971425}
2023-07-02 10:33:53,063 [prior] Evaluating prior at array([0.32357066, 0.48330147])
2023-07-02 10:33:53,063 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:53,063 [model] Got input parameters: {'Omega_m': 0.32357066222357805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4833014673971425, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:53,063 [classy] Got parameters {'Omega_m': 0.32357066222357805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:53,063 [classy] Re-using computed results
2023-07-02 10:33:53,063 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.94674261028348}
2023-07-02 10:33:53,063 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:53,063 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4833014673971425, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:53,063 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:53,083 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.53966
2023-07-02 10:33:53,083 [model] Computed derived parameters: {}
2023-07-02 10:33:53,083 [mcmc] New sample, #275:
Omega_m:0.3235707, b1:0.4923797
2023-07-02 10:33:53,083 [model] Posterior to be computed for parameters {'Omega_m': 0.32356006392974085, 'b1': 0.48330699156515555}
2023-07-02 10:33:53,083 [prior] Evaluating prior at array([0.32356006, 0.48330699])
2023-07-02 10:33:53,083 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:53,083 [model] Got input parameters: {'Omega_m': 0.32356006392974085, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48330699156515555, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:53,083 [classy] Got parameters {'Omega_m': 0.32356006392974085, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:53,083 [classy] Computing new state
2023-07-02 10:33:53,083 [classy] Setting parameters: {'Omega_m': 0.32356006392974085, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:53,128 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.94797900491105}
2023-07-02 10:33:53,128 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:53,130 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00752231
2023-07-02 10:33:53,131 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48330699156515555, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:53,131 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:53,152 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.5405
2023-07-02 10:33:53,152 [model] Computed derived parameters: {}
2023-07-02 10:33:53,152 [mcmc] New sample, #276:
Omega_m:0.3235707, b1:0.4833015
2023-07-02 10:33:53,152 [model] Posterior to be computed for parameters {'Omega_m': 0.32356006392974085, 'b1': 0.4906896996698696}
2023-07-02 10:33:53,152 [prior] Evaluating prior at array([0.32356006, 0.4906897 ])
2023-07-02 10:33:53,152 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:53,152 [model] Got input parameters: {'Omega_m': 0.32356006392974085, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4906896996698696, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:53,152 [classy] Got parameters {'Omega_m': 0.32356006392974085, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:53,152 [classy] Re-using computed results
2023-07-02 10:33:53,152 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.94797900491105}
2023-07-02 10:33:53,152 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:53,153 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4906896996698696, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:53,153 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:53,172 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.45239
2023-07-02 10:33:53,172 [model] Computed derived parameters: {}
2023-07-02 10:33:53,172 [mcmc] New sample, #277:
Omega_m:0.3235601, b1:0.483307
2023-07-02 10:33:53,172 [model] Posterior to be computed for parameters {'Omega_m': 0.3315251115912112, 'b1': 0.4865380633603365}
2023-07-02 10:33:53,172 [prior] Evaluating prior at array([0.33152511, 0.48653806])
2023-07-02 10:33:53,173 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:53,173 [model] Got input parameters: {'Omega_m': 0.3315251115912112, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4865380633603365, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:53,173 [classy] Got parameters {'Omega_m': 0.3315251115912112, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:53,173 [classy] Computing new state
2023-07-02 10:33:53,173 [classy] Setting parameters: {'Omega_m': 0.3315251115912112, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:53,217 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.0290090570606}
2023-07-02 10:33:53,217 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:53,219 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0214242
2023-07-02 10:33:53,219 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4865380633603365, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:53,219 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:53,238 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.801885
2023-07-02 10:33:53,238 [model] Computed derived parameters: {}
2023-07-02 10:33:53,238 [model] Posterior to be computed for parameters {'Omega_m': 0.32356006392974085, 'b1': 0.4956688030054077}
2023-07-02 10:33:53,238 [prior] Evaluating prior at array([0.32356006, 0.4956688 ])
2023-07-02 10:33:53,239 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:53,239 [model] Got input parameters: {'Omega_m': 0.32356006392974085, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4956688030054077, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:53,239 [classy] Got parameters {'Omega_m': 0.32356006392974085, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:53,239 [classy] Re-using computed results
2023-07-02 10:33:53,239 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.94797900491105}
2023-07-02 10:33:53,239 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:53,239 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4956688030054077, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:53,239 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:53,260 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.22314
2023-07-02 10:33:53,260 [model] Computed derived parameters: {}
2023-07-02 10:33:53,260 [mcmc] New sample, #278:
Omega_m:0.3235601, b1:0.4906897
2023-07-02 10:33:53,260 [model] Posterior to be computed for parameters {'Omega_m': 0.31822054808823197, 'b1': 0.49845192857917775}
2023-07-02 10:33:53,260 [prior] Evaluating prior at array([0.31822055, 0.49845193])
2023-07-02 10:33:53,261 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:53,261 [model] Got input parameters: {'Omega_m': 0.31822054808823197, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49845192857917775, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:53,261 [classy] Got parameters {'Omega_m': 0.31822054808823197, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:53,261 [classy] Computing new state
2023-07-02 10:33:53,261 [classy] Setting parameters: {'Omega_m': 0.31822054808823197, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:53,305 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.5754415837184}
2023-07-02 10:33:53,305 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:53,306 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00219179
2023-07-02 10:33:53,307 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49845192857917775, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:53,307 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:53,326 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.83346
2023-07-02 10:33:53,326 [model] Computed derived parameters: {}
2023-07-02 10:33:53,326 [mcmc] New sample, #279:
Omega_m:0.3235601, b1:0.4956688
2023-07-02 10:33:53,326 [model] Posterior to be computed for parameters {'Omega_m': 0.31822054808823197, 'b1': 0.48610974002033136}
2023-07-02 10:33:53,326 [prior] Evaluating prior at array([0.31822055, 0.48610974])
2023-07-02 10:33:53,327 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:53,327 [model] Got input parameters: {'Omega_m': 0.31822054808823197, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48610974002033136, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:53,327 [classy] Got parameters {'Omega_m': 0.31822054808823197, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:53,327 [classy] Re-using computed results
2023-07-02 10:33:53,327 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.5754415837184}
2023-07-02 10:33:53,327 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:53,327 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48610974002033136, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:53,327 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:53,346 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.68695
2023-07-02 10:33:53,347 [model] Computed derived parameters: {}
2023-07-02 10:33:53,347 [mcmc] New sample, #280:
Omega_m:0.3182205, b1:0.4984519
2023-07-02 10:33:53,347 [model] Posterior to be computed for parameters {'Omega_m': 0.32109346218620616, 'b1': 0.4846122857689255}
2023-07-02 10:33:53,347 [prior] Evaluating prior at array([0.32109346, 0.48461229])
2023-07-02 10:33:53,347 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:53,347 [model] Got input parameters: {'Omega_m': 0.32109346218620616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4846122857689255, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:53,347 [classy] Got parameters {'Omega_m': 0.32109346218620616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:53,347 [classy] Computing new state
2023-07-02 10:33:53,347 [classy] Setting parameters: {'Omega_m': 0.32109346218620616, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:53,390 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.23668157389145}
2023-07-02 10:33:53,391 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:53,392 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00465172
2023-07-02 10:33:53,393 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4846122857689255, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:53,393 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:53,412 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.67669
2023-07-02 10:33:53,412 [model] Computed derived parameters: {}
2023-07-02 10:33:53,412 [mcmc] New sample, #281:
Omega_m:0.3182205, b1:0.4861097
2023-07-02 10:33:53,412 [model] Posterior to be computed for parameters {'Omega_m': 0.32109346218620616, 'b1': 0.4710120966171956}
2023-07-02 10:33:53,412 [prior] Evaluating prior at array([0.32109346, 0.4710121 ])
2023-07-02 10:33:53,413 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:53,413 [model] Got input parameters: {'Omega_m': 0.32109346218620616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4710120966171956, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:53,413 [classy] Got parameters {'Omega_m': 0.32109346218620616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:53,413 [classy] Re-using computed results
2023-07-02 10:33:53,413 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.23668157389145}
2023-07-02 10:33:53,413 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:53,413 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4710120966171956, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:53,413 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:53,432 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.84651
2023-07-02 10:33:53,432 [model] Computed derived parameters: {}
2023-07-02 10:33:53,432 [mcmc] New sample, #282:
Omega_m:0.3210935, b1:0.4846123
2023-07-02 10:33:53,432 [model] Posterior to be computed for parameters {'Omega_m': 0.3104378725197752, 'b1': 0.4765661290397052}
2023-07-02 10:33:53,432 [prior] Evaluating prior at array([0.31043787, 0.47656613])
2023-07-02 10:33:53,432 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:53,432 [model] Got input parameters: {'Omega_m': 0.3104378725197752, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4765661290397052, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:53,432 [classy] Got parameters {'Omega_m': 0.3104378725197752, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:53,432 [classy] Computing new state
2023-07-02 10:33:53,432 [classy] Setting parameters: {'Omega_m': 0.3104378725197752, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:53,478 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.50705443581444}
2023-07-02 10:33:53,478 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:53,480 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000460432
2023-07-02 10:33:53,480 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4765661290397052, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:53,480 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:53,499 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.124793
2023-07-02 10:33:53,500 [model] Computed derived parameters: {}
2023-07-02 10:33:53,500 [mcmc] New sample, #283:
Omega_m:0.3210935, b1:0.4710121
2023-07-02 10:33:53,500 [model] Posterior to be computed for parameters {'Omega_m': 0.3104378725197752, 'b1': 0.5145979134099927}
2023-07-02 10:33:53,500 [prior] Evaluating prior at array([0.31043787, 0.51459791])
2023-07-02 10:33:53,500 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:53,500 [model] Got input parameters: {'Omega_m': 0.3104378725197752, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5145979134099927, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:53,500 [classy] Got parameters {'Omega_m': 0.3104378725197752, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:53,500 [classy] Re-using computed results
2023-07-02 10:33:53,500 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.50705443581444}
2023-07-02 10:33:53,500 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:53,500 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5145979134099927, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:53,500 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:53,519 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.70101
2023-07-02 10:33:53,519 [model] Computed derived parameters: {}
2023-07-02 10:33:53,520 [mcmc] New sample, #284:
Omega_m:0.3104379, b1:0.4765661
2023-07-02 10:33:53,520 [model] Posterior to be computed for parameters {'Omega_m': 0.2798918689187615, 'b1': 0.5305194625395163}
2023-07-02 10:33:53,520 [prior] Evaluating prior at array([0.27989187, 0.53051946])
2023-07-02 10:33:53,520 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:53,520 [model] Got input parameters: {'Omega_m': 0.2798918689187615, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5305194625395163, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:53,520 [classy] Got parameters {'Omega_m': 0.2798918689187615, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:53,520 [classy] Computing new state
2023-07-02 10:33:53,520 [classy] Setting parameters: {'Omega_m': 0.2798918689187615, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:53,564 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.3739294115847}
2023-07-02 10:33:53,564 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:53,566 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.071031
2023-07-02 10:33:53,566 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5305194625395163, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:53,566 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:53,586 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.00385
2023-07-02 10:33:53,586 [model] Computed derived parameters: {}
2023-07-02 10:33:53,586 [model] Posterior to be computed for parameters {'Omega_m': 0.3104378725197752, 'b1': 0.5201523104871444}
2023-07-02 10:33:53,586 [prior] Evaluating prior at array([0.31043787, 0.52015231])
2023-07-02 10:33:53,586 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:53,586 [model] Got input parameters: {'Omega_m': 0.3104378725197752, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5201523104871444, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:53,586 [classy] Got parameters {'Omega_m': 0.3104378725197752, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:53,586 [classy] Re-using computed results
2023-07-02 10:33:53,586 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.50705443581444}
2023-07-02 10:33:53,586 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:53,586 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5201523104871444, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:53,586 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:53,606 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.43677
2023-07-02 10:33:53,607 [model] Computed derived parameters: {}
2023-07-02 10:33:53,607 [mcmc] New sample, #285:
Omega_m:0.3104379, b1:0.5145979
2023-07-02 10:33:53,607 [model] Posterior to be computed for parameters {'Omega_m': 0.3138812107630452, 'b1': 0.5183575330188418}
2023-07-02 10:33:53,607 [prior] Evaluating prior at array([0.31388121, 0.51835753])
2023-07-02 10:33:53,607 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:53,607 [model] Got input parameters: {'Omega_m': 0.3138812107630452, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5183575330188418, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:53,607 [classy] Got parameters {'Omega_m': 0.3138812107630452, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:53,607 [classy] Computing new state
2023-07-02 10:33:53,607 [classy] Setting parameters: {'Omega_m': 0.3138812107630452, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:53,652 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.0923279065068}
2023-07-02 10:33:53,652 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:53,654 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000321711
2023-07-02 10:33:53,654 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5183575330188418, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:53,654 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:53,673 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.21838
2023-07-02 10:33:53,674 [model] Computed derived parameters: {}
2023-07-02 10:33:53,674 [mcmc] New sample, #286:
Omega_m:0.3104379, b1:0.5201523
2023-07-02 10:33:53,674 [model] Posterior to be computed for parameters {'Omega_m': 0.3138812107630452, 'b1': 0.5003344783234781}
2023-07-02 10:33:53,674 [prior] Evaluating prior at array([0.31388121, 0.50033448])
2023-07-02 10:33:53,674 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:53,674 [model] Got input parameters: {'Omega_m': 0.3138812107630452, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5003344783234781, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:53,674 [classy] Got parameters {'Omega_m': 0.3138812107630452, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:53,674 [classy] Re-using computed results
2023-07-02 10:33:53,674 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.0923279065068}
2023-07-02 10:33:53,674 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:53,674 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5003344783234781, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:53,674 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:53,693 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.90579
2023-07-02 10:33:53,693 [model] Computed derived parameters: {}
2023-07-02 10:33:53,693 [mcmc] New sample, #287:
Omega_m:0.3138812, b1:0.5183575
2023-07-02 10:33:53,693 [model] Posterior to be computed for parameters {'Omega_m': 0.31571756183507443, 'b1': 0.49937731370730565}
2023-07-02 10:33:53,694 [prior] Evaluating prior at array([0.31571756, 0.49937731])
2023-07-02 10:33:53,694 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:53,694 [model] Got input parameters: {'Omega_m': 0.31571756183507443, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49937731370730565, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:53,694 [classy] Got parameters {'Omega_m': 0.31571756183507443, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:53,694 [classy] Computing new state
2023-07-02 10:33:53,694 [classy] Setting parameters: {'Omega_m': 0.31571756183507443, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:53,738 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.87280901139144}
2023-07-02 10:33:53,738 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:53,740 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000838507
2023-07-02 10:33:53,740 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49937731370730565, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:53,740 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:53,760 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.92489
2023-07-02 10:33:53,760 [model] Computed derived parameters: {}
2023-07-02 10:33:53,760 [mcmc] New sample, #288:
Omega_m:0.3138812, b1:0.5003345
2023-07-02 10:33:53,760 [model] Posterior to be computed for parameters {'Omega_m': 0.31571756183507443, 'b1': 0.4904828326846904}
2023-07-02 10:33:53,760 [prior] Evaluating prior at array([0.31571756, 0.49048283])
2023-07-02 10:33:53,760 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:53,761 [model] Got input parameters: {'Omega_m': 0.31571756183507443, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4904828326846904, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:53,761 [classy] Got parameters {'Omega_m': 0.31571756183507443, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:53,761 [classy] Re-using computed results
2023-07-02 10:33:53,761 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.87280901139144}
2023-07-02 10:33:53,761 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:53,761 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4904828326846904, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:53,761 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:53,780 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.72908
2023-07-02 10:33:53,780 [model] Computed derived parameters: {}
2023-07-02 10:33:53,780 [model] Posterior to be computed for parameters {'Omega_m': 0.32685227335624856, 'b1': 0.4935735477272099}
2023-07-02 10:33:53,780 [prior] Evaluating prior at array([0.32685227, 0.49357355])
2023-07-02 10:33:53,780 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:53,780 [model] Got input parameters: {'Omega_m': 0.32685227335624856, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4935735477272099, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:53,780 [classy] Got parameters {'Omega_m': 0.32685227335624856, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:53,780 [classy] Computing new state
2023-07-02 10:33:53,780 [classy] Setting parameters: {'Omega_m': 0.32685227335624856, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:53,824 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.56569204959635}
2023-07-02 10:33:53,824 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:53,826 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.012423
2023-07-02 10:33:53,826 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4935735477272099, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:53,826 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:53,845 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.59945
2023-07-02 10:33:53,846 [model] Computed derived parameters: {}
2023-07-02 10:33:53,846 [model] Posterior to be computed for parameters {'Omega_m': 0.31571756183507443, 'b1': 0.4926862475308918}
2023-07-02 10:33:53,846 [prior] Evaluating prior at array([0.31571756, 0.49268625])
2023-07-02 10:33:53,846 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:53,846 [model] Got input parameters: {'Omega_m': 0.31571756183507443, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4926862475308918, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:53,846 [classy] Got parameters {'Omega_m': 0.31571756183507443, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:53,846 [classy] Re-using computed results
2023-07-02 10:33:53,846 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.87280901139144}
2023-07-02 10:33:53,846 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:53,846 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4926862475308918, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:53,846 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:53,866 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.81678
2023-07-02 10:33:53,866 [model] Computed derived parameters: {}
2023-07-02 10:33:53,866 [mcmc] New sample, #289:
Omega_m:0.3157176, b1:0.4993773
2023-07-02 10:33:53,866 [model] Posterior to be computed for parameters {'Omega_m': 0.3087804174416922, 'b1': 0.4963021079465623}
2023-07-02 10:33:53,866 [prior] Evaluating prior at array([0.30878042, 0.49630211])
2023-07-02 10:33:53,866 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:53,867 [model] Got input parameters: {'Omega_m': 0.3087804174416922, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4963021079465623, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:53,867 [classy] Got parameters {'Omega_m': 0.3087804174416922, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:53,867 [classy] Computing new state
2023-07-02 10:33:53,867 [classy] Setting parameters: {'Omega_m': 0.3087804174416922, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:53,911 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.70813435248712}
2023-07-02 10:33:53,911 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:53,913 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00105137
2023-07-02 10:33:53,913 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4963021079465623, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:53,913 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:53,932 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.06832
2023-07-02 10:33:53,932 [model] Computed derived parameters: {}
2023-07-02 10:33:53,932 [mcmc] New sample, #290:
Omega_m:0.3157176, b1:0.4926862
2023-07-02 10:33:53,932 [model] Posterior to be computed for parameters {'Omega_m': 0.3087804174416922, 'b1': 0.5026915201143093}
2023-07-02 10:33:53,932 [prior] Evaluating prior at array([0.30878042, 0.50269152])
2023-07-02 10:33:53,933 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:53,933 [model] Got input parameters: {'Omega_m': 0.3087804174416922, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5026915201143093, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:53,933 [classy] Got parameters {'Omega_m': 0.3087804174416922, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:53,933 [classy] Re-using computed results
2023-07-02 10:33:53,933 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.70813435248712}
2023-07-02 10:33:53,933 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:53,933 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5026915201143093, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:53,933 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:53,953 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.47652
2023-07-02 10:33:53,953 [model] Computed derived parameters: {}
2023-07-02 10:33:53,953 [mcmc] New sample, #291:
Omega_m:0.3087804, b1:0.4963021
2023-07-02 10:33:53,953 [model] Posterior to be computed for parameters {'Omega_m': 0.3153399666680525, 'b1': 0.49927247431574345}
2023-07-02 10:33:53,953 [prior] Evaluating prior at array([0.31533997, 0.49927247])
2023-07-02 10:33:53,953 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:53,953 [model] Got input parameters: {'Omega_m': 0.3153399666680525, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49927247431574345, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:53,953 [classy] Got parameters {'Omega_m': 0.3153399666680525, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:53,953 [classy] Computing new state
2023-07-02 10:33:53,953 [classy] Setting parameters: {'Omega_m': 0.3153399666680525, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:53,996 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.91785049146839}
2023-07-02 10:33:53,997 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:53,998 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000699118
2023-07-02 10:33:53,998 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49927247431574345, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:53,998 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:54,018 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.92605
2023-07-02 10:33:54,018 [model] Computed derived parameters: {}
2023-07-02 10:33:54,018 [mcmc] New sample, #292:
Omega_m:0.3087804, b1:0.5026915
2023-07-02 10:33:54,018 [model] Posterior to be computed for parameters {'Omega_m': 0.3153399666680525, 'b1': 0.5070957576836143}
2023-07-02 10:33:54,018 [prior] Evaluating prior at array([0.31533997, 0.50709576])
2023-07-02 10:33:54,019 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:54,019 [model] Got input parameters: {'Omega_m': 0.3153399666680525, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5070957576836143, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,019 [classy] Got parameters {'Omega_m': 0.3153399666680525, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:54,019 [classy] Re-using computed results
2023-07-02 10:33:54,019 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.91785049146839}
2023-07-02 10:33:54,019 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:54,019 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5070957576836143, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,019 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:54,038 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.77924
2023-07-02 10:33:54,038 [model] Computed derived parameters: {}
2023-07-02 10:33:54,038 [mcmc] New sample, #293:
Omega_m:0.31534, b1:0.4992725
2023-07-02 10:33:54,038 [model] Posterior to be computed for parameters {'Omega_m': 0.29701083859785266, 'b1': 0.5166494825139659}
2023-07-02 10:33:54,038 [prior] Evaluating prior at array([0.29701084, 0.51664948])
2023-07-02 10:33:54,039 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:54,039 [model] Got input parameters: {'Omega_m': 0.29701083859785266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5166494825139659, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,039 [classy] Got parameters {'Omega_m': 0.29701083859785266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:54,039 [classy] Computing new state
2023-07-02 10:33:54,039 [classy] Setting parameters: {'Omega_m': 0.29701083859785266, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:54,083 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.1639564575107}
2023-07-02 10:33:54,083 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:54,085 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0154688
2023-07-02 10:33:54,085 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5166494825139659, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,085 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:54,105 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.223758
2023-07-02 10:33:54,105 [model] Computed derived parameters: {}
2023-07-02 10:33:54,105 [model] Posterior to be computed for parameters {'Omega_m': 0.3153399666680525, 'b1': 0.5295800300586563}
2023-07-02 10:33:54,105 [prior] Evaluating prior at array([0.31533997, 0.52958003])
2023-07-02 10:33:54,105 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:54,105 [model] Got input parameters: {'Omega_m': 0.3153399666680525, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5295800300586563, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,105 [classy] Got parameters {'Omega_m': 0.3153399666680525, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:54,105 [classy] Re-using computed results
2023-07-02 10:33:54,105 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.91785049146839}
2023-07-02 10:33:54,105 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:54,105 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5295800300586563, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,105 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:54,126 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.450993
2023-07-02 10:33:54,126 [model] Computed derived parameters: {}
2023-07-02 10:33:54,126 [mcmc] New sample, #294:
Omega_m:0.31534, b1:0.5070958
2023-07-02 10:33:54,126 [model] Posterior to be computed for parameters {'Omega_m': 0.2785021323362605, 'b1': 0.5487810815873548}
2023-07-02 10:33:54,126 [prior] Evaluating prior at array([0.27850213, 0.54878108])
2023-07-02 10:33:54,127 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:54,127 [model] Got input parameters: {'Omega_m': 0.2785021323362605, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5487810815873548, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,127 [classy] Got parameters {'Omega_m': 0.2785021323362605, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:54,127 [classy] Computing new state
2023-07-02 10:33:54,127 [classy] Setting parameters: {'Omega_m': 0.2785021323362605, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:54,171 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.5584082539434}
2023-07-02 10:33:54,171 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:54,173 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0774851
2023-07-02 10:33:54,173 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5487810815873548, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,173 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:54,192 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.69579
2023-07-02 10:33:54,193 [model] Computed derived parameters: {}
2023-07-02 10:33:54,193 [model] Posterior to be computed for parameters {'Omega_m': 0.3153399666680525, 'b1': 0.5119890209164148}
2023-07-02 10:33:54,193 [prior] Evaluating prior at array([0.31533997, 0.51198902])
2023-07-02 10:33:54,193 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:54,193 [model] Got input parameters: {'Omega_m': 0.3153399666680525, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5119890209164148, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,193 [classy] Got parameters {'Omega_m': 0.3153399666680525, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:54,193 [classy] Re-using computed results
2023-07-02 10:33:54,193 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.91785049146839}
2023-07-02 10:33:54,193 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:54,193 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5119890209164148, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,193 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:54,213 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.51636
2023-07-02 10:33:54,213 [model] Computed derived parameters: {}
2023-07-02 10:33:54,213 [mcmc] New sample, #295:
Omega_m:0.31534, b1:0.52958
2023-07-02 10:33:54,213 [model] Posterior to be computed for parameters {'Omega_m': 0.33270362042687757, 'b1': 0.5029385320210362}
2023-07-02 10:33:54,213 [prior] Evaluating prior at array([0.33270362, 0.50293853])
2023-07-02 10:33:54,213 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:54,213 [model] Got input parameters: {'Omega_m': 0.33270362042687757, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5029385320210362, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,213 [classy] Got parameters {'Omega_m': 0.33270362042687757, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:54,213 [classy] Computing new state
2023-07-02 10:33:54,213 [classy] Setting parameters: {'Omega_m': 0.33270362042687757, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:54,257 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.89474106101568}
2023-07-02 10:33:54,257 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:54,259 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0240647
2023-07-02 10:33:54,259 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5029385320210362, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,259 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:54,279 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.08507
2023-07-02 10:33:54,279 [model] Computed derived parameters: {}
2023-07-02 10:33:54,279 [model] Posterior to be computed for parameters {'Omega_m': 0.3153399666680525, 'b1': 0.5178938228650387}
2023-07-02 10:33:54,279 [prior] Evaluating prior at array([0.31533997, 0.51789382])
2023-07-02 10:33:54,279 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:54,279 [model] Got input parameters: {'Omega_m': 0.3153399666680525, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5178938228650387, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,279 [classy] Got parameters {'Omega_m': 0.3153399666680525, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:54,279 [classy] Re-using computed results
2023-07-02 10:33:54,279 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.91785049146839}
2023-07-02 10:33:54,279 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:54,279 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5178938228650387, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,279 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:54,298 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.0206
2023-07-02 10:33:54,298 [model] Computed derived parameters: {}
2023-07-02 10:33:54,298 [mcmc] New sample, #296:
Omega_m:0.31534, b1:0.511989
2023-07-02 10:33:54,299 [model] Posterior to be computed for parameters {'Omega_m': 0.3070165101603717, 'b1': 0.5222322732707112}
2023-07-02 10:33:54,299 [prior] Evaluating prior at array([0.30701651, 0.52223227])
2023-07-02 10:33:54,299 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:54,299 [model] Got input parameters: {'Omega_m': 0.3070165101603717, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5222322732707112, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,299 [classy] Got parameters {'Omega_m': 0.3070165101603717, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:54,299 [classy] Computing new state
2023-07-02 10:33:54,299 [classy] Setting parameters: {'Omega_m': 0.3070165101603717, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:54,343 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.92317361251105}
2023-07-02 10:33:54,343 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:54,345 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00206081
2023-07-02 10:33:54,345 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5222322732707112, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,345 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:54,364 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.39079
2023-07-02 10:33:54,365 [model] Computed derived parameters: {}
2023-07-02 10:33:54,365 [mcmc] New sample, #297:
Omega_m:0.31534, b1:0.5178938
2023-07-02 10:33:54,365 [model] Posterior to be computed for parameters {'Omega_m': 0.3070165101603717, 'b1': 0.5204710226153965}
2023-07-02 10:33:54,365 [prior] Evaluating prior at array([0.30701651, 0.52047102])
2023-07-02 10:33:54,365 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:54,365 [model] Got input parameters: {'Omega_m': 0.3070165101603717, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5204710226153965, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,365 [classy] Got parameters {'Omega_m': 0.3070165101603717, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:54,365 [classy] Re-using computed results
2023-07-02 10:33:54,365 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.92317361251105}
2023-07-02 10:33:54,365 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:54,365 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5204710226153965, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,365 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:54,384 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.45269
2023-07-02 10:33:54,385 [model] Computed derived parameters: {}
2023-07-02 10:33:54,385 [mcmc] New sample, #298:
Omega_m:0.3070165, b1:0.5222323
2023-07-02 10:33:54,385 [model] Posterior to be computed for parameters {'Omega_m': 0.30954623856111213, 'b1': 0.5191524476704434}
2023-07-02 10:33:54,385 [prior] Evaluating prior at array([0.30954624, 0.51915245])
2023-07-02 10:33:54,385 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:54,385 [model] Got input parameters: {'Omega_m': 0.30954623856111213, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5191524476704434, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,385 [classy] Got parameters {'Omega_m': 0.30954623856111213, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:54,385 [classy] Computing new state
2023-07-02 10:33:54,385 [classy] Setting parameters: {'Omega_m': 0.30954623856111213, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:54,429 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.61510711278612}
2023-07-02 10:33:54,429 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:54,430 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000735535
2023-07-02 10:33:54,430 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5191524476704434, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,430 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:54,450 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.52887
2023-07-02 10:33:54,450 [model] Computed derived parameters: {}
2023-07-02 10:33:54,450 [mcmc] New sample, #299:
Omega_m:0.3070165, b1:0.520471
2023-07-02 10:33:54,450 [model] Posterior to be computed for parameters {'Omega_m': 0.30954623856111213, 'b1': 0.523789316435705}
2023-07-02 10:33:54,450 [prior] Evaluating prior at array([0.30954624, 0.52378932])
2023-07-02 10:33:54,450 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:54,450 [model] Got input parameters: {'Omega_m': 0.30954623856111213, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.523789316435705, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,450 [classy] Got parameters {'Omega_m': 0.30954623856111213, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:54,450 [classy] Re-using computed results
2023-07-02 10:33:54,450 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.61510711278612}
2023-07-02 10:33:54,450 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:54,450 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.523789316435705, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,451 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:54,471 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.24507
2023-07-02 10:33:54,471 [model] Computed derived parameters: {}
2023-07-02 10:33:54,471 [mcmc] New sample, #300:
Omega_m:0.3095462, b1:0.5191524
2023-07-02 10:33:54,471 [model] Posterior to be computed for parameters {'Omega_m': 0.3039649582293687, 'b1': 0.5266984573553555}
2023-07-02 10:33:54,471 [prior] Evaluating prior at array([0.30396496, 0.52669846])
2023-07-02 10:33:54,471 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:54,471 [model] Got input parameters: {'Omega_m': 0.3039649582293687, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5266984573553555, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,471 [classy] Got parameters {'Omega_m': 0.3039649582293687, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:54,471 [classy] Computing new state
2023-07-02 10:33:54,471 [classy] Setting parameters: {'Omega_m': 0.3039649582293687, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:54,515 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2977695222496}
2023-07-02 10:33:54,515 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:54,517 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00474881
2023-07-02 10:33:54,517 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5266984573553555, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,517 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:54,536 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.07693
2023-07-02 10:33:54,536 [model] Computed derived parameters: {}
2023-07-02 10:33:54,536 [mcmc] New sample, #301:
Omega_m:0.3095462, b1:0.5237893
2023-07-02 10:33:54,536 [model] Posterior to be computed for parameters {'Omega_m': 0.3039649582293687, 'b1': 0.5182656511445677}
2023-07-02 10:33:54,536 [prior] Evaluating prior at array([0.30396496, 0.51826565])
2023-07-02 10:33:54,536 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:54,536 [model] Got input parameters: {'Omega_m': 0.3039649582293687, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5182656511445677, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,536 [classy] Got parameters {'Omega_m': 0.3039649582293687, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:54,536 [classy] Re-using computed results
2023-07-02 10:33:54,536 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2977695222496}
2023-07-02 10:33:54,536 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:54,536 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5182656511445677, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,536 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:54,556 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.17182
2023-07-02 10:33:54,556 [model] Computed derived parameters: {}
2023-07-02 10:33:54,556 [mcmc] New sample, #302:
Omega_m:0.303965, b1:0.5266985
2023-07-02 10:33:54,556 [model] Posterior to be computed for parameters {'Omega_m': 0.2973586174868648, 'b1': 0.5217090861703744}
2023-07-02 10:33:54,556 [prior] Evaluating prior at array([0.29735862, 0.52170909])
2023-07-02 10:33:54,556 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:54,556 [model] Got input parameters: {'Omega_m': 0.2973586174868648, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5217090861703744, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,556 [classy] Got parameters {'Omega_m': 0.2973586174868648, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:54,556 [classy] Computing new state
2023-07-02 10:33:54,556 [classy] Setting parameters: {'Omega_m': 0.2973586174868648, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:54,600 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.12021896301644}
2023-07-02 10:33:54,600 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:54,602 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0147773
2023-07-02 10:33:54,602 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5217090861703744, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,602 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:54,622 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.701275
2023-07-02 10:33:54,622 [model] Computed derived parameters: {}
2023-07-02 10:33:54,622 [model] Posterior to be computed for parameters {'Omega_m': 0.3039649582293687, 'b1': 0.5241807035549605}
2023-07-02 10:33:54,622 [prior] Evaluating prior at array([0.30396496, 0.5241807 ])
2023-07-02 10:33:54,622 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:54,622 [model] Got input parameters: {'Omega_m': 0.3039649582293687, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5241807035549605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,622 [classy] Got parameters {'Omega_m': 0.3039649582293687, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:54,622 [classy] Re-using computed results
2023-07-02 10:33:54,622 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2977695222496}
2023-07-02 10:33:54,622 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:54,622 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5241807035549605, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,622 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:54,641 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.14529
2023-07-02 10:33:54,641 [model] Computed derived parameters: {}
2023-07-02 10:33:54,642 [mcmc] New sample, #303:
Omega_m:0.303965, b1:0.5182657
2023-07-02 10:33:54,642 [model] Posterior to be computed for parameters {'Omega_m': 0.30068701129068304, 'b1': 0.5258892738121356}
2023-07-02 10:33:54,642 [prior] Evaluating prior at array([0.30068701, 0.52588927])
2023-07-02 10:33:54,642 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:54,642 [model] Got input parameters: {'Omega_m': 0.30068701129068304, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5258892738121356, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,642 [classy] Got parameters {'Omega_m': 0.30068701129068304, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:54,642 [classy] Computing new state
2023-07-02 10:33:54,642 [classy] Setting parameters: {'Omega_m': 0.30068701129068304, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:54,687 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.70385351979522}
2023-07-02 10:33:54,687 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:54,688 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00899303
2023-07-02 10:33:54,689 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5258892738121356, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,689 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:54,708 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.6689
2023-07-02 10:33:54,708 [model] Computed derived parameters: {}
2023-07-02 10:33:54,708 [mcmc] New sample, #304:
Omega_m:0.303965, b1:0.5241807
2023-07-02 10:33:54,708 [model] Posterior to be computed for parameters {'Omega_m': 0.30068701129068304, 'b1': 0.5210397981399907}
2023-07-02 10:33:54,708 [prior] Evaluating prior at array([0.30068701, 0.5210398 ])
2023-07-02 10:33:54,708 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:54,708 [model] Got input parameters: {'Omega_m': 0.30068701129068304, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5210397981399907, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,708 [classy] Got parameters {'Omega_m': 0.30068701129068304, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:54,708 [classy] Re-using computed results
2023-07-02 10:33:54,708 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.70385351979522}
2023-07-02 10:33:54,708 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:54,708 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5210397981399907, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,708 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:54,728 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.59522
2023-07-02 10:33:54,728 [model] Computed derived parameters: {}
2023-07-02 10:33:54,728 [mcmc] New sample, #305:
Omega_m:0.300687, b1:0.5258893
2023-07-02 10:33:54,728 [model] Posterior to be computed for parameters {'Omega_m': 0.281742076150132, 'b1': 0.5309145012119798}
2023-07-02 10:33:54,728 [prior] Evaluating prior at array([0.28174208, 0.5309145 ])
2023-07-02 10:33:54,728 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:54,728 [model] Got input parameters: {'Omega_m': 0.281742076150132, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5309145012119798, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,728 [classy] Got parameters {'Omega_m': 0.281742076150132, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:54,729 [classy] Computing new state
2023-07-02 10:33:54,729 [classy] Setting parameters: {'Omega_m': 0.281742076150132, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:54,772 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.12953556129196}
2023-07-02 10:33:54,772 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:54,774 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0629091
2023-07-02 10:33:54,774 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5309145012119798, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,774 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:54,794 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.54089
2023-07-02 10:33:54,794 [model] Computed derived parameters: {}
2023-07-02 10:33:54,794 [model] Posterior to be computed for parameters {'Omega_m': 0.30068701129068304, 'b1': 0.5295228180476761}
2023-07-02 10:33:54,794 [prior] Evaluating prior at array([0.30068701, 0.52952282])
2023-07-02 10:33:54,794 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:54,794 [model] Got input parameters: {'Omega_m': 0.30068701129068304, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5295228180476761, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,794 [classy] Got parameters {'Omega_m': 0.30068701129068304, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:54,794 [classy] Re-using computed results
2023-07-02 10:33:54,794 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.70385351979522}
2023-07-02 10:33:54,794 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:54,794 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5295228180476761, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,794 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:54,814 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.64241
2023-07-02 10:33:54,814 [model] Computed derived parameters: {}
2023-07-02 10:33:54,814 [mcmc] New sample, #306:
Omega_m:0.300687, b1:0.5210398
2023-07-02 10:33:54,814 [model] Posterior to be computed for parameters {'Omega_m': 0.28175254188471854, 'b1': 0.5393920660457521}
2023-07-02 10:33:54,814 [prior] Evaluating prior at array([0.28175254, 0.53939207])
2023-07-02 10:33:54,814 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:54,814 [model] Got input parameters: {'Omega_m': 0.28175254188471854, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5393920660457521, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,814 [classy] Got parameters {'Omega_m': 0.28175254188471854, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:54,814 [classy] Computing new state
2023-07-02 10:33:54,814 [classy] Setting parameters: {'Omega_m': 0.28175254188471854, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:54,858 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.1281553621312}
2023-07-02 10:33:54,858 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:54,860 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0628645
2023-07-02 10:33:54,860 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5393920660457521, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,860 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:54,880 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.45313
2023-07-02 10:33:54,880 [model] Computed derived parameters: {}
2023-07-02 10:33:54,880 [model] Posterior to be computed for parameters {'Omega_m': 0.30068701129068304, 'b1': 0.5339742265212681}
2023-07-02 10:33:54,880 [prior] Evaluating prior at array([0.30068701, 0.53397423])
2023-07-02 10:33:54,880 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:54,880 [model] Got input parameters: {'Omega_m': 0.30068701129068304, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5339742265212681, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,880 [classy] Got parameters {'Omega_m': 0.30068701129068304, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:54,880 [classy] Re-using computed results
2023-07-02 10:33:54,880 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.70385351979522}
2023-07-02 10:33:54,880 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:54,880 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5339742265212681, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,880 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:54,900 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.51335
2023-07-02 10:33:54,900 [model] Computed derived parameters: {}
2023-07-02 10:33:54,900 [mcmc] New sample, #307:
Omega_m:0.300687, b1:0.5295228
2023-07-02 10:33:54,900 [model] Posterior to be computed for parameters {'Omega_m': 0.30970707221789884, 'b1': 0.5292726837243834}
2023-07-02 10:33:54,900 [prior] Evaluating prior at array([0.30970707, 0.52927268])
2023-07-02 10:33:54,900 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:54,900 [model] Got input parameters: {'Omega_m': 0.30970707221789884, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5292726837243834, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,900 [classy] Got parameters {'Omega_m': 0.30970707221789884, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:54,900 [classy] Computing new state
2023-07-02 10:33:54,900 [classy] Setting parameters: {'Omega_m': 0.30970707221789884, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:54,944 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.595597667278}
2023-07-02 10:33:54,944 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:54,945 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000678569
2023-07-02 10:33:54,946 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5292726837243834, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,946 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:54,965 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.73376
2023-07-02 10:33:54,965 [model] Computed derived parameters: {}
2023-07-02 10:33:54,965 [mcmc] New sample, #308:
Omega_m:0.300687, b1:0.5339742
2023-07-02 10:33:54,966 [model] Posterior to be computed for parameters {'Omega_m': 0.30970707221789884, 'b1': 0.539721980067217}
2023-07-02 10:33:54,966 [prior] Evaluating prior at array([0.30970707, 0.53972198])
2023-07-02 10:33:54,966 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:54,966 [model] Got input parameters: {'Omega_m': 0.30970707221789884, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.539721980067217, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,966 [classy] Got parameters {'Omega_m': 0.30970707221789884, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:54,966 [classy] Re-using computed results
2023-07-02 10:33:54,966 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.595597667278}
2023-07-02 10:33:54,966 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:54,966 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.539721980067217, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,966 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:54,985 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.306318
2023-07-02 10:33:54,986 [model] Computed derived parameters: {}
2023-07-02 10:33:54,986 [model] Posterior to be computed for parameters {'Omega_m': 0.3012228524191634, 'b1': 0.5336949290732564}
2023-07-02 10:33:54,986 [prior] Evaluating prior at array([0.30122285, 0.53369493])
2023-07-02 10:33:54,986 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:54,986 [model] Got input parameters: {'Omega_m': 0.3012228524191634, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5336949290732564, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:54,986 [classy] Got parameters {'Omega_m': 0.3012228524191634, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:54,986 [classy] Computing new state
2023-07-02 10:33:54,986 [classy] Setting parameters: {'Omega_m': 0.3012228524191634, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:55,030 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.63720674656156}
2023-07-02 10:33:55,030 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:55,032 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00820173
2023-07-02 10:33:55,032 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5336949290732564, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:55,032 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:55,051 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.57727
2023-07-02 10:33:55,051 [model] Computed derived parameters: {}
2023-07-02 10:33:55,051 [mcmc] New sample, #309:
Omega_m:0.3097071, b1:0.5292727
2023-07-02 10:33:55,051 [model] Posterior to be computed for parameters {'Omega_m': 0.3012228524191634, 'b1': 0.5366407623995789}
2023-07-02 10:33:55,051 [prior] Evaluating prior at array([0.30122285, 0.53664076])
2023-07-02 10:33:55,051 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:55,051 [model] Got input parameters: {'Omega_m': 0.3012228524191634, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5366407623995789, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:55,051 [classy] Got parameters {'Omega_m': 0.3012228524191634, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:55,052 [classy] Re-using computed results
2023-07-02 10:33:55,052 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.63720674656156}
2023-07-02 10:33:55,052 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:55,052 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5366407623995789, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:55,052 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:55,072 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.42146
2023-07-02 10:33:55,072 [model] Computed derived parameters: {}
2023-07-02 10:33:55,072 [mcmc] New sample, #310:
Omega_m:0.3012229, b1:0.5336949
2023-07-02 10:33:55,072 [model] Posterior to be computed for parameters {'Omega_m': 0.30372827428679394, 'b1': 0.5353348567931795}
2023-07-02 10:33:55,072 [prior] Evaluating prior at array([0.30372827, 0.53533486])
2023-07-02 10:33:55,072 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:55,072 [model] Got input parameters: {'Omega_m': 0.30372827428679394, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5353348567931795, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:55,072 [classy] Got parameters {'Omega_m': 0.30372827428679394, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:55,072 [classy] Computing new state
2023-07-02 10:33:55,072 [classy] Setting parameters: {'Omega_m': 0.30372827428679394, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:55,116 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.32696375338492}
2023-07-02 10:33:55,117 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:55,118 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00500783
2023-07-02 10:33:55,118 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5353348567931795, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:55,119 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:55,140 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.58137
2023-07-02 10:33:55,140 [model] Computed derived parameters: {}
2023-07-02 10:33:55,140 [mcmc] New sample, #311:
Omega_m:0.3012229, b1:0.5366408
2023-07-02 10:33:55,140 [model] Posterior to be computed for parameters {'Omega_m': 0.30372827428679394, 'b1': 0.5466944657130917}
2023-07-02 10:33:55,140 [prior] Evaluating prior at array([0.30372827, 0.54669447])
2023-07-02 10:33:55,140 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:55,140 [model] Got input parameters: {'Omega_m': 0.30372827428679394, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5466944657130917, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:55,140 [classy] Got parameters {'Omega_m': 0.30372827428679394, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:55,140 [classy] Re-using computed results
2023-07-02 10:33:55,140 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.32696375338492}
2023-07-02 10:33:55,140 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:55,140 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5466944657130917, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:55,141 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:55,160 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.319833
2023-07-02 10:33:55,160 [model] Computed derived parameters: {}
2023-07-02 10:33:55,160 [mcmc] New sample, #312:
Omega_m:0.3037283, b1:0.5353349
2023-07-02 10:33:55,160 [model] Posterior to be computed for parameters {'Omega_m': 0.29223895052786464, 'b1': 0.5526830668761821}
2023-07-02 10:33:55,160 [prior] Evaluating prior at array([0.29223895, 0.55268307])
2023-07-02 10:33:55,160 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:55,160 [model] Got input parameters: {'Omega_m': 0.29223895052786464, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5526830668761821, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:55,160 [classy] Got parameters {'Omega_m': 0.29223895052786464, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:55,160 [classy] Computing new state
2023-07-02 10:33:55,160 [classy] Setting parameters: {'Omega_m': 0.29223895052786464, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:55,204 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.76865251727406}
2023-07-02 10:33:55,204 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:55,206 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0266607
2023-07-02 10:33:55,206 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5526830668761821, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:55,206 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:55,226 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.65835
2023-07-02 10:33:55,226 [model] Computed derived parameters: {}
2023-07-02 10:33:55,226 [mcmc] New sample, #313:
Omega_m:0.3037283, b1:0.5466945
2023-07-02 10:33:55,226 [model] Posterior to be computed for parameters {'Omega_m': 0.29223895052786464, 'b1': 0.5112531706938764}
2023-07-02 10:33:55,226 [prior] Evaluating prior at array([0.29223895, 0.51125317])
2023-07-02 10:33:55,226 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:55,226 [model] Got input parameters: {'Omega_m': 0.29223895052786464, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5112531706938764, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:55,226 [classy] Got parameters {'Omega_m': 0.29223895052786464, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:55,226 [classy] Re-using computed results
2023-07-02 10:33:55,226 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.76865251727406}
2023-07-02 10:33:55,226 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:55,226 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5112531706938764, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:55,226 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:55,245 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.69637
2023-07-02 10:33:55,245 [model] Computed derived parameters: {}
2023-07-02 10:33:55,246 [model] Posterior to be computed for parameters {'Omega_m': 0.3042367539641901, 'b1': 0.546429429924097}
2023-07-02 10:33:55,246 [prior] Evaluating prior at array([0.30423675, 0.54642943])
2023-07-02 10:33:55,246 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:55,246 [model] Got input parameters: {'Omega_m': 0.3042367539641901, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.546429429924097, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:55,246 [classy] Got parameters {'Omega_m': 0.3042367539641901, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:55,246 [classy] Computing new state
2023-07-02 10:33:55,246 [classy] Setting parameters: {'Omega_m': 0.3042367539641901, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:55,290 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.26427327932936}
2023-07-02 10:33:55,290 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:55,292 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00446046
2023-07-02 10:33:55,292 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.546429429924097, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:55,292 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:55,311 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.291939
2023-07-02 10:33:55,311 [model] Computed derived parameters: {}
2023-07-02 10:33:55,311 [mcmc] New sample, #314:
Omega_m:0.292239, b1:0.5526831
2023-07-02 10:33:55,312 [model] Posterior to be computed for parameters {'Omega_m': 0.3042367539641901, 'b1': 0.55796251155958}
2023-07-02 10:33:55,312 [prior] Evaluating prior at array([0.30423675, 0.55796251])
2023-07-02 10:33:55,312 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:55,312 [model] Got input parameters: {'Omega_m': 0.3042367539641901, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.55796251155958, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:55,312 [classy] Got parameters {'Omega_m': 0.3042367539641901, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:55,312 [classy] Re-using computed results
2023-07-02 10:33:55,312 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.26427327932936}
2023-07-02 10:33:55,312 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:55,312 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.55796251155958, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:55,312 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:55,332 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.79386
2023-07-02 10:33:55,332 [model] Computed derived parameters: {}
2023-07-02 10:33:55,332 [model] Posterior to be computed for parameters {'Omega_m': 0.30051760779687337, 'b1': 0.5483679672593329}
2023-07-02 10:33:55,332 [prior] Evaluating prior at array([0.30051761, 0.54836797])
2023-07-02 10:33:55,332 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:55,332 [model] Got input parameters: {'Omega_m': 0.30051760779687337, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5483679672593329, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:55,332 [classy] Got parameters {'Omega_m': 0.30051760779687337, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:55,332 [classy] Computing new state
2023-07-02 10:33:55,332 [classy] Setting parameters: {'Omega_m': 0.30051760779687337, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:55,376 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.72494291031444}
2023-07-02 10:33:55,376 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:55,378 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00925114
2023-07-02 10:33:55,378 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5483679672593329, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:55,378 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:55,397 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.358181
2023-07-02 10:33:55,397 [model] Computed derived parameters: {}
2023-07-02 10:33:55,397 [mcmc] New sample, #315:
Omega_m:0.3042368, b1:0.5464294
2023-07-02 10:33:55,398 [model] Posterior to be computed for parameters {'Omega_m': 0.30051760779687337, 'b1': 0.5517616534781751}
2023-07-02 10:33:55,398 [prior] Evaluating prior at array([0.30051761, 0.55176165])
2023-07-02 10:33:55,398 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:55,398 [model] Got input parameters: {'Omega_m': 0.30051760779687337, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5517616534781751, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:55,398 [classy] Got parameters {'Omega_m': 0.30051760779687337, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:55,398 [classy] Re-using computed results
2023-07-02 10:33:55,398 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.72494291031444}
2023-07-02 10:33:55,398 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:55,398 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5517616534781751, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:55,398 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:55,417 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.0790448
2023-07-02 10:33:55,417 [model] Computed derived parameters: {}
2023-07-02 10:33:55,417 [mcmc] New sample, #316:
Omega_m:0.3005176, b1:0.548368
2023-07-02 10:33:55,417 [model] Posterior to be computed for parameters {'Omega_m': 0.315347735905794, 'b1': 0.544031718774852}
2023-07-02 10:33:55,418 [prior] Evaluating prior at array([0.31534774, 0.54403172])
2023-07-02 10:33:55,418 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:55,418 [model] Got input parameters: {'Omega_m': 0.315347735905794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.544031718774852, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:55,418 [classy] Got parameters {'Omega_m': 0.315347735905794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:55,418 [classy] Computing new state
2023-07-02 10:33:55,418 [classy] Setting parameters: {'Omega_m': 0.315347735905794, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:55,462 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.91692184847935}
2023-07-02 10:33:55,462 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:55,463 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000701826
2023-07-02 10:33:55,463 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.544031718774852, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:55,463 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:55,483 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.60892
2023-07-02 10:33:55,483 [model] Computed derived parameters: {}
2023-07-02 10:33:55,483 [model] Posterior to be computed for parameters {'Omega_m': 0.30051760779687337, 'b1': 0.5578986133933553}
2023-07-02 10:33:55,483 [prior] Evaluating prior at array([0.30051761, 0.55789861])
2023-07-02 10:33:55,484 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:55,484 [model] Got input parameters: {'Omega_m': 0.30051760779687337, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5578986133933553, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:55,484 [classy] Got parameters {'Omega_m': 0.30051760779687337, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:55,484 [classy] Re-using computed results
2023-07-02 10:33:55,484 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.72494291031444}
2023-07-02 10:33:55,484 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:55,484 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5578986133933553, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:55,484 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:55,503 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.03738
2023-07-02 10:33:55,503 [model] Computed derived parameters: {}
2023-07-02 10:33:55,503 [model] Posterior to be computed for parameters {'Omega_m': 0.28880168848417864, 'b1': 0.5578683634547434}
2023-07-02 10:33:55,503 [prior] Evaluating prior at array([0.28880169, 0.55786836])
2023-07-02 10:33:55,504 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:55,504 [model] Got input parameters: {'Omega_m': 0.28880168848417864, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5578683634547434, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:55,504 [classy] Got parameters {'Omega_m': 0.28880168848417864, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:55,504 [classy] Computing new state
2023-07-02 10:33:55,504 [classy] Setting parameters: {'Omega_m': 0.28880168848417864, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:55,547 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.2095494159752}
2023-07-02 10:33:55,548 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:55,549 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0367318
2023-07-02 10:33:55,549 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5578683634547434, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:55,549 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:55,569 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.71142
2023-07-02 10:33:55,569 [model] Computed derived parameters: {}
2023-07-02 10:33:55,569 [mcmc] New sample, #317:
Omega_m:0.3005176, b1:0.5517617
2023-07-02 10:33:55,569 [model] Posterior to be computed for parameters {'Omega_m': 0.28880168848417864, 'b1': 0.5920363514992295}
2023-07-02 10:33:55,569 [prior] Evaluating prior at array([0.28880169, 0.59203635])
2023-07-02 10:33:55,569 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:55,569 [model] Got input parameters: {'Omega_m': 0.28880168848417864, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5920363514992295, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:55,569 [classy] Got parameters {'Omega_m': 0.28880168848417864, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:55,569 [classy] Re-using computed results
2023-07-02 10:33:55,569 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.2095494159752}
2023-07-02 10:33:55,569 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:55,569 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5920363514992295, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:55,569 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:55,589 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.78404
2023-07-02 10:33:55,589 [model] Computed derived parameters: {}
2023-07-02 10:33:55,589 [model] Posterior to be computed for parameters {'Omega_m': 0.3155220090936905, 'b1': 0.5439408820434977}
2023-07-02 10:33:55,589 [prior] Evaluating prior at array([0.31552201, 0.54394088])
2023-07-02 10:33:55,590 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:55,590 [model] Got input parameters: {'Omega_m': 0.3155220090936905, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5439408820434977, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:55,590 [classy] Got parameters {'Omega_m': 0.3155220090936905, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:55,590 [classy] Computing new state
2023-07-02 10:33:55,590 [classy] Setting parameters: {'Omega_m': 0.3155220090936905, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:55,633 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.8961298863702}
2023-07-02 10:33:55,634 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:55,635 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000764182
2023-07-02 10:33:55,635 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5439408820434977, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:55,635 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:55,655 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.66808
2023-07-02 10:33:55,655 [model] Computed derived parameters: {}
2023-07-02 10:33:55,655 [model] Posterior to be computed for parameters {'Omega_m': 0.28880168848417864, 'b1': 0.5427010827084139}
2023-07-02 10:33:55,655 [prior] Evaluating prior at array([0.28880169, 0.54270108])
2023-07-02 10:33:55,655 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:55,655 [model] Got input parameters: {'Omega_m': 0.28880168848417864, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5427010827084139, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:55,655 [classy] Got parameters {'Omega_m': 0.28880168848417864, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:55,655 [classy] Re-using computed results
2023-07-02 10:33:55,655 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.2095494159752}
2023-07-02 10:33:55,655 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:55,655 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5427010827084139, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:55,655 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:55,675 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.51765
2023-07-02 10:33:55,676 [model] Computed derived parameters: {}
2023-07-02 10:33:55,676 [mcmc] New sample, #318:
Omega_m:0.2888017, b1:0.5578684
2023-07-02 10:33:55,676 [model] Posterior to be computed for parameters {'Omega_m': 0.31252902824332013, 'b1': 0.5303336381607568}
2023-07-02 10:33:55,676 [prior] Evaluating prior at array([0.31252903, 0.53033364])
2023-07-02 10:33:55,676 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:55,676 [model] Got input parameters: {'Omega_m': 0.31252902824332013, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5303336381607568, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:55,676 [classy] Got parameters {'Omega_m': 0.31252902824332013, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:55,676 [classy] Computing new state
2023-07-02 10:33:55,676 [classy] Setting parameters: {'Omega_m': 0.31252902824332013, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:55,719 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.25470681884383}
2023-07-02 10:33:55,719 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:55,721 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000202495
2023-07-02 10:33:55,721 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5303336381607568, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:55,721 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:55,741 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.09256
2023-07-02 10:33:55,741 [model] Computed derived parameters: {}
2023-07-02 10:33:55,741 [mcmc] New sample, #319:
Omega_m:0.2888017, b1:0.5427011
2023-07-02 10:33:55,741 [model] Posterior to be computed for parameters {'Omega_m': 0.31252902824332013, 'b1': 0.5349969847240742}
2023-07-02 10:33:55,741 [prior] Evaluating prior at array([0.31252903, 0.53499698])
2023-07-02 10:33:55,741 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:55,741 [model] Got input parameters: {'Omega_m': 0.31252902824332013, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5349969847240742, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:55,741 [classy] Got parameters {'Omega_m': 0.31252902824332013, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:55,742 [classy] Re-using computed results
2023-07-02 10:33:55,742 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.25470681884383}
2023-07-02 10:33:55,742 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:55,742 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5349969847240742, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:55,742 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:55,761 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.364768
2023-07-02 10:33:55,761 [model] Computed derived parameters: {}
2023-07-02 10:33:55,761 [mcmc] New sample, #320:
Omega_m:0.312529, b1:0.5303336
2023-07-02 10:33:55,761 [mcmc] Learn + convergence test @ 320 samples accepted.
2023-07-02 10:33:55,761 [mcmc] Ready to check convergence and learn a new proposal covmat
2023-07-02 10:33:55,766 [mcmc] - Acceptance rate: 0.368
2023-07-02 10:33:55,766 [mcmc] - Condition number = 5.35886
2023-07-02 10:33:55,767 [mcmc] - Eigenvalues = array([0.02628313, 0.14084773])
2023-07-02 10:33:55,767 [mcmc] - Convergence of means: R-1 = 0.140848 after 256 accepted steps
2023-07-02 10:33:55,767 [mcmc] - Updated covariance matrix of proposal pdf.
2023-07-02 10:33:55,767 [mcmc] array([[ 5.83849144e-05, -8.25621038e-05],
[-8.25621038e-05, 2.49234300e-04]])
2023-07-02 10:33:55,777 [mcmc] Dumped checkpoint and progress info, and current covmat.
2023-07-02 10:33:55,777 [model] Posterior to be computed for parameters {'Omega_m': 0.3117870232033208, 'b1': 0.5360462540036722}
2023-07-02 10:33:55,777 [prior] Evaluating prior at array([0.31178702, 0.53604625])
2023-07-02 10:33:55,777 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:55,778 [model] Got input parameters: {'Omega_m': 0.3117870232033208, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5360462540036722, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:55,778 [classy] Got parameters {'Omega_m': 0.3117870232033208, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:55,778 [classy] Computing new state
2023-07-02 10:33:55,778 [classy] Setting parameters: {'Omega_m': 0.3117870232033208, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:55,822 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.34407591018703}
2023-07-02 10:33:55,822 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:55,824 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000232208
2023-07-02 10:33:55,824 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5360462540036722, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:55,824 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:55,845 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.39113
2023-07-02 10:33:55,845 [model] Computed derived parameters: {}
2023-07-02 10:33:55,845 [mcmc] New sample, #321:
Omega_m:0.312529, b1:0.534997
2023-07-02 10:33:55,845 [model] Posterior to be computed for parameters {'Omega_m': 0.3117870232033208, 'b1': 0.4810306514882249}
2023-07-02 10:33:55,846 [prior] Evaluating prior at array([0.31178702, 0.48103065])
2023-07-02 10:33:55,846 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:55,846 [model] Got input parameters: {'Omega_m': 0.3117870232033208, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4810306514882249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:55,846 [classy] Got parameters {'Omega_m': 0.3117870232033208, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:55,846 [classy] Re-using computed results
2023-07-02 10:33:55,846 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.34407591018703}
2023-07-02 10:33:55,846 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:55,846 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4810306514882249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:55,846 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:55,867 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.20285
2023-07-02 10:33:55,867 [model] Computed derived parameters: {}
2023-07-02 10:33:55,867 [mcmc] New sample, #322:
Omega_m:0.311787, b1:0.5360463
2023-07-02 10:33:55,867 [model] Posterior to be computed for parameters {'Omega_m': 0.28176681452625685, 'b1': 0.5234822266581105}
2023-07-02 10:33:55,867 [prior] Evaluating prior at array([0.28176681, 0.52348223])
2023-07-02 10:33:55,867 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:55,867 [model] Got input parameters: {'Omega_m': 0.28176681452625685, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5234822266581105, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:55,867 [classy] Got parameters {'Omega_m': 0.28176681452625685, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:55,868 [classy] Computing new state
2023-07-02 10:33:55,868 [classy] Setting parameters: {'Omega_m': 0.28176681452625685, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:55,913 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.12627460344692}
2023-07-02 10:33:55,913 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:55,915 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0628039
2023-07-02 10:33:55,915 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5234822266581105, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:55,915 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:55,936 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.7502
2023-07-02 10:33:55,936 [model] Computed derived parameters: {}
2023-07-02 10:33:55,936 [model] Posterior to be computed for parameters {'Omega_m': 0.3117870232033208, 'b1': 0.49669222638878036}
2023-07-02 10:33:55,936 [prior] Evaluating prior at array([0.31178702, 0.49669223])
2023-07-02 10:33:55,936 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:55,936 [model] Got input parameters: {'Omega_m': 0.3117870232033208, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49669222638878036, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:55,936 [classy] Got parameters {'Omega_m': 0.3117870232033208, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:55,936 [classy] Re-using computed results
2023-07-02 10:33:55,936 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.34407591018703}
2023-07-02 10:33:55,936 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:55,936 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49669222638878036, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:55,936 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:55,956 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.62086
2023-07-02 10:33:55,956 [model] Computed derived parameters: {}
2023-07-02 10:33:55,956 [mcmc] New sample, #323:
Omega_m:0.311787, b1:0.4810307
2023-07-02 10:33:55,956 [model] Posterior to be computed for parameters {'Omega_m': 0.2993613265823718, 'b1': 0.51426340318561}
2023-07-02 10:33:55,956 [prior] Evaluating prior at array([0.29936133, 0.5142634 ])
2023-07-02 10:33:55,956 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:55,956 [model] Got input parameters: {'Omega_m': 0.2993613265823718, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.51426340318561, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:55,956 [classy] Got parameters {'Omega_m': 0.2993613265823718, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:55,956 [classy] Computing new state
2023-07-02 10:33:55,956 [classy] Setting parameters: {'Omega_m': 0.2993613265823718, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:56,001 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.86920239485838}
2023-07-02 10:33:56,001 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:56,003 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0111168
2023-07-02 10:33:56,003 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.51426340318561, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,003 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:56,024 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.872277
2023-07-02 10:33:56,024 [model] Computed derived parameters: {}
2023-07-02 10:33:56,024 [model] Posterior to be computed for parameters {'Omega_m': 0.3117870232033208, 'b1': 0.47886160727360505}
2023-07-02 10:33:56,024 [prior] Evaluating prior at array([0.31178702, 0.47886161])
2023-07-02 10:33:56,025 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:56,025 [model] Got input parameters: {'Omega_m': 0.3117870232033208, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47886160727360505, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,025 [classy] Got parameters {'Omega_m': 0.3117870232033208, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:56,025 [classy] Re-using computed results
2023-07-02 10:33:56,025 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.34407591018703}
2023-07-02 10:33:56,025 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:56,025 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47886160727360505, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,025 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:56,045 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.908878
2023-07-02 10:33:56,045 [model] Computed derived parameters: {}
2023-07-02 10:33:56,045 [model] Posterior to be computed for parameters {'Omega_m': 0.319497004670791, 'b1': 0.48578954208882735}
2023-07-02 10:33:56,045 [prior] Evaluating prior at array([0.319497 , 0.48578954])
2023-07-02 10:33:56,046 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:56,046 [model] Got input parameters: {'Omega_m': 0.319497004670791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48578954208882735, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,046 [classy] Got parameters {'Omega_m': 0.319497004670791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:56,046 [classy] Computing new state
2023-07-02 10:33:56,046 [classy] Setting parameters: {'Omega_m': 0.319497004670791, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:56,092 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.42459552908923}
2023-07-02 10:33:56,092 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:56,094 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00316618
2023-07-02 10:33:56,094 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48578954208882735, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,094 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:56,113 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.71434
2023-07-02 10:33:56,113 [model] Computed derived parameters: {}
2023-07-02 10:33:56,113 [mcmc] New sample, #324:
Omega_m:0.311787, b1:0.4966922
2023-07-02 10:33:56,113 [model] Posterior to be computed for parameters {'Omega_m': 0.319497004670791, 'b1': 0.492789554306529}
2023-07-02 10:33:56,113 [prior] Evaluating prior at array([0.319497 , 0.49278955])
2023-07-02 10:33:56,114 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:56,114 [model] Got input parameters: {'Omega_m': 0.319497004670791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.492789554306529, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,114 [classy] Got parameters {'Omega_m': 0.319497004670791, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:56,114 [classy] Re-using computed results
2023-07-02 10:33:56,114 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.42459552908923}
2023-07-02 10:33:56,114 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:56,114 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.492789554306529, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,114 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:56,136 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.82341
2023-07-02 10:33:56,136 [model] Computed derived parameters: {}
2023-07-02 10:33:56,137 [mcmc] New sample, #325:
Omega_m:0.319497, b1:0.4857895
2023-07-02 10:33:56,137 [model] Posterior to be computed for parameters {'Omega_m': 0.32871300043954627, 'b1': 0.4797572152794664}
2023-07-02 10:33:56,137 [prior] Evaluating prior at array([0.328713 , 0.47975722])
2023-07-02 10:33:56,137 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:56,137 [model] Got input parameters: {'Omega_m': 0.32871300043954627, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4797572152794664, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,137 [classy] Got parameters {'Omega_m': 0.32871300043954627, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:56,137 [classy] Computing new state
2023-07-02 10:33:56,137 [classy] Setting parameters: {'Omega_m': 0.32871300043954627, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:56,181 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.35115292776115}
2023-07-02 10:33:56,181 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:56,183 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0157236
2023-07-02 10:33:56,183 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4797572152794664, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,183 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:56,202 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.9058
2023-07-02 10:33:56,202 [model] Computed derived parameters: {}
2023-07-02 10:33:56,202 [mcmc] New sample, #326:
Omega_m:0.319497, b1:0.4927896
2023-07-02 10:33:56,202 [model] Posterior to be computed for parameters {'Omega_m': 0.32871300043954627, 'b1': 0.5012586211377089}
2023-07-02 10:33:56,202 [prior] Evaluating prior at array([0.328713 , 0.50125862])
2023-07-02 10:33:56,203 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:56,203 [model] Got input parameters: {'Omega_m': 0.32871300043954627, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5012586211377089, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,203 [classy] Got parameters {'Omega_m': 0.32871300043954627, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:56,203 [classy] Re-using computed results
2023-07-02 10:33:56,203 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.35115292776115}
2023-07-02 10:33:56,203 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:56,203 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5012586211377089, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,203 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:56,222 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.094407
2023-07-02 10:33:56,222 [model] Computed derived parameters: {}
2023-07-02 10:33:56,222 [mcmc] New sample, #327:
Omega_m:0.328713, b1:0.4797572
2023-07-02 10:33:56,222 [model] Posterior to be computed for parameters {'Omega_m': 0.3543550335157322, 'b1': 0.4649982238049591}
2023-07-02 10:33:56,222 [prior] Evaluating prior at array([0.35435503, 0.46499822])
2023-07-02 10:33:56,222 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:56,222 [model] Got input parameters: {'Omega_m': 0.3543550335157322, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4649982238049591, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,222 [classy] Got parameters {'Omega_m': 0.3543550335157322, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:56,222 [classy] Computing new state
2023-07-02 10:33:56,222 [classy] Setting parameters: {'Omega_m': 0.3543550335157322, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:56,266 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.5018683268413}
2023-07-02 10:33:56,266 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:56,268 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0974575
2023-07-02 10:33:56,268 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4649982238049591, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,268 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:56,288 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.05577
2023-07-02 10:33:56,288 [model] Computed derived parameters: {}
2023-07-02 10:33:56,288 [model] Posterior to be computed for parameters {'Omega_m': 0.32871300043954627, 'b1': 0.5488506990338249}
2023-07-02 10:33:56,288 [prior] Evaluating prior at array([0.328713 , 0.5488507])
2023-07-02 10:33:56,288 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:56,288 [model] Got input parameters: {'Omega_m': 0.32871300043954627, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5488506990338249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,288 [classy] Got parameters {'Omega_m': 0.32871300043954627, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:56,288 [classy] Re-using computed results
2023-07-02 10:33:56,288 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.35115292776115}
2023-07-02 10:33:56,288 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:56,288 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5488506990338249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,289 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:56,308 [fs_likelihood.fslikelihood] Computed log-likelihood = -13.8567
2023-07-02 10:33:56,308 [model] Computed derived parameters: {}
2023-07-02 10:33:56,308 [model] Posterior to be computed for parameters {'Omega_m': 0.3356905369090545, 'b1': 0.4913916872625205}
2023-07-02 10:33:56,308 [prior] Evaluating prior at array([0.33569054, 0.49139169])
2023-07-02 10:33:56,308 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:56,308 [model] Got input parameters: {'Omega_m': 0.3356905369090545, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4913916872625205, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,308 [classy] Got parameters {'Omega_m': 0.3356905369090545, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:56,308 [classy] Computing new state
2023-07-02 10:33:56,308 [classy] Setting parameters: {'Omega_m': 0.3356905369090545, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:56,352 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.5563543638445}
2023-07-02 10:33:56,352 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:56,354 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0314115
2023-07-02 10:33:56,354 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4913916872625205, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,354 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:56,373 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.53935
2023-07-02 10:33:56,374 [model] Computed derived parameters: {}
2023-07-02 10:33:56,374 [model] Posterior to be computed for parameters {'Omega_m': 0.32871300043954627, 'b1': 0.505162320511507}
2023-07-02 10:33:56,374 [prior] Evaluating prior at array([0.328713 , 0.50516232])
2023-07-02 10:33:56,374 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:56,374 [model] Got input parameters: {'Omega_m': 0.32871300043954627, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.505162320511507, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,374 [classy] Got parameters {'Omega_m': 0.32871300043954627, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:56,374 [classy] Re-using computed results
2023-07-02 10:33:56,374 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.35115292776115}
2023-07-02 10:33:56,374 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:56,374 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.505162320511507, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,374 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:56,394 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.521766
2023-07-02 10:33:56,394 [model] Computed derived parameters: {}
2023-07-02 10:33:56,394 [model] Posterior to be computed for parameters {'Omega_m': 0.31485673550860915, 'b1': 0.5208527644901814}
2023-07-02 10:33:56,394 [prior] Evaluating prior at array([0.31485674, 0.52085276])
2023-07-02 10:33:56,394 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:56,394 [model] Got input parameters: {'Omega_m': 0.31485673550860915, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5208527644901814, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,395 [classy] Got parameters {'Omega_m': 0.31485673550860915, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:56,395 [classy] Computing new state
2023-07-02 10:33:56,395 [classy] Setting parameters: {'Omega_m': 0.31485673550860915, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:56,438 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.97556538597232}
2023-07-02 10:33:56,438 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:56,440 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000545684
2023-07-02 10:33:56,440 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5208527644901814, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,440 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:56,459 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.7987
2023-07-02 10:33:56,459 [model] Computed derived parameters: {}
2023-07-02 10:33:56,459 [mcmc] New sample, #328:
Omega_m:0.328713, b1:0.5012586
2023-07-02 10:33:56,459 [model] Posterior to be computed for parameters {'Omega_m': 0.31485673550860915, 'b1': 0.5260896995663333}
2023-07-02 10:33:56,460 [prior] Evaluating prior at array([0.31485674, 0.5260897 ])
2023-07-02 10:33:56,460 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:56,460 [model] Got input parameters: {'Omega_m': 0.31485673550860915, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5260896995663333, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,460 [classy] Got parameters {'Omega_m': 0.31485673550860915, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:56,460 [classy] Re-using computed results
2023-07-02 10:33:56,460 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.97556538597232}
2023-07-02 10:33:56,460 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:56,460 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5260896995663333, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,460 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:56,480 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.13063
2023-07-02 10:33:56,480 [model] Computed derived parameters: {}
2023-07-02 10:33:56,480 [mcmc] New sample, #329:
Omega_m:0.3148567, b1:0.5208528
2023-07-02 10:33:56,480 [model] Posterior to be computed for parameters {'Omega_m': 0.2948052999495469, 'b1': 0.5544444333077412}
2023-07-02 10:33:56,480 [prior] Evaluating prior at array([0.2948053 , 0.55444443])
2023-07-02 10:33:56,480 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:56,480 [model] Got input parameters: {'Omega_m': 0.2948052999495469, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5544444333077412, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,480 [classy] Got parameters {'Omega_m': 0.2948052999495469, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:56,480 [classy] Computing new state
2023-07-02 10:33:56,480 [classy] Setting parameters: {'Omega_m': 0.2948052999495469, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:56,524 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.4423876450121}
2023-07-02 10:33:56,524 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:56,526 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0202447
2023-07-02 10:33:56,526 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5544444333077412, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,526 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:56,546 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.43539
2023-07-02 10:33:56,546 [model] Computed derived parameters: {}
2023-07-02 10:33:56,546 [model] Posterior to be computed for parameters {'Omega_m': 0.31485673550860915, 'b1': 0.5484704507863232}
2023-07-02 10:33:56,546 [prior] Evaluating prior at array([0.31485674, 0.54847045])
2023-07-02 10:33:56,546 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:56,546 [model] Got input parameters: {'Omega_m': 0.31485673550860915, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5484704507863232, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,546 [classy] Got parameters {'Omega_m': 0.31485673550860915, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:56,546 [classy] Re-using computed results
2023-07-02 10:33:56,546 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.97556538597232}
2023-07-02 10:33:56,547 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:56,547 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5484704507863232, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,547 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:56,566 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.55068
2023-07-02 10:33:56,566 [model] Computed derived parameters: {}
2023-07-02 10:33:56,566 [model] Posterior to be computed for parameters {'Omega_m': 0.35670040994647145, 'b1': 0.4669185622204331}
2023-07-02 10:33:56,566 [prior] Evaluating prior at array([0.35670041, 0.46691856])
2023-07-02 10:33:56,566 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:56,566 [model] Got input parameters: {'Omega_m': 0.35670040994647145, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4669185622204331, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,566 [classy] Got parameters {'Omega_m': 0.35670040994647145, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:56,566 [classy] Computing new state
2023-07-02 10:33:56,566 [classy] Setting parameters: {'Omega_m': 0.35670040994647145, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:56,610 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.25075137877093}
2023-07-02 10:33:56,610 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:56,612 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.108076
2023-07-02 10:33:56,612 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4669185622204331, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,612 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:56,631 [fs_likelihood.fslikelihood] Computed log-likelihood = -10.2832
2023-07-02 10:33:56,632 [model] Computed derived parameters: {}
2023-07-02 10:33:56,632 [model] Posterior to be computed for parameters {'Omega_m': 0.31485673550860915, 'b1': 0.5057755739912578}
2023-07-02 10:33:56,632 [prior] Evaluating prior at array([0.31485674, 0.50577557])
2023-07-02 10:33:56,632 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:56,632 [model] Got input parameters: {'Omega_m': 0.31485673550860915, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5057755739912578, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,632 [classy] Got parameters {'Omega_m': 0.31485673550860915, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:56,632 [classy] Re-using computed results
2023-07-02 10:33:56,632 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.97556538597232}
2023-07-02 10:33:56,632 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:56,632 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5057755739912578, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,632 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:56,652 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.85375
2023-07-02 10:33:56,652 [model] Computed derived parameters: {}
2023-07-02 10:33:56,652 [mcmc] New sample, #330:
Omega_m:0.3148567, b1:0.5260897
2023-07-02 10:33:56,652 [model] Posterior to be computed for parameters {'Omega_m': 0.2924593008111374, 'b1': 0.5374477849642203}
2023-07-02 10:33:56,652 [prior] Evaluating prior at array([0.2924593 , 0.53744778])
2023-07-02 10:33:56,652 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:56,652 [model] Got input parameters: {'Omega_m': 0.2924593008111374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5374477849642203, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,652 [classy] Got parameters {'Omega_m': 0.2924593008111374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:56,652 [classy] Computing new state
2023-07-02 10:33:56,652 [classy] Setting parameters: {'Omega_m': 0.2924593008111374, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:56,696 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.740542692545}
2023-07-02 10:33:56,696 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:56,698 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0260732
2023-07-02 10:33:56,698 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5374477849642203, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,698 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:56,717 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.307959
2023-07-02 10:33:56,718 [model] Computed derived parameters: {}
2023-07-02 10:33:56,718 [mcmc] New sample, #331:
Omega_m:0.3148567, b1:0.5057756
2023-07-02 10:33:56,718 [model] Posterior to be computed for parameters {'Omega_m': 0.2924593008111374, 'b1': 0.5168254349462263}
2023-07-02 10:33:56,718 [prior] Evaluating prior at array([0.2924593 , 0.51682543])
2023-07-02 10:33:56,718 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:56,718 [model] Got input parameters: {'Omega_m': 0.2924593008111374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5168254349462263, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,718 [classy] Got parameters {'Omega_m': 0.2924593008111374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:56,718 [classy] Re-using computed results
2023-07-02 10:33:56,718 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.740542692545}
2023-07-02 10:33:56,718 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:56,718 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5168254349462263, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,718 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:56,738 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.80425
2023-07-02 10:33:56,738 [model] Computed derived parameters: {}
2023-07-02 10:33:56,738 [mcmc] New sample, #332:
Omega_m:0.2924593, b1:0.5374478
2023-07-02 10:33:56,739 [model] Posterior to be computed for parameters {'Omega_m': 0.2783700799838957, 'b1': 0.5367490012167613}
2023-07-02 10:33:56,739 [prior] Evaluating prior at array([0.27837008, 0.536749 ])
2023-07-02 10:33:56,739 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:56,739 [model] Got input parameters: {'Omega_m': 0.2783700799838957, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5367490012167613, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,739 [classy] Got parameters {'Omega_m': 0.2783700799838957, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:56,739 [classy] Computing new state
2023-07-02 10:33:56,739 [classy] Setting parameters: {'Omega_m': 0.2783700799838957, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:56,783 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.5759755620221}
2023-07-02 10:33:56,783 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:56,784 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0781141
2023-07-02 10:33:56,784 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5367490012167613, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,784 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:56,804 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.22381
2023-07-02 10:33:56,804 [model] Computed derived parameters: {}
2023-07-02 10:33:56,804 [model] Posterior to be computed for parameters {'Omega_m': 0.2924593008111374, 'b1': 0.6169558330306847}
2023-07-02 10:33:56,804 [prior] Evaluating prior at array([0.2924593 , 0.61695583])
2023-07-02 10:33:56,805 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:56,805 [model] Got input parameters: {'Omega_m': 0.2924593008111374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6169558330306847, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,805 [classy] Got parameters {'Omega_m': 0.2924593008111374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:56,805 [classy] Re-using computed results
2023-07-02 10:33:56,805 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.740542692545}
2023-07-02 10:33:56,805 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:56,805 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6169558330306847, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,805 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:56,824 [fs_likelihood.fslikelihood] Computed log-likelihood = -16.5143
2023-07-02 10:33:56,824 [model] Computed derived parameters: {}
2023-07-02 10:33:56,824 [model] Posterior to be computed for parameters {'Omega_m': 0.2718894070263659, 'b1': 0.5459133204314447}
2023-07-02 10:33:56,824 [prior] Evaluating prior at array([0.27188941, 0.54591332])
2023-07-02 10:33:56,824 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:56,824 [model] Got input parameters: {'Omega_m': 0.2718894070263659, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5459133204314447, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,824 [classy] Got parameters {'Omega_m': 0.2718894070263659, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:56,824 [classy] Computing new state
2023-07-02 10:33:56,824 [classy] Setting parameters: {'Omega_m': 0.2718894070263659, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:56,869 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.4470986127955}
2023-07-02 10:33:56,869 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:56,871 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.11246
2023-07-02 10:33:56,871 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5459133204314447, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,871 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:56,890 [fs_likelihood.fslikelihood] Computed log-likelihood = -12.3249
2023-07-02 10:33:56,891 [model] Computed derived parameters: {}
2023-07-02 10:33:56,891 [model] Posterior to be computed for parameters {'Omega_m': 0.2924593008111374, 'b1': 0.5069827720525667}
2023-07-02 10:33:56,891 [prior] Evaluating prior at array([0.2924593 , 0.50698277])
2023-07-02 10:33:56,891 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:56,891 [model] Got input parameters: {'Omega_m': 0.2924593008111374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5069827720525667, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,891 [classy] Got parameters {'Omega_m': 0.2924593008111374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:56,891 [classy] Re-using computed results
2023-07-02 10:33:56,891 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.740542692545}
2023-07-02 10:33:56,891 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:56,891 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5069827720525667, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,891 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:56,911 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.25973
2023-07-02 10:33:56,911 [model] Computed derived parameters: {}
2023-07-02 10:33:56,911 [mcmc] New sample, #333:
Omega_m:0.2924593, b1:0.5168254
2023-07-02 10:33:56,911 [model] Posterior to be computed for parameters {'Omega_m': 0.3093521914785011, 'b1': 0.4830945364404621}
2023-07-02 10:33:56,911 [prior] Evaluating prior at array([0.30935219, 0.48309454])
2023-07-02 10:33:56,911 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:56,911 [model] Got input parameters: {'Omega_m': 0.3093521914785011, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4830945364404621, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,911 [classy] Got parameters {'Omega_m': 0.3093521914785011, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:56,911 [classy] Computing new state
2023-07-02 10:33:56,911 [classy] Setting parameters: {'Omega_m': 0.3093521914785011, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:56,955 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.63865989616025}
2023-07-02 10:33:56,955 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:56,957 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000808593
2023-07-02 10:33:56,957 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4830945364404621, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,957 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:56,977 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.756472
2023-07-02 10:33:56,977 [model] Computed derived parameters: {}
2023-07-02 10:33:56,977 [mcmc] New sample, #334:
Omega_m:0.2924593, b1:0.5069828
2023-07-02 10:33:56,977 [model] Posterior to be computed for parameters {'Omega_m': 0.3093521914785011, 'b1': 0.46985935379866645}
2023-07-02 10:33:56,977 [prior] Evaluating prior at array([0.30935219, 0.46985935])
2023-07-02 10:33:56,977 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:56,977 [model] Got input parameters: {'Omega_m': 0.3093521914785011, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46985935379866645, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,977 [classy] Got parameters {'Omega_m': 0.3093521914785011, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:56,977 [classy] Re-using computed results
2023-07-02 10:33:56,977 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.63865989616025}
2023-07-02 10:33:56,977 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:56,977 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46985935379866645, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,977 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:56,997 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.54205
2023-07-02 10:33:56,997 [model] Computed derived parameters: {}
2023-07-02 10:33:56,997 [model] Posterior to be computed for parameters {'Omega_m': 0.29434259735560503, 'b1': 0.5043196025295068}
2023-07-02 10:33:56,997 [prior] Evaluating prior at array([0.2943426, 0.5043196])
2023-07-02 10:33:56,998 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:56,998 [model] Got input parameters: {'Omega_m': 0.29434259735560503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5043196025295068, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:56,998 [classy] Got parameters {'Omega_m': 0.29434259735560503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:56,998 [classy] Computing new state
2023-07-02 10:33:56,998 [classy] Setting parameters: {'Omega_m': 0.29434259735560503, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:57,043 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.5010298673712}
2023-07-02 10:33:57,043 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:57,045 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0213328
2023-07-02 10:33:57,045 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5043196025295068, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:57,045 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:57,064 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.60974
2023-07-02 10:33:57,064 [model] Computed derived parameters: {}
2023-07-02 10:33:57,064 [model] Posterior to be computed for parameters {'Omega_m': 0.3093521914785011, 'b1': 0.4694589962158406}
2023-07-02 10:33:57,064 [prior] Evaluating prior at array([0.30935219, 0.469459 ])
2023-07-02 10:33:57,065 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:57,065 [model] Got input parameters: {'Omega_m': 0.3093521914785011, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4694589962158406, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:57,065 [classy] Got parameters {'Omega_m': 0.3093521914785011, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:57,065 [classy] Re-using computed results
2023-07-02 10:33:57,065 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.63865989616025}
2023-07-02 10:33:57,065 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:57,065 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4694589962158406, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:57,065 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:57,084 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.62466
2023-07-02 10:33:57,084 [model] Computed derived parameters: {}
2023-07-02 10:33:57,084 [model] Posterior to be computed for parameters {'Omega_m': 0.30475123840662965, 'b1': 0.48960074388507907}
2023-07-02 10:33:57,085 [prior] Evaluating prior at array([0.30475124, 0.48960074])
2023-07-02 10:33:57,085 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:57,085 [model] Got input parameters: {'Omega_m': 0.30475123840662965, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48960074388507907, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:57,085 [classy] Got parameters {'Omega_m': 0.30475123840662965, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:57,085 [classy] Computing new state
2023-07-02 10:33:57,085 [classy] Setting parameters: {'Omega_m': 0.30475123840662965, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:57,129 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2009367594883}
2023-07-02 10:33:57,129 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:57,131 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00394095
2023-07-02 10:33:57,131 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48960074388507907, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:57,131 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:57,152 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.0527742
2023-07-02 10:33:57,152 [model] Computed derived parameters: {}
2023-07-02 10:33:57,152 [mcmc] New sample, #335:
Omega_m:0.3093522, b1:0.4830945
2023-07-02 10:33:57,152 [model] Posterior to be computed for parameters {'Omega_m': 0.30475123840662965, 'b1': 0.4666158906380616}
2023-07-02 10:33:57,152 [prior] Evaluating prior at array([0.30475124, 0.46661589])
2023-07-02 10:33:57,152 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:57,152 [model] Got input parameters: {'Omega_m': 0.30475123840662965, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4666158906380616, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:57,152 [classy] Got parameters {'Omega_m': 0.30475123840662965, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:57,152 [classy] Re-using computed results
2023-07-02 10:33:57,152 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2009367594883}
2023-07-02 10:33:57,152 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:57,152 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4666158906380616, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:57,152 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:57,172 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.65046
2023-07-02 10:33:57,172 [model] Computed derived parameters: {}
2023-07-02 10:33:57,172 [model] Posterior to be computed for parameters {'Omega_m': 0.29851669274326603, 'b1': 0.4984170145088265}
2023-07-02 10:33:57,172 [prior] Evaluating prior at array([0.29851669, 0.49841701])
2023-07-02 10:33:57,172 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:57,172 [model] Got input parameters: {'Omega_m': 0.29851669274326603, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4984170145088265, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:57,172 [classy] Got parameters {'Omega_m': 0.29851669274326603, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:57,172 [classy] Computing new state
2023-07-02 10:33:57,172 [classy] Setting parameters: {'Omega_m': 0.29851669274326603, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:57,216 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.97488737327072}
2023-07-02 10:33:57,216 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:57,218 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0125939
2023-07-02 10:33:57,218 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4984170145088265, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:57,218 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:57,237 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.35682
2023-07-02 10:33:57,238 [model] Computed derived parameters: {}
2023-07-02 10:33:57,238 [model] Posterior to be computed for parameters {'Omega_m': 0.30475123840662965, 'b1': 0.5187947111097473}
2023-07-02 10:33:57,238 [prior] Evaluating prior at array([0.30475124, 0.51879471])
2023-07-02 10:33:57,238 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:57,238 [model] Got input parameters: {'Omega_m': 0.30475123840662965, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5187947111097473, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:57,238 [classy] Got parameters {'Omega_m': 0.30475123840662965, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:57,238 [classy] Re-using computed results
2023-07-02 10:33:57,238 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2009367594883}
2023-07-02 10:33:57,238 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:57,238 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5187947111097473, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:57,238 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:57,258 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.28626
2023-07-02 10:33:57,258 [model] Computed derived parameters: {}
2023-07-02 10:33:57,258 [mcmc] New sample, #336:
Omega_m:0.3047512, b1:0.4896007
2023-07-02 10:33:57,258 [model] Posterior to be computed for parameters {'Omega_m': 0.3036967279463571, 'b1': 0.5202858942841632}
2023-07-02 10:33:57,258 [prior] Evaluating prior at array([0.30369673, 0.52028589])
2023-07-02 10:33:57,258 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:57,258 [model] Got input parameters: {'Omega_m': 0.3036967279463571, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5202858942841632, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:57,258 [classy] Got parameters {'Omega_m': 0.3036967279463571, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:57,258 [classy] Computing new state
2023-07-02 10:33:57,258 [classy] Setting parameters: {'Omega_m': 0.3036967279463571, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:57,302 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.33085649140878}
2023-07-02 10:33:57,302 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:57,304 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00504291
2023-07-02 10:33:57,304 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5202858942841632, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:57,304 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:57,323 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.14607
2023-07-02 10:33:57,323 [model] Computed derived parameters: {}
2023-07-02 10:33:57,323 [mcmc] New sample, #337:
Omega_m:0.3047512, b1:0.5187947
2023-07-02 10:33:57,323 [model] Posterior to be computed for parameters {'Omega_m': 0.3036967279463571, 'b1': 0.508255803699687}
2023-07-02 10:33:57,323 [prior] Evaluating prior at array([0.30369673, 0.5082558 ])
2023-07-02 10:33:57,323 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:57,323 [model] Got input parameters: {'Omega_m': 0.3036967279463571, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.508255803699687, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:57,323 [classy] Got parameters {'Omega_m': 0.3036967279463571, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:57,324 [classy] Re-using computed results
2023-07-02 10:33:57,324 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.33085649140878}
2023-07-02 10:33:57,324 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:57,324 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.508255803699687, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:57,324 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:57,343 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.72783
2023-07-02 10:33:57,343 [model] Computed derived parameters: {}
2023-07-02 10:33:57,343 [mcmc] New sample, #338:
Omega_m:0.3036967, b1:0.5202859
2023-07-02 10:33:57,343 [model] Posterior to be computed for parameters {'Omega_m': 0.27840067413578484, 'b1': 0.5440269517750643}
2023-07-02 10:33:57,343 [prior] Evaluating prior at array([0.27840067, 0.54402695])
2023-07-02 10:33:57,343 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:57,343 [model] Got input parameters: {'Omega_m': 0.27840067413578484, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5440269517750643, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:57,343 [classy] Got parameters {'Omega_m': 0.27840067413578484, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:57,343 [classy] Computing new state
2023-07-02 10:33:57,343 [classy] Setting parameters: {'Omega_m': 0.27840067413578484, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:57,387 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.57190649804704}
2023-07-02 10:33:57,387 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:57,389 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0779682
2023-07-02 10:33:57,389 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5440269517750643, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:57,389 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:57,408 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.24831
2023-07-02 10:33:57,408 [model] Computed derived parameters: {}
2023-07-02 10:33:57,409 [model] Posterior to be computed for parameters {'Omega_m': 0.3036967279463571, 'b1': 0.5004668867843597}
2023-07-02 10:33:57,409 [prior] Evaluating prior at array([0.30369673, 0.50046689])
2023-07-02 10:33:57,409 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:57,409 [model] Got input parameters: {'Omega_m': 0.3036967279463571, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5004668867843597, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:57,409 [classy] Got parameters {'Omega_m': 0.3036967279463571, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:57,409 [classy] Re-using computed results
2023-07-02 10:33:57,409 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.33085649140878}
2023-07-02 10:33:57,409 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:57,409 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5004668867843597, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:57,409 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:57,428 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.05921
2023-07-02 10:33:57,428 [model] Computed derived parameters: {}
2023-07-02 10:33:57,428 [model] Posterior to be computed for parameters {'Omega_m': 0.2977286925026266, 'b1': 0.5166952022388994}
2023-07-02 10:33:57,428 [prior] Evaluating prior at array([0.29772869, 0.5166952 ])
2023-07-02 10:33:57,428 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:57,428 [model] Got input parameters: {'Omega_m': 0.2977286925026266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5166952022388994, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:57,429 [classy] Got parameters {'Omega_m': 0.2977286925026266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:57,429 [classy] Computing new state
2023-07-02 10:33:57,429 [classy] Setting parameters: {'Omega_m': 0.2977286925026266, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:57,472 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.07372260836118}
2023-07-02 10:33:57,473 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:57,474 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0140596
2023-07-02 10:33:57,474 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5166952022388994, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:57,474 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:57,493 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.493463
2023-07-02 10:33:57,494 [model] Computed derived parameters: {}
2023-07-02 10:33:57,494 [model] Posterior to be computed for parameters {'Omega_m': 0.3036967279463571, 'b1': 0.5249174652095655}
2023-07-02 10:33:57,494 [prior] Evaluating prior at array([0.30369673, 0.52491747])
2023-07-02 10:33:57,494 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:57,494 [model] Got input parameters: {'Omega_m': 0.3036967279463571, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5249174652095655, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:57,494 [classy] Got parameters {'Omega_m': 0.3036967279463571, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:57,494 [classy] Re-using computed results
2023-07-02 10:33:57,494 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.33085649140878}
2023-07-02 10:33:57,494 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:57,494 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5249174652095655, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:57,494 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:57,514 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.10325
2023-07-02 10:33:57,514 [model] Computed derived parameters: {}
2023-07-02 10:33:57,514 [mcmc] New sample, #339:
Omega_m:0.3036967, b1:0.5082558
2023-07-02 10:33:57,514 [model] Posterior to be computed for parameters {'Omega_m': 0.27941781513620356, 'b1': 0.5592502742613158}
2023-07-02 10:33:57,514 [prior] Evaluating prior at array([0.27941782, 0.55925027])
2023-07-02 10:33:57,514 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:57,514 [model] Got input parameters: {'Omega_m': 0.27941781513620356, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5592502742613158, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:57,514 [classy] Got parameters {'Omega_m': 0.27941781513620356, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:57,514 [classy] Computing new state
2023-07-02 10:33:57,514 [classy] Setting parameters: {'Omega_m': 0.27941781513620356, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:57,558 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.43676876012066}
2023-07-02 10:33:57,558 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:57,560 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0731982
2023-07-02 10:33:57,560 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5592502742613158, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:57,560 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:57,579 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.51244
2023-07-02 10:33:57,579 [model] Computed derived parameters: {}
2023-07-02 10:33:57,579 [model] Posterior to be computed for parameters {'Omega_m': 0.3036967279463571, 'b1': 0.5323495960847019}
2023-07-02 10:33:57,579 [prior] Evaluating prior at array([0.30369673, 0.5323496 ])
2023-07-02 10:33:57,580 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:57,580 [model] Got input parameters: {'Omega_m': 0.3036967279463571, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5323495960847019, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:57,580 [classy] Got parameters {'Omega_m': 0.3036967279463571, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:57,580 [classy] Re-using computed results
2023-07-02 10:33:57,580 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.33085649140878}
2023-07-02 10:33:57,580 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:57,580 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5323495960847019, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:57,580 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:57,599 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.79196
2023-07-02 10:33:57,599 [model] Computed derived parameters: {}
2023-07-02 10:33:57,599 [model] Posterior to be computed for parameters {'Omega_m': 0.3164564435048646, 'b1': 0.506873952254501}
2023-07-02 10:33:57,599 [prior] Evaluating prior at array([0.31645644, 0.50687395])
2023-07-02 10:33:57,600 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:57,600 [model] Got input parameters: {'Omega_m': 0.3164564435048646, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.506873952254501, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:57,600 [classy] Got parameters {'Omega_m': 0.3164564435048646, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:57,600 [classy] Computing new state
2023-07-02 10:33:57,600 [classy] Setting parameters: {'Omega_m': 0.3164564435048646, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:57,643 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.78481102943462}
2023-07-02 10:33:57,643 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:57,645 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00116058
2023-07-02 10:33:57,645 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.506873952254501, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:57,645 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:57,665 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.68868
2023-07-02 10:33:57,665 [model] Computed derived parameters: {}
2023-07-02 10:33:57,665 [mcmc] New sample, #340:
Omega_m:0.3036967, b1:0.5249175
2023-07-02 10:33:57,665 [model] Posterior to be computed for parameters {'Omega_m': 0.3164564435048646, 'b1': 0.5181945269301252}
2023-07-02 10:33:57,665 [prior] Evaluating prior at array([0.31645644, 0.51819453])
2023-07-02 10:33:57,665 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:57,665 [model] Got input parameters: {'Omega_m': 0.3164564435048646, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5181945269301252, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:57,666 [classy] Got parameters {'Omega_m': 0.3164564435048646, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:57,666 [classy] Re-using computed results
2023-07-02 10:33:57,666 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.78481102943462}
2023-07-02 10:33:57,666 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:57,666 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5181945269301252, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:57,666 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:57,685 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.76077
2023-07-02 10:33:57,686 [model] Computed derived parameters: {}
2023-07-02 10:33:57,686 [model] Posterior to be computed for parameters {'Omega_m': 0.33353294197643324, 'b1': 0.4827260768582154}
2023-07-02 10:33:57,686 [prior] Evaluating prior at array([0.33353294, 0.48272608])
2023-07-02 10:33:57,686 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:57,686 [model] Got input parameters: {'Omega_m': 0.33353294197643324, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4827260768582154, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:57,686 [classy] Got parameters {'Omega_m': 0.33353294197643324, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:57,686 [classy] Computing new state
2023-07-02 10:33:57,686 [classy] Setting parameters: {'Omega_m': 0.33353294197643324, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:57,730 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.80051424165774}
2023-07-02 10:33:57,730 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:57,732 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0260108
2023-07-02 10:33:57,732 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4827260768582154, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:57,732 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:57,751 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.466693
2023-07-02 10:33:57,751 [model] Computed derived parameters: {}
2023-07-02 10:33:57,751 [model] Posterior to be computed for parameters {'Omega_m': 0.3164564435048646, 'b1': 0.5562248129981515}
2023-07-02 10:33:57,751 [prior] Evaluating prior at array([0.31645644, 0.55622481])
2023-07-02 10:33:57,752 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:57,752 [model] Got input parameters: {'Omega_m': 0.3164564435048646, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5562248129981515, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:57,752 [classy] Got parameters {'Omega_m': 0.3164564435048646, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:57,752 [classy] Re-using computed results
2023-07-02 10:33:57,752 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.78481102943462}
2023-07-02 10:33:57,752 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:57,752 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5562248129981515, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:57,752 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:57,771 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.88263
2023-07-02 10:33:57,771 [model] Computed derived parameters: {}
2023-07-02 10:33:57,772 [model] Posterior to be computed for parameters {'Omega_m': 0.31640918084833974, 'b1': 0.5069407863740696}
2023-07-02 10:33:57,772 [prior] Evaluating prior at array([0.31640918, 0.50694079])
2023-07-02 10:33:57,772 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:57,772 [model] Got input parameters: {'Omega_m': 0.31640918084833974, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5069407863740696, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:57,772 [classy] Got parameters {'Omega_m': 0.31640918084833974, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:57,772 [classy] Computing new state
2023-07-02 10:33:57,772 [classy] Setting parameters: {'Omega_m': 0.31640918084833974, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:57,816 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.7904324880373}
2023-07-02 10:33:57,816 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:57,818 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00113805
2023-07-02 10:33:57,818 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5069407863740696, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:57,818 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:57,837 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.69029
2023-07-02 10:33:57,837 [model] Computed derived parameters: {}
2023-07-02 10:33:57,837 [mcmc] New sample, #341:
Omega_m:0.3164564, b1:0.506874
2023-07-02 10:33:57,837 [model] Posterior to be computed for parameters {'Omega_m': 0.31640918084833974, 'b1': 0.5073199169572127}
2023-07-02 10:33:57,837 [prior] Evaluating prior at array([0.31640918, 0.50731992])
2023-07-02 10:33:57,838 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:57,838 [model] Got input parameters: {'Omega_m': 0.31640918084833974, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5073199169572127, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:57,838 [classy] Got parameters {'Omega_m': 0.31640918084833974, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:57,838 [classy] Re-using computed results
2023-07-02 10:33:57,838 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.7904324880373}
2023-07-02 10:33:57,838 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:57,838 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5073199169572127, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:57,838 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:57,858 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.6709
2023-07-02 10:33:57,858 [model] Computed derived parameters: {}
2023-07-02 10:33:57,858 [mcmc] New sample, #342:
Omega_m:0.3164092, b1:0.5069408
2023-07-02 10:33:57,858 [model] Posterior to be computed for parameters {'Omega_m': 0.32195202798203837, 'b1': 0.49948177718001757}
2023-07-02 10:33:57,858 [prior] Evaluating prior at array([0.32195203, 0.49948178])
2023-07-02 10:33:57,858 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:57,858 [model] Got input parameters: {'Omega_m': 0.32195202798203837, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49948177718001757, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:57,859 [classy] Got parameters {'Omega_m': 0.32195202798203837, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:57,859 [classy] Computing new state
2023-07-02 10:33:57,859 [classy] Setting parameters: {'Omega_m': 0.32195202798203837, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:57,902 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.13596828734586}
2023-07-02 10:33:57,902 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:57,905 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00557209
2023-07-02 10:33:57,905 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49948177718001757, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:57,905 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:57,924 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.29797
2023-07-02 10:33:57,924 [model] Computed derived parameters: {}
2023-07-02 10:33:57,925 [mcmc] New sample, #343:
Omega_m:0.3164092, b1:0.5073199
2023-07-02 10:33:57,925 [model] Posterior to be computed for parameters {'Omega_m': 0.32195202798203837, 'b1': 0.5393403046853895}
2023-07-02 10:33:57,925 [prior] Evaluating prior at array([0.32195203, 0.5393403 ])
2023-07-02 10:33:57,925 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:57,925 [model] Got input parameters: {'Omega_m': 0.32195202798203837, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5393403046853895, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:57,925 [classy] Got parameters {'Omega_m': 0.32195202798203837, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:57,925 [classy] Re-using computed results
2023-07-02 10:33:57,925 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.13596828734586}
2023-07-02 10:33:57,925 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:57,925 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5393403046853895, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:57,925 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:57,944 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.93258
2023-07-02 10:33:57,944 [model] Computed derived parameters: {}
2023-07-02 10:33:57,944 [model] Posterior to be computed for parameters {'Omega_m': 0.3271694096315802, 'b1': 0.49210387812314904}
2023-07-02 10:33:57,945 [prior] Evaluating prior at array([0.32716941, 0.49210388])
2023-07-02 10:33:57,945 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:57,945 [model] Got input parameters: {'Omega_m': 0.3271694096315802, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49210387812314904, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:57,945 [classy] Got parameters {'Omega_m': 0.3271694096315802, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:57,945 [classy] Computing new state
2023-07-02 10:33:57,945 [classy] Setting parameters: {'Omega_m': 0.3271694096315802, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:57,989 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.5290514821312}
2023-07-02 10:33:57,989 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:57,990 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0129586
2023-07-02 10:33:57,991 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49210387812314904, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:57,991 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:58,011 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.63138
2023-07-02 10:33:58,011 [model] Computed derived parameters: {}
2023-07-02 10:33:58,011 [mcmc] New sample, #344:
Omega_m:0.321952, b1:0.4994818
2023-07-02 10:33:58,011 [model] Posterior to be computed for parameters {'Omega_m': 0.3271694096315802, 'b1': 0.512544607465576}
2023-07-02 10:33:58,011 [prior] Evaluating prior at array([0.32716941, 0.51254461])
2023-07-02 10:33:58,011 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:58,011 [model] Got input parameters: {'Omega_m': 0.3271694096315802, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.512544607465576, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,011 [classy] Got parameters {'Omega_m': 0.3271694096315802, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:58,011 [classy] Re-using computed results
2023-07-02 10:33:58,012 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.5290514821312}
2023-07-02 10:33:58,012 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:58,012 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.512544607465576, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,012 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:58,031 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.15347
2023-07-02 10:33:58,031 [model] Computed derived parameters: {}
2023-07-02 10:33:58,031 [model] Posterior to be computed for parameters {'Omega_m': 0.34450779123450037, 'b1': 0.4675856738075715}
2023-07-02 10:33:58,031 [prior] Evaluating prior at array([0.34450779, 0.46758567])
2023-07-02 10:33:58,031 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:58,031 [model] Got input parameters: {'Omega_m': 0.34450779123450037, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4675856738075715, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,031 [classy] Got parameters {'Omega_m': 0.34450779123450037, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:58,031 [classy] Computing new state
2023-07-02 10:33:58,032 [classy] Setting parameters: {'Omega_m': 0.34450779123450037, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:58,076 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.57309944634636}
2023-07-02 10:33:58,076 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:58,078 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0584099
2023-07-02 10:33:58,078 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4675856738075715, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,078 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:58,097 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.54067
2023-07-02 10:33:58,097 [model] Computed derived parameters: {}
2023-07-02 10:33:58,097 [model] Posterior to be computed for parameters {'Omega_m': 0.3271694096315802, 'b1': 0.4353646958261076}
2023-07-02 10:33:58,097 [prior] Evaluating prior at array([0.32716941, 0.4353647 ])
2023-07-02 10:33:58,098 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:58,098 [model] Got input parameters: {'Omega_m': 0.3271694096315802, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4353646958261076, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,098 [classy] Got parameters {'Omega_m': 0.3271694096315802, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:58,098 [classy] Re-using computed results
2023-07-02 10:33:58,098 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.5290514821312}
2023-07-02 10:33:58,098 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:58,098 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4353646958261076, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,098 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:58,118 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.64533
2023-07-02 10:33:58,118 [model] Computed derived parameters: {}
2023-07-02 10:33:58,118 [model] Posterior to be computed for parameters {'Omega_m': 0.34512785825255005, 'b1': 0.4667088370770122}
2023-07-02 10:33:58,118 [prior] Evaluating prior at array([0.34512786, 0.46670884])
2023-07-02 10:33:58,119 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:58,119 [model] Got input parameters: {'Omega_m': 0.34512785825255005, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4667088370770122, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,119 [classy] Got parameters {'Omega_m': 0.34512785825255005, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:58,119 [classy] Computing new state
2023-07-02 10:33:58,119 [classy] Setting parameters: {'Omega_m': 0.34512785825255005, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:58,163 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.50482570702775}
2023-07-02 10:33:58,164 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:58,165 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0605977
2023-07-02 10:33:58,166 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4667088370770122, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,166 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:58,185 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.74016
2023-07-02 10:33:58,185 [model] Computed derived parameters: {}
2023-07-02 10:33:58,185 [mcmc] New sample, #345:
Omega_m:0.3271694, b1:0.4921039
2023-07-02 10:33:58,185 [model] Posterior to be computed for parameters {'Omega_m': 0.34512785825255005, 'b1': 0.4622165594146393}
2023-07-02 10:33:58,185 [prior] Evaluating prior at array([0.34512786, 0.46221656])
2023-07-02 10:33:58,185 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:58,185 [model] Got input parameters: {'Omega_m': 0.34512785825255005, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4622165594146393, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,185 [classy] Got parameters {'Omega_m': 0.34512785825255005, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:58,186 [classy] Re-using computed results
2023-07-02 10:33:58,186 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.50482570702775}
2023-07-02 10:33:58,186 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:58,186 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4622165594146393, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,186 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:58,205 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.26434
2023-07-02 10:33:58,205 [model] Computed derived parameters: {}
2023-07-02 10:33:58,205 [mcmc] New sample, #346:
Omega_m:0.3451279, b1:0.4667088
2023-07-02 10:33:58,205 [model] Posterior to be computed for parameters {'Omega_m': 0.3561250594681581, 'b1': 0.44666541787912345}
2023-07-02 10:33:58,205 [prior] Evaluating prior at array([0.35612506, 0.44666542])
2023-07-02 10:33:58,205 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:58,205 [model] Got input parameters: {'Omega_m': 0.3561250594681581, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44666541787912345, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,205 [classy] Got parameters {'Omega_m': 0.3561250594681581, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:58,205 [classy] Computing new state
2023-07-02 10:33:58,205 [classy] Setting parameters: {'Omega_m': 0.3561250594681581, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:58,249 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.31221153355764}
2023-07-02 10:33:58,249 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:58,251 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.105425
2023-07-02 10:33:58,251 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44666541787912345, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,251 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:58,271 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.19044
2023-07-02 10:33:58,271 [model] Computed derived parameters: {}
2023-07-02 10:33:58,271 [model] Posterior to be computed for parameters {'Omega_m': 0.34512785825255005, 'b1': 0.4969898077929139}
2023-07-02 10:33:58,271 [prior] Evaluating prior at array([0.34512786, 0.49698981])
2023-07-02 10:33:58,271 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:58,271 [model] Got input parameters: {'Omega_m': 0.34512785825255005, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4969898077929139, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,271 [classy] Got parameters {'Omega_m': 0.34512785825255005, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:58,271 [classy] Re-using computed results
2023-07-02 10:33:58,272 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.50482570702775}
2023-07-02 10:33:58,272 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:58,272 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4969898077929139, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,272 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:58,291 [fs_likelihood.fslikelihood] Computed log-likelihood = -9.12811
2023-07-02 10:33:58,291 [model] Computed derived parameters: {}
2023-07-02 10:33:58,291 [model] Posterior to be computed for parameters {'Omega_m': 0.3490782393808513, 'b1': 0.4566303257138088}
2023-07-02 10:33:58,291 [prior] Evaluating prior at array([0.34907824, 0.45663033])
2023-07-02 10:33:58,292 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:58,292 [model] Got input parameters: {'Omega_m': 0.3490782393808513, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4566303257138088, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,292 [classy] Got parameters {'Omega_m': 0.3490782393808513, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:58,292 [classy] Computing new state
2023-07-02 10:33:58,292 [classy] Setting parameters: {'Omega_m': 0.3490782393808513, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:58,335 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.0724723665007}
2023-07-02 10:33:58,335 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:58,337 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0754014
2023-07-02 10:33:58,337 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4566303257138088, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,337 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:58,357 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.56747
2023-07-02 10:33:58,357 [model] Computed derived parameters: {}
2023-07-02 10:33:58,357 [model] Posterior to be computed for parameters {'Omega_m': 0.34512785825255005, 'b1': 0.44654270464853485}
2023-07-02 10:33:58,357 [prior] Evaluating prior at array([0.34512786, 0.4465427 ])
2023-07-02 10:33:58,357 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:58,357 [model] Got input parameters: {'Omega_m': 0.34512785825255005, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44654270464853485, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,357 [classy] Got parameters {'Omega_m': 0.34512785825255005, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:58,357 [classy] Re-using computed results
2023-07-02 10:33:58,357 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.50482570702775}
2023-07-02 10:33:58,357 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:58,357 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44654270464853485, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,357 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:58,377 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.51246
2023-07-02 10:33:58,377 [model] Computed derived parameters: {}
2023-07-02 10:33:58,377 [mcmc] New sample, #347:
Omega_m:0.3451279, b1:0.4622166
2023-07-02 10:33:58,377 [model] Posterior to be computed for parameters {'Omega_m': 0.3238976969857947, 'b1': 0.4765642743377901}
2023-07-02 10:33:58,377 [prior] Evaluating prior at array([0.3238977 , 0.47656427])
2023-07-02 10:33:58,378 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:58,378 [model] Got input parameters: {'Omega_m': 0.3238976969857947, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4765642743377901, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,378 [classy] Got parameters {'Omega_m': 0.3238976969857947, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:58,378 [classy] Computing new state
2023-07-02 10:33:58,378 [classy] Setting parameters: {'Omega_m': 0.3238976969857947, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:58,422 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.90861184879094}
2023-07-02 10:33:58,422 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:58,423 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00796908
2023-07-02 10:33:58,424 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4765642743377901, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,424 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:58,443 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.35853
2023-07-02 10:33:58,443 [model] Computed derived parameters: {}
2023-07-02 10:33:58,443 [mcmc] New sample, #348:
Omega_m:0.3451279, b1:0.4465427
2023-07-02 10:33:58,443 [model] Posterior to be computed for parameters {'Omega_m': 0.3238976969857947, 'b1': 0.4871919984567674}
2023-07-02 10:33:58,443 [prior] Evaluating prior at array([0.3238977, 0.487192 ])
2023-07-02 10:33:58,443 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:58,443 [model] Got input parameters: {'Omega_m': 0.3238976969857947, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4871919984567674, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,443 [classy] Got parameters {'Omega_m': 0.3238976969857947, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:58,443 [classy] Re-using computed results
2023-07-02 10:33:58,443 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.90861184879094}
2023-07-02 10:33:58,443 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:58,443 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4871919984567674, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,444 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:58,463 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.49165
2023-07-02 10:33:58,463 [model] Computed derived parameters: {}
2023-07-02 10:33:58,463 [mcmc] New sample, #349:
Omega_m:0.3238977, b1:0.4765643
2023-07-02 10:33:58,463 [model] Posterior to be computed for parameters {'Omega_m': 0.3536620607430115, 'b1': 0.44510221357167157}
2023-07-02 10:33:58,463 [prior] Evaluating prior at array([0.35366206, 0.44510221])
2023-07-02 10:33:58,463 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:58,463 [model] Got input parameters: {'Omega_m': 0.3536620607430115, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44510221357167157, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,463 [classy] Got parameters {'Omega_m': 0.3536620607430115, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:58,464 [classy] Computing new state
2023-07-02 10:33:58,464 [classy] Setting parameters: {'Omega_m': 0.3536620607430115, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:58,507 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.57635805199703}
2023-07-02 10:33:58,507 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:58,509 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.094415
2023-07-02 10:33:58,509 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44510221357167157, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,509 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:58,529 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.73921
2023-07-02 10:33:58,529 [model] Computed derived parameters: {}
2023-07-02 10:33:58,529 [model] Posterior to be computed for parameters {'Omega_m': 0.3238976969857947, 'b1': 0.5181795097611104}
2023-07-02 10:33:58,529 [prior] Evaluating prior at array([0.3238977 , 0.51817951])
2023-07-02 10:33:58,529 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:58,529 [model] Got input parameters: {'Omega_m': 0.3238976969857947, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5181795097611104, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,529 [classy] Got parameters {'Omega_m': 0.3238976969857947, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:58,529 [classy] Re-using computed results
2023-07-02 10:33:58,529 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.90861184879094}
2023-07-02 10:33:58,529 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:58,529 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5181795097611104, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,529 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:58,548 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.730424
2023-07-02 10:33:58,548 [model] Computed derived parameters: {}
2023-07-02 10:33:58,548 [model] Posterior to be computed for parameters {'Omega_m': 0.32669430903771113, 'b1': 0.4832373095330477}
2023-07-02 10:33:58,548 [prior] Evaluating prior at array([0.32669431, 0.48323731])
2023-07-02 10:33:58,549 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:58,549 [model] Got input parameters: {'Omega_m': 0.32669430903771113, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4832373095330477, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,549 [classy] Got parameters {'Omega_m': 0.32669430903771113, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:58,549 [classy] Computing new state
2023-07-02 10:33:58,549 [classy] Setting parameters: {'Omega_m': 0.32669430903771113, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:58,593 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.58395680004216}
2023-07-02 10:33:58,593 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:58,594 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0121603
2023-07-02 10:33:58,595 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4832373095330477, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,595 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:58,614 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.17213
2023-07-02 10:33:58,614 [model] Computed derived parameters: {}
2023-07-02 10:33:58,614 [mcmc] New sample, #350:
Omega_m:0.3238977, b1:0.487192
2023-07-02 10:33:58,615 [model] Posterior to be computed for parameters {'Omega_m': 0.32669430903771113, 'b1': 0.5035907335598834}
2023-07-02 10:33:58,615 [prior] Evaluating prior at array([0.32669431, 0.50359073])
2023-07-02 10:33:58,615 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:58,615 [model] Got input parameters: {'Omega_m': 0.32669430903771113, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5035907335598834, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,615 [classy] Got parameters {'Omega_m': 0.32669430903771113, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:58,615 [classy] Re-using computed results
2023-07-02 10:33:58,615 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.58395680004216}
2023-07-02 10:33:58,615 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:58,615 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5035907335598834, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,615 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:58,634 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.548058
2023-07-02 10:33:58,634 [model] Computed derived parameters: {}
2023-07-02 10:33:58,634 [model] Posterior to be computed for parameters {'Omega_m': 0.3557945584978752, 'b1': 0.4420866486329316}
2023-07-02 10:33:58,634 [prior] Evaluating prior at array([0.35579456, 0.44208665])
2023-07-02 10:33:58,635 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:58,635 [model] Got input parameters: {'Omega_m': 0.3557945584978752, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4420866486329316, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,635 [classy] Got parameters {'Omega_m': 0.3557945584978752, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:58,635 [classy] Computing new state
2023-07-02 10:33:58,635 [classy] Setting parameters: {'Omega_m': 0.3557945584978752, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:58,679 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.3475597847608}
2023-07-02 10:33:58,679 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:58,681 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.103916
2023-07-02 10:33:58,681 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4420866486329316, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,681 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:58,700 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.54204
2023-07-02 10:33:58,700 [model] Computed derived parameters: {}
2023-07-02 10:33:58,700 [model] Posterior to be computed for parameters {'Omega_m': 0.32669430903771113, 'b1': 0.538146183363322}
2023-07-02 10:33:58,700 [prior] Evaluating prior at array([0.32669431, 0.53814618])
2023-07-02 10:33:58,700 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:58,701 [model] Got input parameters: {'Omega_m': 0.32669430903771113, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.538146183363322, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,701 [classy] Got parameters {'Omega_m': 0.32669430903771113, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:58,701 [classy] Re-using computed results
2023-07-02 10:33:58,701 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.58395680004216}
2023-07-02 10:33:58,701 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:58,701 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.538146183363322, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,701 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:58,720 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.84763
2023-07-02 10:33:58,720 [model] Computed derived parameters: {}
2023-07-02 10:33:58,720 [model] Posterior to be computed for parameters {'Omega_m': 0.2904527361570845, 'b1': 0.5344865154252195}
2023-07-02 10:33:58,720 [prior] Evaluating prior at array([0.29045274, 0.53448652])
2023-07-02 10:33:58,721 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:58,721 [model] Got input parameters: {'Omega_m': 0.2904527361570845, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5344865154252195, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,721 [classy] Got parameters {'Omega_m': 0.2904527361570845, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:58,721 [classy] Computing new state
2023-07-02 10:33:58,721 [classy] Setting parameters: {'Omega_m': 0.2904527361570845, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:58,764 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.99720687881018}
2023-07-02 10:33:58,765 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:58,766 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0316807
2023-07-02 10:33:58,766 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5344865154252195, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,766 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:58,786 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.17263
2023-07-02 10:33:58,786 [model] Computed derived parameters: {}
2023-07-02 10:33:58,786 [model] Posterior to be computed for parameters {'Omega_m': 0.32669430903771113, 'b1': 0.4735103346262174}
2023-07-02 10:33:58,786 [prior] Evaluating prior at array([0.32669431, 0.47351033])
2023-07-02 10:33:58,786 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:58,786 [model] Got input parameters: {'Omega_m': 0.32669430903771113, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4735103346262174, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,786 [classy] Got parameters {'Omega_m': 0.32669430903771113, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:58,786 [classy] Re-using computed results
2023-07-02 10:33:58,786 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.58395680004216}
2023-07-02 10:33:58,786 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:58,786 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4735103346262174, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,787 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:58,806 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.13238
2023-07-02 10:33:58,806 [model] Computed derived parameters: {}
2023-07-02 10:33:58,806 [mcmc] New sample, #351:
Omega_m:0.3266943, b1:0.4832373
2023-07-02 10:33:58,806 [model] Posterior to be computed for parameters {'Omega_m': 0.3628205529809486, 'b1': 0.4224242153770302}
2023-07-02 10:33:58,806 [prior] Evaluating prior at array([0.36282055, 0.42242422])
2023-07-02 10:33:58,806 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:58,806 [model] Got input parameters: {'Omega_m': 0.3628205529809486, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4224242153770302, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,806 [classy] Got parameters {'Omega_m': 0.3628205529809486, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:58,806 [classy] Computing new state
2023-07-02 10:33:58,806 [classy] Setting parameters: {'Omega_m': 0.3628205529809486, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:58,850 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.60260062588577}
2023-07-02 10:33:58,850 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:58,852 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.138067
2023-07-02 10:33:58,852 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4224242153770302, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,852 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:58,871 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.6798
2023-07-02 10:33:58,872 [model] Computed derived parameters: {}
2023-07-02 10:33:58,872 [model] Posterior to be computed for parameters {'Omega_m': 0.32669430903771113, 'b1': 0.4772316055619289}
2023-07-02 10:33:58,872 [prior] Evaluating prior at array([0.32669431, 0.47723161])
2023-07-02 10:33:58,872 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:58,872 [model] Got input parameters: {'Omega_m': 0.32669430903771113, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4772316055619289, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,872 [classy] Got parameters {'Omega_m': 0.32669430903771113, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:58,872 [classy] Re-using computed results
2023-07-02 10:33:58,872 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.58395680004216}
2023-07-02 10:33:58,872 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:58,872 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4772316055619289, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,872 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:58,892 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.20827
2023-07-02 10:33:58,892 [model] Computed derived parameters: {}
2023-07-02 10:33:58,892 [mcmc] New sample, #352:
Omega_m:0.3266943, b1:0.4735103
2023-07-02 10:33:58,892 [model] Posterior to be computed for parameters {'Omega_m': 0.35193552570279996, 'b1': 0.44153800269047183}
2023-07-02 10:33:58,892 [prior] Evaluating prior at array([0.35193553, 0.441538 ])
2023-07-02 10:33:58,892 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:58,892 [model] Got input parameters: {'Omega_m': 0.35193552570279996, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44153800269047183, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,892 [classy] Got parameters {'Omega_m': 0.35193552570279996, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:58,892 [classy] Computing new state
2023-07-02 10:33:58,892 [classy] Setting parameters: {'Omega_m': 0.35193552570279996, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:58,937 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.76252773701663}
2023-07-02 10:33:58,937 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:58,939 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0870256
2023-07-02 10:33:58,939 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44153800269047183, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,939 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:58,958 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.74285
2023-07-02 10:33:58,958 [model] Computed derived parameters: {}
2023-07-02 10:33:58,958 [model] Posterior to be computed for parameters {'Omega_m': 0.32669430903771113, 'b1': 0.4479765827375237}
2023-07-02 10:33:58,958 [prior] Evaluating prior at array([0.32669431, 0.44797658])
2023-07-02 10:33:58,958 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:58,958 [model] Got input parameters: {'Omega_m': 0.32669430903771113, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4479765827375237, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,958 [classy] Got parameters {'Omega_m': 0.32669430903771113, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:58,958 [classy] Re-using computed results
2023-07-02 10:33:58,958 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.58395680004216}
2023-07-02 10:33:58,959 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:58,959 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4479765827375237, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,959 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:58,978 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.345188
2023-07-02 10:33:58,978 [model] Computed derived parameters: {}
2023-07-02 10:33:58,978 [model] Posterior to be computed for parameters {'Omega_m': 0.3370104943604416, 'b1': 0.4626434885569676}
2023-07-02 10:33:58,979 [prior] Evaluating prior at array([0.33701049, 0.46264349])
2023-07-02 10:33:58,979 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:58,979 [model] Got input parameters: {'Omega_m': 0.3370104943604416, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4626434885569676, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:58,979 [classy] Got parameters {'Omega_m': 0.3370104943604416, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:58,979 [classy] Computing new state
2023-07-02 10:33:58,979 [classy] Setting parameters: {'Omega_m': 0.3370104943604416, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:59,022 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.40768086881573}
2023-07-02 10:33:59,023 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:59,024 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0349534
2023-07-02 10:33:59,024 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4626434885569676, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:59,025 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:59,044 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.473463
2023-07-02 10:33:59,044 [model] Computed derived parameters: {}
2023-07-02 10:33:59,044 [mcmc] New sample, #353:
Omega_m:0.3266943, b1:0.4772316
2023-07-02 10:33:59,044 [model] Posterior to be computed for parameters {'Omega_m': 0.3370104943604416, 'b1': 0.42668022661685284}
2023-07-02 10:33:59,044 [prior] Evaluating prior at array([0.33701049, 0.42668023])
2023-07-02 10:33:59,044 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:59,044 [model] Got input parameters: {'Omega_m': 0.3370104943604416, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42668022661685284, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:59,044 [classy] Got parameters {'Omega_m': 0.3370104943604416, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:59,044 [classy] Re-using computed results
2023-07-02 10:33:59,044 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.40768086881573}
2023-07-02 10:33:59,044 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:59,044 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42668022661685284, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:59,044 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:59,063 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.54675
2023-07-02 10:33:59,064 [model] Computed derived parameters: {}
2023-07-02 10:33:59,064 [model] Posterior to be computed for parameters {'Omega_m': 0.30641205370319907, 'b1': 0.5059127415330351}
2023-07-02 10:33:59,064 [prior] Evaluating prior at array([0.30641205, 0.50591274])
2023-07-02 10:33:59,064 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:59,064 [model] Got input parameters: {'Omega_m': 0.30641205370319907, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5059127415330351, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:59,064 [classy] Got parameters {'Omega_m': 0.30641205370319907, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:59,064 [classy] Computing new state
2023-07-02 10:33:59,064 [classy] Setting parameters: {'Omega_m': 0.30641205370319907, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:59,108 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.9971166485374}
2023-07-02 10:33:59,108 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:59,110 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00249794
2023-07-02 10:33:59,110 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5059127415330351, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:59,110 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:59,132 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.21072
2023-07-02 10:33:59,132 [model] Computed derived parameters: {}
2023-07-02 10:33:59,132 [mcmc] New sample, #354:
Omega_m:0.3370105, b1:0.4626435
2023-07-02 10:33:59,132 [model] Posterior to be computed for parameters {'Omega_m': 0.30641205370319907, 'b1': 0.5162927549867663}
2023-07-02 10:33:59,132 [prior] Evaluating prior at array([0.30641205, 0.51629275])
2023-07-02 10:33:59,133 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:59,133 [model] Got input parameters: {'Omega_m': 0.30641205370319907, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5162927549867663, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:59,133 [classy] Got parameters {'Omega_m': 0.30641205370319907, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:59,133 [classy] Re-using computed results
2023-07-02 10:33:59,133 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.9971166485374}
2023-07-02 10:33:59,133 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:59,133 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5162927549867663, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:59,133 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:59,153 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.4767
2023-07-02 10:33:59,153 [model] Computed derived parameters: {}
2023-07-02 10:33:59,153 [mcmc] New sample, #355:
Omega_m:0.3064121, b1:0.5059127
2023-07-02 10:33:59,153 [model] Posterior to be computed for parameters {'Omega_m': 0.3029997865972861, 'b1': 0.5211180416829599}
2023-07-02 10:33:59,153 [prior] Evaluating prior at array([0.30299979, 0.52111804])
2023-07-02 10:33:59,153 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:59,153 [model] Got input parameters: {'Omega_m': 0.3029997865972861, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5211180416829599, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:59,153 [classy] Got parameters {'Omega_m': 0.3029997865972861, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:59,153 [classy] Computing new state
2023-07-02 10:33:59,153 [classy] Setting parameters: {'Omega_m': 0.3029997865972861, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:59,197 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.41693983705898}
2023-07-02 10:33:59,197 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:59,199 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00585108
2023-07-02 10:33:59,199 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5211180416829599, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:59,199 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:59,219 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.04422
2023-07-02 10:33:59,219 [model] Computed derived parameters: {}
2023-07-02 10:33:59,219 [mcmc] New sample, #356:
Omega_m:0.3064121, b1:0.5162928
2023-07-02 10:33:59,219 [model] Posterior to be computed for parameters {'Omega_m': 0.3029997865972861, 'b1': 0.6092070961755289}
2023-07-02 10:33:59,219 [prior] Evaluating prior at array([0.30299979, 0.6092071 ])
2023-07-02 10:33:59,219 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:59,219 [model] Got input parameters: {'Omega_m': 0.3029997865972861, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6092070961755289, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:59,219 [classy] Got parameters {'Omega_m': 0.3029997865972861, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:59,219 [classy] Re-using computed results
2023-07-02 10:33:59,219 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.41693983705898}
2023-07-02 10:33:59,220 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:59,220 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6092070961755289, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:59,220 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:59,239 [fs_likelihood.fslikelihood] Computed log-likelihood = -19.95
2023-07-02 10:33:59,239 [model] Computed derived parameters: {}
2023-07-02 10:33:59,239 [model] Posterior to be computed for parameters {'Omega_m': 0.3013225429407779, 'b1': 0.5234898318303373}
2023-07-02 10:33:59,239 [prior] Evaluating prior at array([0.30132254, 0.52348983])
2023-07-02 10:33:59,240 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:59,240 [model] Got input parameters: {'Omega_m': 0.3013225429407779, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5234898318303373, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:59,240 [classy] Got parameters {'Omega_m': 0.3013225429407779, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:59,240 [classy] Computing new state
2023-07-02 10:33:59,240 [classy] Setting parameters: {'Omega_m': 0.3013225429407779, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:59,284 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.62481840707625}
2023-07-02 10:33:59,284 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:59,286 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00805874
2023-07-02 10:33:59,286 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5234898318303373, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:59,286 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:59,305 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.77263
2023-07-02 10:33:59,305 [model] Computed derived parameters: {}
2023-07-02 10:33:59,305 [mcmc] New sample, #357:
Omega_m:0.3029998, b1:0.521118
2023-07-02 10:33:59,305 [model] Posterior to be computed for parameters {'Omega_m': 0.3013225429407779, 'b1': 0.5483551461464687}
2023-07-02 10:33:59,305 [prior] Evaluating prior at array([0.30132254, 0.54835515])
2023-07-02 10:33:59,306 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:59,306 [model] Got input parameters: {'Omega_m': 0.3013225429407779, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5483551461464687, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:59,306 [classy] Got parameters {'Omega_m': 0.3013225429407779, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:59,306 [classy] Re-using computed results
2023-07-02 10:33:59,306 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.62481840707625}
2023-07-02 10:33:59,306 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:59,306 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5483551461464687, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:59,306 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:59,326 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.319601
2023-07-02 10:33:59,326 [model] Computed derived parameters: {}
2023-07-02 10:33:59,326 [model] Posterior to be computed for parameters {'Omega_m': 0.3007412339943405, 'b1': 0.5243118607743089}
2023-07-02 10:33:59,326 [prior] Evaluating prior at array([0.30074123, 0.52431186])
2023-07-02 10:33:59,326 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:59,326 [model] Got input parameters: {'Omega_m': 0.3007412339943405, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5243118607743089, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:59,326 [classy] Got parameters {'Omega_m': 0.3007412339943405, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:59,326 [classy] Computing new state
2023-07-02 10:33:59,326 [classy] Setting parameters: {'Omega_m': 0.3007412339943405, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:59,370 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.69710255486774}
2023-07-02 10:33:59,370 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:59,372 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00891116
2023-07-02 10:33:59,372 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5243118607743089, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:59,372 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:59,392 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.66924
2023-07-02 10:33:59,392 [model] Computed derived parameters: {}
2023-07-02 10:33:59,392 [mcmc] New sample, #358:
Omega_m:0.3013225, b1:0.5234898
2023-07-02 10:33:59,392 [model] Posterior to be computed for parameters {'Omega_m': 0.3007412339943405, 'b1': 0.5193881621776889}
2023-07-02 10:33:59,392 [prior] Evaluating prior at array([0.30074123, 0.51938816])
2023-07-02 10:33:59,393 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:59,393 [model] Got input parameters: {'Omega_m': 0.3007412339943405, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5193881621776889, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:59,393 [classy] Got parameters {'Omega_m': 0.3007412339943405, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:59,393 [classy] Re-using computed results
2023-07-02 10:33:59,393 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.69710255486774}
2023-07-02 10:33:59,393 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:59,393 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5193881621776889, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:59,393 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:59,412 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.55518
2023-07-02 10:33:59,412 [model] Computed derived parameters: {}
2023-07-02 10:33:59,412 [mcmc] New sample, #359:
Omega_m:0.3007412, b1:0.5243119
2023-07-02 10:33:59,412 [model] Posterior to be computed for parameters {'Omega_m': 0.2999288016564884, 'b1': 0.5205370226946755}
2023-07-02 10:33:59,412 [prior] Evaluating prior at array([0.2999288 , 0.52053702])
2023-07-02 10:33:59,412 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:59,413 [model] Got input parameters: {'Omega_m': 0.2999288016564884, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5205370226946755, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:59,413 [classy] Got parameters {'Omega_m': 0.2999288016564884, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:59,413 [classy] Computing new state
2023-07-02 10:33:59,413 [classy] Setting parameters: {'Omega_m': 0.2999288016564884, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:59,457 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.79834225312166}
2023-07-02 10:33:59,457 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:59,458 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0101786
2023-07-02 10:33:59,459 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5205370226946755, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:59,459 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:59,479 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.3943
2023-07-02 10:33:59,479 [model] Computed derived parameters: {}
2023-07-02 10:33:59,479 [mcmc] New sample, #360:
Omega_m:0.3007412, b1:0.5193882
2023-07-02 10:33:59,479 [model] Posterior to be computed for parameters {'Omega_m': 0.2999288016564884, 'b1': 0.47472049413044237}
2023-07-02 10:33:59,479 [prior] Evaluating prior at array([0.2999288 , 0.47472049])
2023-07-02 10:33:59,480 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:59,480 [model] Got input parameters: {'Omega_m': 0.2999288016564884, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47472049413044237, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:59,480 [classy] Got parameters {'Omega_m': 0.2999288016564884, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:59,480 [classy] Re-using computed results
2023-07-02 10:33:59,480 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.79834225312166}
2023-07-02 10:33:59,480 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:59,480 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47472049413044237, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:59,480 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:59,499 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.5402
2023-07-02 10:33:59,499 [model] Computed derived parameters: {}
2023-07-02 10:33:59,500 [model] Posterior to be computed for parameters {'Omega_m': 0.3047433114156396, 'b1': 0.5137288247522372}
2023-07-02 10:33:59,500 [prior] Evaluating prior at array([0.30474331, 0.51372882])
2023-07-02 10:33:59,500 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:59,500 [model] Got input parameters: {'Omega_m': 0.3047433114156396, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5137288247522372, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:59,500 [classy] Got parameters {'Omega_m': 0.3047433114156396, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:59,500 [classy] Computing new state
2023-07-02 10:33:59,500 [classy] Setting parameters: {'Omega_m': 0.3047433114156396, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:59,544 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2019121948667}
2023-07-02 10:33:59,544 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:59,546 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0039487
2023-07-02 10:33:59,546 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5137288247522372, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:59,546 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:59,566 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.2123
2023-07-02 10:33:59,566 [model] Computed derived parameters: {}
2023-07-02 10:33:59,566 [mcmc] New sample, #361:
Omega_m:0.2999288, b1:0.520537
2023-07-02 10:33:59,566 [model] Posterior to be computed for parameters {'Omega_m': 0.3047433114156396, 'b1': 0.5309169448072816}
2023-07-02 10:33:59,566 [prior] Evaluating prior at array([0.30474331, 0.53091694])
2023-07-02 10:33:59,566 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:59,566 [model] Got input parameters: {'Omega_m': 0.3047433114156396, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5309169448072816, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:59,566 [classy] Got parameters {'Omega_m': 0.3047433114156396, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:59,566 [classy] Re-using computed results
2023-07-02 10:33:59,566 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2019121948667}
2023-07-02 10:33:59,566 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:59,566 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5309169448072816, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:59,566 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:59,587 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.90017
2023-07-02 10:33:59,587 [model] Computed derived parameters: {}
2023-07-02 10:33:59,587 [mcmc] New sample, #362:
Omega_m:0.3047433, b1:0.5137288
2023-07-02 10:33:59,587 [model] Posterior to be computed for parameters {'Omega_m': 0.306334387878479, 'b1': 0.5286670036829594}
2023-07-02 10:33:59,587 [prior] Evaluating prior at array([0.30633439, 0.528667 ])
2023-07-02 10:33:59,587 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:59,587 [model] Got input parameters: {'Omega_m': 0.306334387878479, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5286670036829594, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:59,587 [classy] Got parameters {'Omega_m': 0.306334387878479, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:59,587 [classy] Computing new state
2023-07-02 10:33:59,587 [classy] Setting parameters: {'Omega_m': 0.306334387878479, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:59,632 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.00662391847243}
2023-07-02 10:33:59,632 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:59,633 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00255747
2023-07-02 10:33:59,634 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5286670036829594, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:59,634 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:59,653 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.04037
2023-07-02 10:33:59,653 [model] Computed derived parameters: {}
2023-07-02 10:33:59,653 [mcmc] New sample, #363:
Omega_m:0.3047433, b1:0.5309169
2023-07-02 10:33:59,653 [model] Posterior to be computed for parameters {'Omega_m': 0.306334387878479, 'b1': 0.5380079157217817}
2023-07-02 10:33:59,653 [prior] Evaluating prior at array([0.30633439, 0.53800792])
2023-07-02 10:33:59,653 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:59,653 [model] Got input parameters: {'Omega_m': 0.306334387878479, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5380079157217817, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:59,653 [classy] Got parameters {'Omega_m': 0.306334387878479, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:59,653 [classy] Re-using computed results
2023-07-02 10:33:59,653 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.00662391847243}
2023-07-02 10:33:59,653 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:59,653 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5380079157217817, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:59,653 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:59,672 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.15584
2023-07-02 10:33:59,673 [model] Computed derived parameters: {}
2023-07-02 10:33:59,673 [mcmc] New sample, #364:
Omega_m:0.3063344, b1:0.528667
2023-07-02 10:33:59,673 [model] Posterior to be computed for parameters {'Omega_m': 0.3100820817656607, 'b1': 0.5327083020356528}
2023-07-02 10:33:59,673 [prior] Evaluating prior at array([0.31008208, 0.5327083 ])
2023-07-02 10:33:59,673 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:59,673 [model] Got input parameters: {'Omega_m': 0.3100820817656607, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5327083020356528, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:59,673 [classy] Got parameters {'Omega_m': 0.3100820817656607, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:59,673 [classy] Computing new state
2023-07-02 10:33:59,673 [classy] Setting parameters: {'Omega_m': 0.3100820817656607, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:59,717 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.55013797528926}
2023-07-02 10:33:59,718 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:59,719 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000558299
2023-07-02 10:33:59,719 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5327083020356528, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:59,719 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:59,740 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.269
2023-07-02 10:33:59,740 [model] Computed derived parameters: {}
2023-07-02 10:33:59,740 [mcmc] New sample, #365:
Omega_m:0.3063344, b1:0.5380079
2023-07-02 10:33:59,740 [model] Posterior to be computed for parameters {'Omega_m': 0.3100820817656607, 'b1': 0.5610362963643449}
2023-07-02 10:33:59,740 [prior] Evaluating prior at array([0.31008208, 0.5610363 ])
2023-07-02 10:33:59,740 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:59,740 [model] Got input parameters: {'Omega_m': 0.3100820817656607, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5610362963643449, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:59,740 [classy] Got parameters {'Omega_m': 0.3100820817656607, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:59,740 [classy] Re-using computed results
2023-07-02 10:33:59,740 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.55013797528926}
2023-07-02 10:33:59,740 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:59,740 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5610362963643449, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:59,740 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:59,759 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.79005
2023-07-02 10:33:59,760 [model] Computed derived parameters: {}
2023-07-02 10:33:59,760 [model] Posterior to be computed for parameters {'Omega_m': 0.297930075429868, 'b1': 0.5498924534177505}
2023-07-02 10:33:59,760 [prior] Evaluating prior at array([0.29793008, 0.54989245])
2023-07-02 10:33:59,760 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:59,760 [model] Got input parameters: {'Omega_m': 0.297930075429868, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5498924534177505, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:59,760 [classy] Got parameters {'Omega_m': 0.297930075429868, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:59,760 [classy] Computing new state
2023-07-02 10:33:59,760 [classy] Setting parameters: {'Omega_m': 0.297930075429868, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:59,805 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.04844272578305}
2023-07-02 10:33:59,805 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:59,806 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0136769
2023-07-02 10:33:59,806 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5498924534177505, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:59,806 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:59,826 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.196817
2023-07-02 10:33:59,826 [model] Computed derived parameters: {}
2023-07-02 10:33:59,826 [model] Posterior to be computed for parameters {'Omega_m': 0.3100820817656607, 'b1': 0.5184212274663356}
2023-07-02 10:33:59,826 [prior] Evaluating prior at array([0.31008208, 0.51842123])
2023-07-02 10:33:59,826 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:59,826 [model] Got input parameters: {'Omega_m': 0.3100820817656607, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5184212274663356, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:59,826 [classy] Got parameters {'Omega_m': 0.3100820817656607, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:59,827 [classy] Re-using computed results
2023-07-02 10:33:59,827 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.55013797528926}
2023-07-02 10:33:59,827 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:59,827 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5184212274663356, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:59,827 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:59,847 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.55041
2023-07-02 10:33:59,847 [model] Computed derived parameters: {}
2023-07-02 10:33:59,847 [mcmc] New sample, #366:
Omega_m:0.3100821, b1:0.5327083
2023-07-02 10:33:59,847 [model] Posterior to be computed for parameters {'Omega_m': 0.304065971352212, 'b1': 0.5269286088171513}
2023-07-02 10:33:59,847 [prior] Evaluating prior at array([0.30406597, 0.52692861])
2023-07-02 10:33:59,847 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:59,847 [model] Got input parameters: {'Omega_m': 0.304065971352212, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5269286088171513, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:59,847 [classy] Got parameters {'Omega_m': 0.304065971352212, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:59,847 [classy] Computing new state
2023-07-02 10:33:59,847 [classy] Setting parameters: {'Omega_m': 0.304065971352212, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:59,892 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.28531780081414}
2023-07-02 10:33:59,892 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:59,894 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00464052
2023-07-02 10:33:59,894 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5269286088171513, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:59,894 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:59,913 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.07602
2023-07-02 10:33:59,913 [model] Computed derived parameters: {}
2023-07-02 10:33:59,914 [model] Posterior to be computed for parameters {'Omega_m': 0.3100820817656607, 'b1': 0.5312831796253852}
2023-07-02 10:33:59,914 [prior] Evaluating prior at array([0.31008208, 0.53128318])
2023-07-02 10:33:59,914 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:59,914 [model] Got input parameters: {'Omega_m': 0.3100820817656607, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5312831796253852, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:59,914 [classy] Got parameters {'Omega_m': 0.3100820817656607, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:59,914 [classy] Re-using computed results
2023-07-02 10:33:59,914 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.55013797528926}
2023-07-02 10:33:59,914 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:33:59,914 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5312831796253852, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:59,914 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:33:59,934 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.44872
2023-07-02 10:33:59,934 [model] Computed derived parameters: {}
2023-07-02 10:33:59,934 [model] Posterior to be computed for parameters {'Omega_m': 0.28140960850445523, 'b1': 0.5589669700708685}
2023-07-02 10:33:59,934 [prior] Evaluating prior at array([0.28140961, 0.55896697])
2023-07-02 10:33:59,935 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:33:59,935 [model] Got input parameters: {'Omega_m': 0.28140960850445523, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5589669700708685, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:59,935 [classy] Got parameters {'Omega_m': 0.28140960850445523, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:33:59,935 [classy] Computing new state
2023-07-02 10:33:59,935 [classy] Setting parameters: {'Omega_m': 0.28140960850445523, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:33:59,979 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.17334913713125}
2023-07-02 10:33:59,979 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:33:59,981 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0643291
2023-07-02 10:33:59,981 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5589669700708685, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:33:59,981 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:00,000 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.47915
2023-07-02 10:34:00,000 [model] Computed derived parameters: {}
2023-07-02 10:34:00,000 [model] Posterior to be computed for parameters {'Omega_m': 0.3100820817656607, 'b1': 0.5015174155101206}
2023-07-02 10:34:00,000 [prior] Evaluating prior at array([0.31008208, 0.50151742])
2023-07-02 10:34:00,001 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:00,001 [model] Got input parameters: {'Omega_m': 0.3100820817656607, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5015174155101206, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,001 [classy] Got parameters {'Omega_m': 0.3100820817656607, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:00,001 [classy] Re-using computed results
2023-07-02 10:34:00,001 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.55013797528926}
2023-07-02 10:34:00,001 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:00,001 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5015174155101206, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,001 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:00,020 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.61638
2023-07-02 10:34:00,020 [model] Computed derived parameters: {}
2023-07-02 10:34:00,020 [mcmc] New sample, #367:
Omega_m:0.3100821, b1:0.5184212
2023-07-02 10:34:00,020 [model] Posterior to be computed for parameters {'Omega_m': 0.30546450836965516, 'b1': 0.5080471257540324}
2023-07-02 10:34:00,020 [prior] Evaluating prior at array([0.30546451, 0.50804713])
2023-07-02 10:34:00,021 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:00,021 [model] Got input parameters: {'Omega_m': 0.30546450836965516, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5080471257540324, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,021 [classy] Got parameters {'Omega_m': 0.30546450836965516, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:00,021 [classy] Computing new state
2023-07-02 10:34:00,021 [classy] Setting parameters: {'Omega_m': 0.30546450836965516, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:00,065 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.11328191181138}
2023-07-02 10:34:00,065 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:00,067 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00327756
2023-07-02 10:34:00,067 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5080471257540324, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,067 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:00,088 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.12786
2023-07-02 10:34:00,088 [model] Computed derived parameters: {}
2023-07-02 10:34:00,088 [model] Posterior to be computed for parameters {'Omega_m': 0.3100820817656607, 'b1': 0.449894631677556}
2023-07-02 10:34:00,088 [prior] Evaluating prior at array([0.31008208, 0.44989463])
2023-07-02 10:34:00,088 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:00,088 [model] Got input parameters: {'Omega_m': 0.3100820817656607, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.449894631677556, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,089 [classy] Got parameters {'Omega_m': 0.3100820817656607, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:00,089 [classy] Re-using computed results
2023-07-02 10:34:00,089 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.55013797528926}
2023-07-02 10:34:00,089 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:00,089 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.449894631677556, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,089 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:00,109 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.13449
2023-07-02 10:34:00,109 [model] Computed derived parameters: {}
2023-07-02 10:34:00,109 [model] Posterior to be computed for parameters {'Omega_m': 0.3357715769196523, 'b1': 0.46518990205618194}
2023-07-02 10:34:00,109 [prior] Evaluating prior at array([0.33577158, 0.4651899 ])
2023-07-02 10:34:00,109 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:00,109 [model] Got input parameters: {'Omega_m': 0.3357715769196523, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46518990205618194, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,109 [classy] Got parameters {'Omega_m': 0.3357715769196523, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:00,109 [classy] Computing new state
2023-07-02 10:34:00,109 [classy] Setting parameters: {'Omega_m': 0.3357715769196523, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:00,158 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.5472113739485}
2023-07-02 10:34:00,158 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:00,160 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0316237
2023-07-02 10:34:00,160 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46518990205618194, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,160 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:00,179 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.727329
2023-07-02 10:34:00,179 [model] Computed derived parameters: {}
2023-07-02 10:34:00,179 [mcmc] New sample, #368:
Omega_m:0.3100821, b1:0.5015174
2023-07-02 10:34:00,179 [model] Posterior to be computed for parameters {'Omega_m': 0.3357715769196523, 'b1': 0.46374019534941474}
2023-07-02 10:34:00,179 [prior] Evaluating prior at array([0.33577158, 0.4637402 ])
2023-07-02 10:34:00,180 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:00,180 [model] Got input parameters: {'Omega_m': 0.3357715769196523, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46374019534941474, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,180 [classy] Got parameters {'Omega_m': 0.3357715769196523, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:00,180 [classy] Re-using computed results
2023-07-02 10:34:00,180 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.5472113739485}
2023-07-02 10:34:00,180 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:00,180 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46374019534941474, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,180 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:00,200 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.741294
2023-07-02 10:34:00,200 [model] Computed derived parameters: {}
2023-07-02 10:34:00,200 [mcmc] New sample, #369:
Omega_m:0.3357716, b1:0.4651899
2023-07-02 10:34:00,200 [model] Posterior to be computed for parameters {'Omega_m': 0.3484646051337628, 'b1': 0.4457909849637962}
2023-07-02 10:34:00,201 [prior] Evaluating prior at array([0.34846461, 0.44579098])
2023-07-02 10:34:00,201 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:00,201 [model] Got input parameters: {'Omega_m': 0.3484646051337628, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4457909849637962, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,201 [classy] Got parameters {'Omega_m': 0.3484646051337628, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:00,201 [classy] Computing new state
2023-07-02 10:34:00,201 [classy] Setting parameters: {'Omega_m': 0.3484646051337628, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:00,247 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.13933695823752}
2023-07-02 10:34:00,247 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:00,248 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0730047
2023-07-02 10:34:00,249 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4457909849637962, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,249 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:00,270 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.5764
2023-07-02 10:34:00,270 [model] Computed derived parameters: {}
2023-07-02 10:34:00,270 [model] Posterior to be computed for parameters {'Omega_m': 0.3357715769196523, 'b1': 0.4552282237432503}
2023-07-02 10:34:00,270 [prior] Evaluating prior at array([0.33577158, 0.45522822])
2023-07-02 10:34:00,270 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:00,270 [model] Got input parameters: {'Omega_m': 0.3357715769196523, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4552282237432503, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,270 [classy] Got parameters {'Omega_m': 0.3357715769196523, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:00,270 [classy] Re-using computed results
2023-07-02 10:34:00,270 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.5472113739485}
2023-07-02 10:34:00,270 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:00,270 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4552282237432503, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,270 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:00,291 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.591418
2023-07-02 10:34:00,291 [model] Computed derived parameters: {}
2023-07-02 10:34:00,291 [mcmc] New sample, #370:
Omega_m:0.3357716, b1:0.4637402
2023-07-02 10:34:00,291 [model] Posterior to be computed for parameters {'Omega_m': 0.34097483181638716, 'b1': 0.4478703013266224}
2023-07-02 10:34:00,291 [prior] Evaluating prior at array([0.34097483, 0.4478703 ])
2023-07-02 10:34:00,292 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:00,292 [model] Got input parameters: {'Omega_m': 0.34097483181638716, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4478703013266224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,292 [classy] Got parameters {'Omega_m': 0.34097483181638716, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:00,292 [classy] Computing new state
2023-07-02 10:34:00,292 [classy] Setting parameters: {'Omega_m': 0.34097483181638716, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:00,336 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.9643061477438}
2023-07-02 10:34:00,336 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:00,338 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.046658
2023-07-02 10:34:00,338 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4478703013266224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,338 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:00,357 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.505656
2023-07-02 10:34:00,357 [model] Computed derived parameters: {}
2023-07-02 10:34:00,357 [model] Posterior to be computed for parameters {'Omega_m': 0.3357715769196523, 'b1': 0.4686038888114684}
2023-07-02 10:34:00,357 [prior] Evaluating prior at array([0.33577158, 0.46860389])
2023-07-02 10:34:00,358 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:00,358 [model] Got input parameters: {'Omega_m': 0.3357715769196523, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4686038888114684, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,358 [classy] Got parameters {'Omega_m': 0.3357715769196523, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:00,358 [classy] Re-using computed results
2023-07-02 10:34:00,358 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.5472113739485}
2023-07-02 10:34:00,358 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:00,358 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4686038888114684, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,358 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:00,377 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.648418
2023-07-02 10:34:00,377 [model] Computed derived parameters: {}
2023-07-02 10:34:00,377 [mcmc] New sample, #371:
Omega_m:0.3357716, b1:0.4552282
2023-07-02 10:34:00,377 [model] Posterior to be computed for parameters {'Omega_m': 0.3392266129036548, 'b1': 0.46371812264750434}
2023-07-02 10:34:00,377 [prior] Evaluating prior at array([0.33922661, 0.46371812])
2023-07-02 10:34:00,377 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:00,377 [model] Got input parameters: {'Omega_m': 0.3392266129036548, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46371812264750434, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,377 [classy] Got parameters {'Omega_m': 0.3392266129036548, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:00,378 [classy] Computing new state
2023-07-02 10:34:00,378 [classy] Setting parameters: {'Omega_m': 0.3392266129036548, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:00,422 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.15924799238002}
2023-07-02 10:34:00,422 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:00,424 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0413009
2023-07-02 10:34:00,424 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46371812264750434, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,424 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:00,444 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.152064
2023-07-02 10:34:00,444 [model] Computed derived parameters: {}
2023-07-02 10:34:00,444 [mcmc] New sample, #372:
Omega_m:0.3357716, b1:0.4686039
2023-07-02 10:34:00,444 [model] Posterior to be computed for parameters {'Omega_m': 0.3392266129036548, 'b1': 0.46399124076873466}
2023-07-02 10:34:00,444 [prior] Evaluating prior at array([0.33922661, 0.46399124])
2023-07-02 10:34:00,445 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:00,445 [model] Got input parameters: {'Omega_m': 0.3392266129036548, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46399124076873466, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,445 [classy] Got parameters {'Omega_m': 0.3392266129036548, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:00,445 [classy] Re-using computed results
2023-07-02 10:34:00,445 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.15924799238002}
2023-07-02 10:34:00,445 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:00,445 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46399124076873466, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,445 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:00,464 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.16328
2023-07-02 10:34:00,464 [model] Computed derived parameters: {}
2023-07-02 10:34:00,464 [mcmc] New sample, #373:
Omega_m:0.3392266, b1:0.4637181
2023-07-02 10:34:00,464 [model] Posterior to be computed for parameters {'Omega_m': 0.3392414315069503, 'b1': 0.46397028578276245}
2023-07-02 10:34:00,464 [prior] Evaluating prior at array([0.33924143, 0.46397029])
2023-07-02 10:34:00,464 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:00,464 [model] Got input parameters: {'Omega_m': 0.3392414315069503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46397028578276245, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,464 [classy] Got parameters {'Omega_m': 0.3392414315069503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:00,464 [classy] Computing new state
2023-07-02 10:34:00,464 [classy] Setting parameters: {'Omega_m': 0.3392414315069503, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:00,509 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.15759263528454}
2023-07-02 10:34:00,509 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:00,511 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.041345
2023-07-02 10:34:00,511 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46397028578276245, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,511 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:00,530 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.166957
2023-07-02 10:34:00,530 [model] Computed derived parameters: {}
2023-07-02 10:34:00,530 [mcmc] New sample, #374:
Omega_m:0.3392266, b1:0.4639912
2023-07-02 10:34:00,530 [model] Posterior to be computed for parameters {'Omega_m': 0.3392414315069503, 'b1': 0.37307515200024777}
2023-07-02 10:34:00,531 [prior] Evaluating prior at array([0.33924143, 0.37307515])
2023-07-02 10:34:00,531 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:00,531 [model] Got input parameters: {'Omega_m': 0.3392414315069503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.37307515200024777, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,531 [classy] Got parameters {'Omega_m': 0.3392414315069503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:00,531 [classy] Re-using computed results
2023-07-02 10:34:00,531 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.15759263528454}
2023-07-02 10:34:00,531 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:00,531 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.37307515200024777, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,531 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:00,551 [fs_likelihood.fslikelihood] Computed log-likelihood = -17.5786
2023-07-02 10:34:00,551 [model] Computed derived parameters: {}
2023-07-02 10:34:00,551 [model] Posterior to be computed for parameters {'Omega_m': 0.3319842465738009, 'b1': 0.4742326705324972}
2023-07-02 10:34:00,551 [prior] Evaluating prior at array([0.33198425, 0.47423267])
2023-07-02 10:34:00,552 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:00,552 [model] Got input parameters: {'Omega_m': 0.3319842465738009, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4742326705324972, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,552 [classy] Got parameters {'Omega_m': 0.3319842465738009, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:00,552 [classy] Computing new state
2023-07-02 10:34:00,552 [classy] Setting parameters: {'Omega_m': 0.3319842465738009, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:00,596 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.97664988466943}
2023-07-02 10:34:00,596 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:00,597 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0224353
2023-07-02 10:34:00,598 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4742326705324972, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,598 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:00,617 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.39
2023-07-02 10:34:00,617 [model] Computed derived parameters: {}
2023-07-02 10:34:00,617 [mcmc] New sample, #375:
Omega_m:0.3392414, b1:0.4639703
2023-07-02 10:34:00,617 [model] Posterior to be computed for parameters {'Omega_m': 0.3319842465738009, 'b1': 0.47016964205098094}
2023-07-02 10:34:00,617 [prior] Evaluating prior at array([0.33198425, 0.47016964])
2023-07-02 10:34:00,617 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:00,617 [model] Got input parameters: {'Omega_m': 0.3319842465738009, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47016964205098094, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,617 [classy] Got parameters {'Omega_m': 0.3319842465738009, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:00,618 [classy] Re-using computed results
2023-07-02 10:34:00,618 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.97664988466943}
2023-07-02 10:34:00,618 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:00,618 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47016964205098094, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,618 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:00,637 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.449
2023-07-02 10:34:00,637 [model] Computed derived parameters: {}
2023-07-02 10:34:00,637 [mcmc] New sample, #376:
Omega_m:0.3319842, b1:0.4742327
2023-07-02 10:34:00,637 [model] Posterior to be computed for parameters {'Omega_m': 0.33016587977308526, 'b1': 0.4727409944275546}
2023-07-02 10:34:00,637 [prior] Evaluating prior at array([0.33016588, 0.47274099])
2023-07-02 10:34:00,637 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:00,638 [model] Got input parameters: {'Omega_m': 0.33016587977308526, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4727409944275546, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,638 [classy] Got parameters {'Omega_m': 0.33016587977308526, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:00,638 [classy] Computing new state
2023-07-02 10:34:00,638 [classy] Setting parameters: {'Omega_m': 0.33016587977308526, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:00,682 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.18440148741675}
2023-07-02 10:34:00,682 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:00,683 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0185628
2023-07-02 10:34:00,684 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4727409944275546, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,684 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:00,704 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.74339
2023-07-02 10:34:00,704 [model] Computed derived parameters: {}
2023-07-02 10:34:00,704 [mcmc] New sample, #377:
Omega_m:0.3319842, b1:0.4701696
2023-07-02 10:34:00,704 [model] Posterior to be computed for parameters {'Omega_m': 0.33016587977308526, 'b1': 0.4861989109628942}
2023-07-02 10:34:00,704 [prior] Evaluating prior at array([0.33016588, 0.48619891])
2023-07-02 10:34:00,704 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:00,704 [model] Got input parameters: {'Omega_m': 0.33016587977308526, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4861989109628942, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,704 [classy] Got parameters {'Omega_m': 0.33016587977308526, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:00,704 [classy] Re-using computed results
2023-07-02 10:34:00,704 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.18440148741675}
2023-07-02 10:34:00,704 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:00,704 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4861989109628942, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,704 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:00,723 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.24987
2023-07-02 10:34:00,723 [model] Computed derived parameters: {}
2023-07-02 10:34:00,724 [mcmc] New sample, #378:
Omega_m:0.3301659, b1:0.472741
2023-07-02 10:34:00,724 [model] Posterior to be computed for parameters {'Omega_m': 0.31822809996285656, 'b1': 0.5030801246288957}
2023-07-02 10:34:00,724 [prior] Evaluating prior at array([0.3182281 , 0.50308012])
2023-07-02 10:34:00,724 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:00,724 [model] Got input parameters: {'Omega_m': 0.31822809996285656, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5030801246288957, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,724 [classy] Got parameters {'Omega_m': 0.31822809996285656, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:00,724 [classy] Computing new state
2023-07-02 10:34:00,724 [classy] Setting parameters: {'Omega_m': 0.31822809996285656, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:00,768 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.57454846355145}
2023-07-02 10:34:00,768 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:00,770 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00219698
2023-07-02 10:34:00,770 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5030801246288957, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,770 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:00,790 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.67421
2023-07-02 10:34:00,790 [model] Computed derived parameters: {}
2023-07-02 10:34:00,790 [mcmc] New sample, #379:
Omega_m:0.3301659, b1:0.4861989
2023-07-02 10:34:00,791 [model] Posterior to be computed for parameters {'Omega_m': 0.31822809996285656, 'b1': 0.47963362413864974}
2023-07-02 10:34:00,791 [prior] Evaluating prior at array([0.3182281 , 0.47963362])
2023-07-02 10:34:00,791 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:00,791 [model] Got input parameters: {'Omega_m': 0.31822809996285656, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47963362413864974, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,791 [classy] Got parameters {'Omega_m': 0.31822809996285656, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:00,791 [classy] Re-using computed results
2023-07-02 10:34:00,791 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.57454846355145}
2023-07-02 10:34:00,791 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:00,791 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47963362413864974, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,791 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:00,811 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.28769
2023-07-02 10:34:00,811 [model] Computed derived parameters: {}
2023-07-02 10:34:00,811 [mcmc] New sample, #380:
Omega_m:0.3182281, b1:0.5030801
2023-07-02 10:34:00,811 [model] Posterior to be computed for parameters {'Omega_m': 0.31009147375237867, 'b1': 0.491139626742398}
2023-07-02 10:34:00,811 [prior] Evaluating prior at array([0.31009147, 0.49113963])
2023-07-02 10:34:00,811 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:00,811 [model] Got input parameters: {'Omega_m': 0.31009147375237867, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.491139626742398, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,811 [classy] Got parameters {'Omega_m': 0.31009147375237867, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:00,811 [classy] Computing new state
2023-07-02 10:34:00,811 [classy] Setting parameters: {'Omega_m': 0.31009147375237867, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:00,856 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.54899976677146}
2023-07-02 10:34:00,856 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:00,857 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000555511
2023-07-02 10:34:00,857 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.491139626742398, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,858 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:00,877 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.91203
2023-07-02 10:34:00,877 [model] Computed derived parameters: {}
2023-07-02 10:34:00,877 [mcmc] New sample, #381:
Omega_m:0.3182281, b1:0.4796336
2023-07-02 10:34:00,877 [model] Posterior to be computed for parameters {'Omega_m': 0.31009147375237867, 'b1': 0.44323128292284303}
2023-07-02 10:34:00,877 [prior] Evaluating prior at array([0.31009147, 0.44323128])
2023-07-02 10:34:00,877 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:00,877 [model] Got input parameters: {'Omega_m': 0.31009147375237867, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44323128292284303, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,877 [classy] Got parameters {'Omega_m': 0.31009147375237867, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:00,877 [classy] Re-using computed results
2023-07-02 10:34:00,877 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.54899976677146}
2023-07-02 10:34:00,877 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:00,877 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44323128292284303, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,877 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:00,898 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.16592
2023-07-02 10:34:00,898 [model] Computed derived parameters: {}
2023-07-02 10:34:00,898 [model] Posterior to be computed for parameters {'Omega_m': 0.29298879356262336, 'b1': 0.5153245257046967}
2023-07-02 10:34:00,898 [prior] Evaluating prior at array([0.29298879, 0.51532453])
2023-07-02 10:34:00,898 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:00,898 [model] Got input parameters: {'Omega_m': 0.29298879356262336, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5153245257046967, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,898 [classy] Got parameters {'Omega_m': 0.29298879356262336, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:00,898 [classy] Computing new state
2023-07-02 10:34:00,898 [classy] Setting parameters: {'Omega_m': 0.29298879356262336, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:00,943 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.67306915815044}
2023-07-02 10:34:00,943 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:00,945 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0246896
2023-07-02 10:34:00,945 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5153245257046967, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,945 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:00,964 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.71918
2023-07-02 10:34:00,964 [model] Computed derived parameters: {}
2023-07-02 10:34:00,964 [model] Posterior to be computed for parameters {'Omega_m': 0.31009147375237867, 'b1': 0.5208796410411071}
2023-07-02 10:34:00,964 [prior] Evaluating prior at array([0.31009147, 0.52087964])
2023-07-02 10:34:00,964 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:00,964 [model] Got input parameters: {'Omega_m': 0.31009147375237867, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5208796410411071, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,964 [classy] Got parameters {'Omega_m': 0.31009147375237867, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:00,964 [classy] Re-using computed results
2023-07-02 10:34:00,964 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.54899976677146}
2023-07-02 10:34:00,965 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:00,965 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5208796410411071, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,965 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:00,983 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.41089
2023-07-02 10:34:00,984 [model] Computed derived parameters: {}
2023-07-02 10:34:00,984 [mcmc] New sample, #382:
Omega_m:0.3100915, b1:0.4911396
2023-07-02 10:34:00,984 [model] Posterior to be computed for parameters {'Omega_m': 0.3256378573794381, 'b1': 0.49889550094856255}
2023-07-02 10:34:00,984 [prior] Evaluating prior at array([0.32563786, 0.4988955 ])
2023-07-02 10:34:00,984 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:00,984 [model] Got input parameters: {'Omega_m': 0.3256378573794381, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49889550094856255, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:00,984 [classy] Got parameters {'Omega_m': 0.3256378573794381, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:00,984 [classy] Computing new state
2023-07-02 10:34:00,984 [classy] Setting parameters: {'Omega_m': 0.3256378573794381, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:01,028 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.7063046580616}
2023-07-02 10:34:01,028 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:01,029 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0104746
2023-07-02 10:34:01,030 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49889550094856255, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:01,030 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:01,050 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.45708
2023-07-02 10:34:01,050 [model] Computed derived parameters: {}
2023-07-02 10:34:01,050 [model] Posterior to be computed for parameters {'Omega_m': 0.31009147375237867, 'b1': 0.5859242913094588}
2023-07-02 10:34:01,050 [prior] Evaluating prior at array([0.31009147, 0.58592429])
2023-07-02 10:34:01,050 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:01,050 [model] Got input parameters: {'Omega_m': 0.31009147375237867, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5859242913094588, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:01,050 [classy] Got parameters {'Omega_m': 0.31009147375237867, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:01,050 [classy] Re-using computed results
2023-07-02 10:34:01,050 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.54899976677146}
2023-07-02 10:34:01,050 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:01,050 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5859242913094588, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:01,050 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:01,069 [fs_likelihood.fslikelihood] Computed log-likelihood = -14.2342
2023-07-02 10:34:01,069 [model] Computed derived parameters: {}
2023-07-02 10:34:01,070 [model] Posterior to be computed for parameters {'Omega_m': 0.3062966987295614, 'b1': 0.5262458321581266}
2023-07-02 10:34:01,070 [prior] Evaluating prior at array([0.3062967 , 0.52624583])
2023-07-02 10:34:01,070 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:01,070 [model] Got input parameters: {'Omega_m': 0.3062966987295614, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5262458321581266, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:01,070 [classy] Got parameters {'Omega_m': 0.3062966987295614, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:01,070 [classy] Computing new state
2023-07-02 10:34:01,070 [classy] Setting parameters: {'Omega_m': 0.3062966987295614, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:01,115 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.01124039635167}
2023-07-02 10:34:01,115 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:01,116 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00258666
2023-07-02 10:34:01,116 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5262458321581266, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:01,117 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:01,138 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.18989
2023-07-02 10:34:01,138 [model] Computed derived parameters: {}
2023-07-02 10:34:01,139 [mcmc] New sample, #383:
Omega_m:0.3100915, b1:0.5208796
2023-07-02 10:34:01,139 [model] Posterior to be computed for parameters {'Omega_m': 0.3062966987295614, 'b1': 0.5681512142353196}
2023-07-02 10:34:01,139 [prior] Evaluating prior at array([0.3062967 , 0.56815121])
2023-07-02 10:34:01,139 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:01,139 [model] Got input parameters: {'Omega_m': 0.3062966987295614, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5681512142353196, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:01,139 [classy] Got parameters {'Omega_m': 0.3062966987295614, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:01,139 [classy] Re-using computed results
2023-07-02 10:34:01,139 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.01124039635167}
2023-07-02 10:34:01,139 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:01,139 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5681512142353196, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:01,139 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:01,159 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.14401
2023-07-02 10:34:01,160 [model] Computed derived parameters: {}
2023-07-02 10:34:01,160 [model] Posterior to be computed for parameters {'Omega_m': 0.32180664021827077, 'b1': 0.5043132248910918}
2023-07-02 10:34:01,160 [prior] Evaluating prior at array([0.32180664, 0.50431322])
2023-07-02 10:34:01,160 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:01,160 [model] Got input parameters: {'Omega_m': 0.32180664021827077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5043132248910918, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:01,160 [classy] Got parameters {'Omega_m': 0.32180664021827077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:01,160 [classy] Computing new state
2023-07-02 10:34:01,160 [classy] Setting parameters: {'Omega_m': 0.32180664021827077, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:01,204 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.15300475096248}
2023-07-02 10:34:01,204 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:01,206 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00541032
2023-07-02 10:34:01,206 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5043132248910918, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:01,206 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:01,226 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.95319
2023-07-02 10:34:01,226 [model] Computed derived parameters: {}
2023-07-02 10:34:01,226 [mcmc] New sample, #384:
Omega_m:0.3062967, b1:0.5262458
2023-07-02 10:34:01,226 [model] Posterior to be computed for parameters {'Omega_m': 0.32180664021827077, 'b1': 0.5228490216839586}
2023-07-02 10:34:01,226 [prior] Evaluating prior at array([0.32180664, 0.52284902])
2023-07-02 10:34:01,226 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:01,226 [model] Got input parameters: {'Omega_m': 0.32180664021827077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5228490216839586, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:01,226 [classy] Got parameters {'Omega_m': 0.32180664021827077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:01,226 [classy] Re-using computed results
2023-07-02 10:34:01,226 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.15300475096248}
2023-07-02 10:34:01,226 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:01,226 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5228490216839586, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:01,226 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:01,246 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.72533
2023-07-02 10:34:01,247 [model] Computed derived parameters: {}
2023-07-02 10:34:01,247 [model] Posterior to be computed for parameters {'Omega_m': 0.32634099463032473, 'b1': 0.4979011946070625}
2023-07-02 10:34:01,247 [prior] Evaluating prior at array([0.32634099, 0.49790119])
2023-07-02 10:34:01,247 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:01,247 [model] Got input parameters: {'Omega_m': 0.32634099463032473, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4979011946070625, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:01,247 [classy] Got parameters {'Omega_m': 0.32634099463032473, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:01,247 [classy] Computing new state
2023-07-02 10:34:01,247 [classy] Setting parameters: {'Omega_m': 0.32634099463032473, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:01,290 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.62483476134938}
2023-07-02 10:34:01,291 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:01,292 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0115828
2023-07-02 10:34:01,292 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4979011946070625, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:01,292 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:01,312 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.34868
2023-07-02 10:34:01,313 [model] Computed derived parameters: {}
2023-07-02 10:34:01,313 [mcmc] New sample, #385:
Omega_m:0.3218066, b1:0.5043132
2023-07-02 10:34:01,313 [model] Posterior to be computed for parameters {'Omega_m': 0.32634099463032473, 'b1': 0.5640244243980341}
2023-07-02 10:34:01,313 [prior] Evaluating prior at array([0.32634099, 0.56402442])
2023-07-02 10:34:01,313 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:01,313 [model] Got input parameters: {'Omega_m': 0.32634099463032473, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5640244243980341, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:01,313 [classy] Got parameters {'Omega_m': 0.32634099463032473, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:01,313 [classy] Re-using computed results
2023-07-02 10:34:01,313 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.62483476134938}
2023-07-02 10:34:01,313 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:01,313 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5640244243980341, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:01,313 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:01,332 [fs_likelihood.fslikelihood] Computed log-likelihood = -18.7688
2023-07-02 10:34:01,332 [model] Computed derived parameters: {}
2023-07-02 10:34:01,332 [model] Posterior to be computed for parameters {'Omega_m': 0.3624106644658897, 'b1': 0.446895076799916}
2023-07-02 10:34:01,333 [prior] Evaluating prior at array([0.36241066, 0.44689508])
2023-07-02 10:34:01,333 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:01,333 [model] Got input parameters: {'Omega_m': 0.3624106644658897, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.446895076799916, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:01,333 [classy] Got parameters {'Omega_m': 0.3624106644658897, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:01,333 [classy] Computing new state
2023-07-02 10:34:01,333 [classy] Setting parameters: {'Omega_m': 0.3624106644658897, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:01,377 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.64568997189525}
2023-07-02 10:34:01,377 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:01,379 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.135957
2023-07-02 10:34:01,379 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.446895076799916, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:01,379 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:01,399 [fs_likelihood.fslikelihood] Computed log-likelihood = -10.2864
2023-07-02 10:34:01,399 [model] Computed derived parameters: {}
2023-07-02 10:34:01,399 [model] Posterior to be computed for parameters {'Omega_m': 0.32634099463032473, 'b1': 0.47295512434369624}
2023-07-02 10:34:01,399 [prior] Evaluating prior at array([0.32634099, 0.47295512])
2023-07-02 10:34:01,400 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:01,400 [model] Got input parameters: {'Omega_m': 0.32634099463032473, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47295512434369624, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:01,400 [classy] Got parameters {'Omega_m': 0.32634099463032473, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:01,400 [classy] Re-using computed results
2023-07-02 10:34:01,400 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.62483476134938}
2023-07-02 10:34:01,400 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:01,400 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47295512434369624, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:01,400 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:01,419 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.13413
2023-07-02 10:34:01,419 [model] Computed derived parameters: {}
2023-07-02 10:34:01,420 [mcmc] New sample, #386:
Omega_m:0.326341, b1:0.4979012
2023-07-02 10:34:01,420 [model] Posterior to be computed for parameters {'Omega_m': 0.35378144629416375, 'b1': 0.43415158340118853}
2023-07-02 10:34:01,420 [prior] Evaluating prior at array([0.35378145, 0.43415158])
2023-07-02 10:34:01,420 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:01,420 [model] Got input parameters: {'Omega_m': 0.35378144629416375, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.43415158340118853, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:01,420 [classy] Got parameters {'Omega_m': 0.35378144629416375, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:01,420 [classy] Computing new state
2023-07-02 10:34:01,420 [classy] Setting parameters: {'Omega_m': 0.35378144629416375, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:01,464 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.5635174786093}
2023-07-02 10:34:01,464 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:01,466 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0949359
2023-07-02 10:34:01,466 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.43415158340118853, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:01,466 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:01,486 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.22108
2023-07-02 10:34:01,486 [model] Computed derived parameters: {}
2023-07-02 10:34:01,486 [model] Posterior to be computed for parameters {'Omega_m': 0.32634099463032473, 'b1': 0.4740608036104873}
2023-07-02 10:34:01,486 [prior] Evaluating prior at array([0.32634099, 0.4740608 ])
2023-07-02 10:34:01,486 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:01,486 [model] Got input parameters: {'Omega_m': 0.32634099463032473, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4740608036104873, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:01,486 [classy] Got parameters {'Omega_m': 0.32634099463032473, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:01,486 [classy] Re-using computed results
2023-07-02 10:34:01,486 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.62483476134938}
2023-07-02 10:34:01,487 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:01,487 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4740608036104873, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:01,487 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:01,507 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.17153
2023-07-02 10:34:01,507 [model] Computed derived parameters: {}
2023-07-02 10:34:01,507 [mcmc] New sample, #387:
Omega_m:0.326341, b1:0.4729551
2023-07-02 10:34:01,507 [model] Posterior to be computed for parameters {'Omega_m': 0.3375857085063246, 'b1': 0.4581596544377444}
2023-07-02 10:34:01,507 [prior] Evaluating prior at array([0.33758571, 0.45815965])
2023-07-02 10:34:01,508 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:01,508 [model] Got input parameters: {'Omega_m': 0.3375857085063246, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4581596544377444, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:01,508 [classy] Got parameters {'Omega_m': 0.3375857085063246, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:01,508 [classy] Computing new state
2023-07-02 10:34:01,508 [classy] Setting parameters: {'Omega_m': 0.3375857085063246, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:01,551 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.34305836986834}
2023-07-02 10:34:01,552 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:01,553 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0365528
2023-07-02 10:34:01,554 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4581596544377444, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:01,554 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:01,573 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.357779
2023-07-02 10:34:01,573 [model] Computed derived parameters: {}
2023-07-02 10:34:01,573 [model] Posterior to be computed for parameters {'Omega_m': 0.32634099463032473, 'b1': 0.49489267969220424}
2023-07-02 10:34:01,573 [prior] Evaluating prior at array([0.32634099, 0.49489268])
2023-07-02 10:34:01,573 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:01,573 [model] Got input parameters: {'Omega_m': 0.32634099463032473, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49489267969220424, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:01,573 [classy] Got parameters {'Omega_m': 0.32634099463032473, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:01,573 [classy] Re-using computed results
2023-07-02 10:34:01,573 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.62483476134938}
2023-07-02 10:34:01,573 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:01,573 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49489267969220424, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:01,573 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:01,592 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.62803
2023-07-02 10:34:01,593 [model] Computed derived parameters: {}
2023-07-02 10:34:01,593 [mcmc] New sample, #388:
Omega_m:0.326341, b1:0.4740608
2023-07-02 10:34:01,593 [model] Posterior to be computed for parameters {'Omega_m': 0.34314133607444913, 'b1': 0.4711353179307621}
2023-07-02 10:34:01,593 [prior] Evaluating prior at array([0.34314134, 0.47113532])
2023-07-02 10:34:01,593 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:01,593 [model] Got input parameters: {'Omega_m': 0.34314133607444913, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4711353179307621, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:01,593 [classy] Got parameters {'Omega_m': 0.34314133607444913, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:01,593 [classy] Computing new state
2023-07-02 10:34:01,593 [classy] Setting parameters: {'Omega_m': 0.34314133607444913, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:01,637 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.72397389692074}
2023-07-02 10:34:01,638 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:01,639 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.053719
2023-07-02 10:34:01,639 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4711353179307621, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:01,639 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:01,660 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.30515
2023-07-02 10:34:01,660 [model] Computed derived parameters: {}
2023-07-02 10:34:01,660 [model] Posterior to be computed for parameters {'Omega_m': 0.32634099463032473, 'b1': 0.49251742952574756}
2023-07-02 10:34:01,660 [prior] Evaluating prior at array([0.32634099, 0.49251743])
2023-07-02 10:34:01,660 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:01,660 [model] Got input parameters: {'Omega_m': 0.32634099463032473, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49251742952574756, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:01,660 [classy] Got parameters {'Omega_m': 0.32634099463032473, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:01,660 [classy] Re-using computed results
2023-07-02 10:34:01,660 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.62483476134938}
2023-07-02 10:34:01,660 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:01,660 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49251742952574756, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:01,661 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:01,679 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.8121
2023-07-02 10:34:01,680 [model] Computed derived parameters: {}
2023-07-02 10:34:01,680 [mcmc] New sample, #389:
Omega_m:0.326341, b1:0.4948927
2023-07-02 10:34:01,680 [model] Posterior to be computed for parameters {'Omega_m': 0.3298326384116941, 'b1': 0.48757989627786874}
2023-07-02 10:34:01,680 [prior] Evaluating prior at array([0.32983264, 0.4875799 ])
2023-07-02 10:34:01,680 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:01,680 [model] Got input parameters: {'Omega_m': 0.3298326384116941, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48757989627786874, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:01,680 [classy] Got parameters {'Omega_m': 0.3298326384116941, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:01,680 [classy] Computing new state
2023-07-02 10:34:01,680 [classy] Setting parameters: {'Omega_m': 0.3298326384116941, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:01,725 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.2225851889139}
2023-07-02 10:34:01,725 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:01,727 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0178916
2023-07-02 10:34:01,727 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48757989627786874, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:01,727 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:01,746 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.24088
2023-07-02 10:34:01,746 [model] Computed derived parameters: {}
2023-07-02 10:34:01,746 [model] Posterior to be computed for parameters {'Omega_m': 0.32634099463032473, 'b1': 0.5483764733617812}
2023-07-02 10:34:01,746 [prior] Evaluating prior at array([0.32634099, 0.54837647])
2023-07-02 10:34:01,747 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:01,747 [model] Got input parameters: {'Omega_m': 0.32634099463032473, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5483764733617812, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:01,747 [classy] Got parameters {'Omega_m': 0.32634099463032473, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:01,747 [classy] Re-using computed results
2023-07-02 10:34:01,747 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.62483476134938}
2023-07-02 10:34:01,747 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:01,747 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5483764733617812, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:01,747 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:01,767 [fs_likelihood.fslikelihood] Computed log-likelihood = -11.4689
2023-07-02 10:34:01,767 [model] Computed derived parameters: {}
2023-07-02 10:34:01,767 [model] Posterior to be computed for parameters {'Omega_m': 0.30927079193676327, 'b1': 0.516656402062756}
2023-07-02 10:34:01,767 [prior] Evaluating prior at array([0.30927079, 0.5166564 ])
2023-07-02 10:34:01,767 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:01,767 [model] Got input parameters: {'Omega_m': 0.30927079193676327, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.516656402062756, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:01,767 [classy] Got parameters {'Omega_m': 0.30927079193676327, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:01,767 [classy] Computing new state
2023-07-02 10:34:01,767 [classy] Setting parameters: {'Omega_m': 0.30927079193676327, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:01,811 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.64854361278285}
2023-07-02 10:34:01,812 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:01,813 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000840646
2023-07-02 10:34:01,813 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.516656402062756, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:01,813 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:01,833 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.63063
2023-07-02 10:34:01,833 [model] Computed derived parameters: {}
2023-07-02 10:34:01,833 [mcmc] New sample, #390:
Omega_m:0.326341, b1:0.4925174
2023-07-02 10:34:01,833 [model] Posterior to be computed for parameters {'Omega_m': 0.30927079193676327, 'b1': 0.5340731051513992}
2023-07-02 10:34:01,833 [prior] Evaluating prior at array([0.30927079, 0.53407311])
2023-07-02 10:34:01,833 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:01,833 [model] Got input parameters: {'Omega_m': 0.30927079193676327, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5340731051513992, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:01,833 [classy] Got parameters {'Omega_m': 0.30927079193676327, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:01,833 [classy] Re-using computed results
2023-07-02 10:34:01,833 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.64854361278285}
2023-07-02 10:34:01,833 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:01,833 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5340731051513992, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:01,833 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:01,853 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.23223
2023-07-02 10:34:01,853 [model] Computed derived parameters: {}
2023-07-02 10:34:01,854 [mcmc] New sample, #391:
Omega_m:0.3092708, b1:0.5166564
2023-07-02 10:34:01,854 [model] Posterior to be computed for parameters {'Omega_m': 0.33364597473123825, 'b1': 0.4996041607209782}
2023-07-02 10:34:01,854 [prior] Evaluating prior at array([0.33364597, 0.49960416])
2023-07-02 10:34:01,854 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:01,854 [model] Got input parameters: {'Omega_m': 0.33364597473123825, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4996041607209782, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:01,854 [classy] Got parameters {'Omega_m': 0.33364597473123825, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:01,854 [classy] Computing new state
2023-07-02 10:34:01,854 [classy] Setting parameters: {'Omega_m': 0.33364597473123825, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:01,898 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.78768795442875}
2023-07-02 10:34:01,898 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:01,900 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0262816
2023-07-02 10:34:01,900 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4996041607209782, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:01,900 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:01,920 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.93907
2023-07-02 10:34:01,920 [model] Computed derived parameters: {}
2023-07-02 10:34:01,920 [model] Posterior to be computed for parameters {'Omega_m': 0.30927079193676327, 'b1': 0.5762989093017274}
2023-07-02 10:34:01,920 [prior] Evaluating prior at array([0.30927079, 0.57629891])
2023-07-02 10:34:01,920 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:01,920 [model] Got input parameters: {'Omega_m': 0.30927079193676327, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5762989093017274, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:01,920 [classy] Got parameters {'Omega_m': 0.30927079193676327, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:01,920 [classy] Re-using computed results
2023-07-02 10:34:01,920 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.64854361278285}
2023-07-02 10:34:01,920 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:01,920 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5762989093017274, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:01,921 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:01,940 [fs_likelihood.fslikelihood] Computed log-likelihood = -9.56627
2023-07-02 10:34:01,940 [model] Computed derived parameters: {}
2023-07-02 10:34:01,940 [model] Posterior to be computed for parameters {'Omega_m': 0.3069571317792465, 'b1': 0.5373448518321421}
2023-07-02 10:34:01,940 [prior] Evaluating prior at array([0.30695713, 0.53734485])
2023-07-02 10:34:01,940 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:01,940 [model] Got input parameters: {'Omega_m': 0.3069571317792465, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5373448518321421, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:01,941 [classy] Got parameters {'Omega_m': 0.3069571317792465, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:01,941 [classy] Computing new state
2023-07-02 10:34:01,941 [classy] Setting parameters: {'Omega_m': 0.3069571317792465, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:01,985 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.93043151232916}
2023-07-02 10:34:01,985 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:01,986 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00210168
2023-07-02 10:34:01,987 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5373448518321421, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:01,987 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:02,007 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.16082
2023-07-02 10:34:02,007 [model] Computed derived parameters: {}
2023-07-02 10:34:02,007 [mcmc] New sample, #392:
Omega_m:0.3092708, b1:0.5340731
2023-07-02 10:34:02,007 [model] Posterior to be computed for parameters {'Omega_m': 0.3069571317792465, 'b1': 0.5153848024989736}
2023-07-02 10:34:02,007 [prior] Evaluating prior at array([0.30695713, 0.5153848 ])
2023-07-02 10:34:02,007 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:02,007 [model] Got input parameters: {'Omega_m': 0.3069571317792465, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5153848024989736, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:02,007 [classy] Got parameters {'Omega_m': 0.3069571317792465, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:02,008 [classy] Re-using computed results
2023-07-02 10:34:02,008 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.93043151232916}
2023-07-02 10:34:02,008 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:02,008 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5153848024989736, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:02,008 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:02,029 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.53154
2023-07-02 10:34:02,029 [model] Computed derived parameters: {}
2023-07-02 10:34:02,029 [mcmc] New sample, #393:
Omega_m:0.3069571, b1:0.5373449
2023-07-02 10:34:02,029 [model] Posterior to be computed for parameters {'Omega_m': 0.3327655738089936, 'b1': 0.47888908627563787}
2023-07-02 10:34:02,029 [prior] Evaluating prior at array([0.33276557, 0.47888909])
2023-07-02 10:34:02,029 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:02,029 [model] Got input parameters: {'Omega_m': 0.3327655738089936, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47888908627563787, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:02,029 [classy] Got parameters {'Omega_m': 0.3327655738089936, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:02,029 [classy] Computing new state
2023-07-02 10:34:02,029 [classy] Setting parameters: {'Omega_m': 0.3327655738089936, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:02,074 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.88769621461336}
2023-07-02 10:34:02,074 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:02,076 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0242075
2023-07-02 10:34:02,076 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47888908627563787, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:02,076 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:02,096 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.995321
2023-07-02 10:34:02,096 [model] Computed derived parameters: {}
2023-07-02 10:34:02,096 [model] Posterior to be computed for parameters {'Omega_m': 0.3069571317792465, 'b1': 0.5151205545158337}
2023-07-02 10:34:02,096 [prior] Evaluating prior at array([0.30695713, 0.51512055])
2023-07-02 10:34:02,096 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:02,096 [model] Got input parameters: {'Omega_m': 0.3069571317792465, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5151205545158337, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:02,096 [classy] Got parameters {'Omega_m': 0.3069571317792465, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:02,096 [classy] Re-using computed results
2023-07-02 10:34:02,096 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.93043151232916}
2023-07-02 10:34:02,096 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:02,096 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5151205545158337, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:02,096 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:02,117 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.53196
2023-07-02 10:34:02,117 [model] Computed derived parameters: {}
2023-07-02 10:34:02,117 [mcmc] New sample, #394:
Omega_m:0.3069571, b1:0.5153848
2023-07-02 10:34:02,117 [model] Posterior to be computed for parameters {'Omega_m': 0.29514104408932057, 'b1': 0.5318296833622995}
2023-07-02 10:34:02,117 [prior] Evaluating prior at array([0.29514104, 0.53182968])
2023-07-02 10:34:02,117 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:02,117 [model] Got input parameters: {'Omega_m': 0.29514104408932057, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5318296833622995, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:02,117 [classy] Got parameters {'Omega_m': 0.29514104408932057, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:02,117 [classy] Computing new state
2023-07-02 10:34:02,117 [classy] Setting parameters: {'Omega_m': 0.29514104408932057, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:02,163 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.3998885998488}
2023-07-02 10:34:02,163 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:02,165 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0194741
2023-07-02 10:34:02,165 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5318296833622995, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:02,165 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:02,184 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.412718
2023-07-02 10:34:02,184 [model] Computed derived parameters: {}
2023-07-02 10:34:02,184 [model] Posterior to be computed for parameters {'Omega_m': 0.3069571317792465, 'b1': 0.507175400849865}
2023-07-02 10:34:02,185 [prior] Evaluating prior at array([0.30695713, 0.5071754 ])
2023-07-02 10:34:02,185 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:02,185 [model] Got input parameters: {'Omega_m': 0.3069571317792465, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.507175400849865, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:02,185 [classy] Got parameters {'Omega_m': 0.3069571317792465, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:02,185 [classy] Re-using computed results
2023-07-02 10:34:02,185 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.93043151232916}
2023-07-02 10:34:02,185 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:02,185 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.507175400849865, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:02,185 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:02,204 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.37146
2023-07-02 10:34:02,204 [model] Computed derived parameters: {}
2023-07-02 10:34:02,204 [mcmc] New sample, #395:
Omega_m:0.3069571, b1:0.5151206
2023-07-02 10:34:02,204 [model] Posterior to be computed for parameters {'Omega_m': 0.29850861524975986, 'b1': 0.5191224475337723}
2023-07-02 10:34:02,204 [prior] Evaluating prior at array([0.29850862, 0.51912245])
2023-07-02 10:34:02,204 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:02,204 [model] Got input parameters: {'Omega_m': 0.29850861524975986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5191224475337723, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:02,204 [classy] Got parameters {'Omega_m': 0.29850861524975986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:02,204 [classy] Computing new state
2023-07-02 10:34:02,205 [classy] Setting parameters: {'Omega_m': 0.29850861524975986, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:02,248 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.9758988057451}
2023-07-02 10:34:02,249 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:02,251 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0126084
2023-07-02 10:34:02,251 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5191224475337723, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:02,251 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:02,271 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.921069
2023-07-02 10:34:02,271 [model] Computed derived parameters: {}
2023-07-02 10:34:02,271 [mcmc] New sample, #396:
Omega_m:0.3069571, b1:0.5071754
2023-07-02 10:34:02,271 [model] Posterior to be computed for parameters {'Omega_m': 0.29850861524975986, 'b1': 0.5194416788091566}
2023-07-02 10:34:02,271 [prior] Evaluating prior at array([0.29850862, 0.51944168])
2023-07-02 10:34:02,272 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:02,272 [model] Got input parameters: {'Omega_m': 0.29850861524975986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5194416788091566, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:02,272 [classy] Got parameters {'Omega_m': 0.29850861524975986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:02,272 [classy] Re-using computed results
2023-07-02 10:34:02,272 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.9758988057451}
2023-07-02 10:34:02,272 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:02,272 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5194416788091566, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:02,272 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:02,291 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.9394
2023-07-02 10:34:02,291 [model] Computed derived parameters: {}
2023-07-02 10:34:02,291 [mcmc] New sample, #397:
Omega_m:0.2985086, b1:0.5191224
2023-07-02 10:34:02,292 [model] Posterior to be computed for parameters {'Omega_m': 0.2776255104055501, 'b1': 0.5489724760334908}
2023-07-02 10:34:02,292 [prior] Evaluating prior at array([0.27762551, 0.54897248])
2023-07-02 10:34:02,292 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:02,292 [model] Got input parameters: {'Omega_m': 0.2776255104055501, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5489724760334908, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:02,292 [classy] Got parameters {'Omega_m': 0.2776255104055501, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:02,292 [classy] Computing new state
2023-07-02 10:34:02,292 [classy] Setting parameters: {'Omega_m': 0.2776255104055501, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:02,336 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.6751775939724}
2023-07-02 10:34:02,336 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:02,338 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0817138
2023-07-02 10:34:02,338 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5489724760334908, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:02,338 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:02,358 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.28374
2023-07-02 10:34:02,358 [model] Computed derived parameters: {}
2023-07-02 10:34:02,358 [model] Posterior to be computed for parameters {'Omega_m': 0.29850861524975986, 'b1': 0.5828570092383326}
2023-07-02 10:34:02,358 [prior] Evaluating prior at array([0.29850862, 0.58285701])
2023-07-02 10:34:02,358 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:02,359 [model] Got input parameters: {'Omega_m': 0.29850861524975986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5828570092383326, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:02,359 [classy] Got parameters {'Omega_m': 0.29850861524975986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:02,359 [classy] Re-using computed results
2023-07-02 10:34:02,359 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.9758988057451}
2023-07-02 10:34:02,359 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:02,359 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5828570092383326, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:02,359 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:02,378 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.46582
2023-07-02 10:34:02,378 [model] Computed derived parameters: {}
2023-07-02 10:34:02,379 [model] Posterior to be computed for parameters {'Omega_m': 0.3163930303707986, 'b1': 0.49415132853053656}
2023-07-02 10:34:02,379 [prior] Evaluating prior at array([0.31639303, 0.49415133])
2023-07-02 10:34:02,379 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:02,379 [model] Got input parameters: {'Omega_m': 0.3163930303707986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49415132853053656, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:02,379 [classy] Got parameters {'Omega_m': 0.3163930303707986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:02,379 [classy] Computing new state
2023-07-02 10:34:02,379 [classy] Setting parameters: {'Omega_m': 0.3163930303707986, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:02,423 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.79235206554358}
2023-07-02 10:34:02,423 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:02,425 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00113043
2023-07-02 10:34:02,425 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49415132853053656, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:02,425 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:02,444 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.88248
2023-07-02 10:34:02,444 [model] Computed derived parameters: {}
2023-07-02 10:34:02,445 [mcmc] New sample, #398:
Omega_m:0.2985086, b1:0.5194417
2023-07-02 10:34:02,445 [model] Posterior to be computed for parameters {'Omega_m': 0.3163930303707986, 'b1': 0.45995741762883807}
2023-07-02 10:34:02,445 [prior] Evaluating prior at array([0.31639303, 0.45995742])
2023-07-02 10:34:02,445 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:02,445 [model] Got input parameters: {'Omega_m': 0.3163930303707986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45995741762883807, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:02,445 [classy] Got parameters {'Omega_m': 0.3163930303707986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:02,445 [classy] Re-using computed results
2023-07-02 10:34:02,445 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.79235206554358}
2023-07-02 10:34:02,445 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:02,445 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45995741762883807, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:02,445 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:02,465 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.806045
2023-07-02 10:34:02,465 [model] Computed derived parameters: {}
2023-07-02 10:34:02,465 [model] Posterior to be computed for parameters {'Omega_m': 0.29572736309142833, 'b1': 0.5233746473083404}
2023-07-02 10:34:02,465 [prior] Evaluating prior at array([0.29572736, 0.52337465])
2023-07-02 10:34:02,465 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:02,465 [model] Got input parameters: {'Omega_m': 0.29572736309142833, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5233746473083404, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:02,465 [classy] Got parameters {'Omega_m': 0.29572736309142833, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:02,465 [classy] Computing new state
2023-07-02 10:34:02,465 [classy] Setting parameters: {'Omega_m': 0.29572736309142833, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:02,509 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.32576712333324}
2023-07-02 10:34:02,509 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:02,512 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0181659
2023-07-02 10:34:02,512 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5233746473083404, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:02,512 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:02,531 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.24131
2023-07-02 10:34:02,531 [model] Computed derived parameters: {}
2023-07-02 10:34:02,531 [model] Posterior to be computed for parameters {'Omega_m': 0.3163930303707986, 'b1': 0.4652973365539925}
2023-07-02 10:34:02,531 [prior] Evaluating prior at array([0.31639303, 0.46529734])
2023-07-02 10:34:02,532 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:02,532 [model] Got input parameters: {'Omega_m': 0.3163930303707986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4652973365539925, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:02,532 [classy] Got parameters {'Omega_m': 0.3163930303707986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:02,532 [classy] Re-using computed results
2023-07-02 10:34:02,532 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.79235206554358}
2023-07-02 10:34:02,532 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:02,532 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4652973365539925, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:02,532 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:02,551 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.155575
2023-07-02 10:34:02,551 [model] Computed derived parameters: {}
2023-07-02 10:34:02,551 [model] Posterior to be computed for parameters {'Omega_m': 0.32621898852460657, 'b1': 0.4802564417337894}
2023-07-02 10:34:02,551 [prior] Evaluating prior at array([0.32621899, 0.48025644])
2023-07-02 10:34:02,551 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:02,551 [model] Got input parameters: {'Omega_m': 0.32621898852460657, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4802564417337894, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:02,551 [classy] Got parameters {'Omega_m': 0.32621898852460657, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:02,551 [classy] Computing new state
2023-07-02 10:34:02,551 [classy] Setting parameters: {'Omega_m': 0.32621898852460657, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:02,595 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.63896155274264}
2023-07-02 10:34:02,596 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:02,597 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0113865
2023-07-02 10:34:02,597 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4802564417337894, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:02,597 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:02,618 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.274
2023-07-02 10:34:02,618 [model] Computed derived parameters: {}
2023-07-02 10:34:02,618 [model] Posterior to be computed for parameters {'Omega_m': 0.3163930303707986, 'b1': 0.47251288564438876}
2023-07-02 10:34:02,618 [prior] Evaluating prior at array([0.31639303, 0.47251289])
2023-07-02 10:34:02,618 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:02,618 [model] Got input parameters: {'Omega_m': 0.3163930303707986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47251288564438876, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:02,619 [classy] Got parameters {'Omega_m': 0.3163930303707986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:02,619 [classy] Re-using computed results
2023-07-02 10:34:02,619 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.79235206554358}
2023-07-02 10:34:02,619 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:02,619 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47251288564438876, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:02,619 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:02,638 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.23337
2023-07-02 10:34:02,638 [model] Computed derived parameters: {}
2023-07-02 10:34:02,638 [model] Posterior to be computed for parameters {'Omega_m': 0.30163674124987483, 'b1': 0.5150181960324958}
2023-07-02 10:34:02,638 [prior] Evaluating prior at array([0.30163674, 0.5150182 ])
2023-07-02 10:34:02,638 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:02,638 [model] Got input parameters: {'Omega_m': 0.30163674124987483, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5150181960324958, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:02,638 [classy] Got parameters {'Omega_m': 0.30163674124987483, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:02,638 [classy] Computing new state
2023-07-02 10:34:02,638 [classy] Setting parameters: {'Omega_m': 0.30163674124987483, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:02,683 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.58580014591882}
2023-07-02 10:34:02,683 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:02,685 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00761678
2023-07-02 10:34:02,685 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5150181960324958, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:02,685 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:02,705 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.59043
2023-07-02 10:34:02,705 [model] Computed derived parameters: {}
2023-07-02 10:34:02,705 [model] Posterior to be computed for parameters {'Omega_m': 0.3163930303707986, 'b1': 0.526007633647398}
2023-07-02 10:34:02,705 [prior] Evaluating prior at array([0.31639303, 0.52600763])
2023-07-02 10:34:02,705 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:02,705 [model] Got input parameters: {'Omega_m': 0.3163930303707986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.526007633647398, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:02,705 [classy] Got parameters {'Omega_m': 0.3163930303707986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:02,705 [classy] Re-using computed results
2023-07-02 10:34:02,705 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.79235206554358}
2023-07-02 10:34:02,705 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:02,705 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.526007633647398, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:02,705 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:02,726 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.712257
2023-07-02 10:34:02,726 [model] Computed derived parameters: {}
2023-07-02 10:34:02,726 [model] Posterior to be computed for parameters {'Omega_m': 0.30629227855963836, 'b1': 0.5084348010205674}
2023-07-02 10:34:02,726 [prior] Evaluating prior at array([0.30629228, 0.5084348 ])
2023-07-02 10:34:02,726 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:02,726 [model] Got input parameters: {'Omega_m': 0.30629227855963836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5084348010205674, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:02,726 [classy] Got parameters {'Omega_m': 0.30629227855963836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:02,726 [classy] Computing new state
2023-07-02 10:34:02,726 [classy] Setting parameters: {'Omega_m': 0.30629227855963836, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:02,770 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.01178131470812}
2023-07-02 10:34:02,770 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:02,772 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00259009
2023-07-02 10:34:02,772 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5084348010205674, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:02,772 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:02,791 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.3061
2023-07-02 10:34:02,791 [model] Computed derived parameters: {}
2023-07-02 10:34:02,791 [mcmc] New sample, #399:
Omega_m:0.316393, b1:0.4941513
2023-07-02 10:34:02,792 [model] Posterior to be computed for parameters {'Omega_m': 0.30629227855963836, 'b1': 0.47395597949394064}
2023-07-02 10:34:02,792 [prior] Evaluating prior at array([0.30629228, 0.47395598])
2023-07-02 10:34:02,792 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:02,792 [model] Got input parameters: {'Omega_m': 0.30629227855963836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47395597949394064, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:02,792 [classy] Got parameters {'Omega_m': 0.30629227855963836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:02,792 [classy] Re-using computed results
2023-07-02 10:34:02,792 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.01178131470812}
2023-07-02 10:34:02,792 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:02,792 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47395597949394064, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:02,792 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:02,811 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.09902
2023-07-02 10:34:02,811 [model] Computed derived parameters: {}
2023-07-02 10:34:02,811 [model] Posterior to be computed for parameters {'Omega_m': 0.3028074554373338, 'b1': 0.513362689174899}
2023-07-02 10:34:02,811 [prior] Evaluating prior at array([0.30280746, 0.51336269])
2023-07-02 10:34:02,812 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:02,812 [model] Got input parameters: {'Omega_m': 0.3028074554373338, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.513362689174899, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:02,812 [classy] Got parameters {'Omega_m': 0.3028074554373338, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:02,812 [classy] Computing new state
2023-07-02 10:34:02,812 [classy] Setting parameters: {'Omega_m': 0.3028074554373338, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:02,856 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.4407275791473}
2023-07-02 10:34:02,856 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:02,858 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00608537
2023-07-02 10:34:02,858 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.513362689174899, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:02,858 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:02,878 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.79847
2023-07-02 10:34:02,878 [model] Computed derived parameters: {}
2023-07-02 10:34:02,878 [model] Posterior to be computed for parameters {'Omega_m': 0.30629227855963836, 'b1': 0.5189580995967357}
2023-07-02 10:34:02,878 [prior] Evaluating prior at array([0.30629228, 0.5189581 ])
2023-07-02 10:34:02,878 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:02,879 [model] Got input parameters: {'Omega_m': 0.30629227855963836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5189580995967357, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:02,879 [classy] Got parameters {'Omega_m': 0.30629227855963836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:02,879 [classy] Re-using computed results
2023-07-02 10:34:02,879 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.01178131470812}
2023-07-02 10:34:02,879 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:02,879 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5189580995967357, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:02,879 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:02,898 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.44347
2023-07-02 10:34:02,899 [model] Computed derived parameters: {}
2023-07-02 10:34:02,899 [mcmc] New sample, #400:
Omega_m:0.3062923, b1:0.5084348
2023-07-02 10:34:02,899 [mcmc] Learn + convergence test @ 400 samples accepted.
2023-07-02 10:34:02,899 [mcmc] Ready to check convergence and learn a new proposal covmat
2023-07-02 10:34:02,904 [mcmc] - Acceptance rate: 0.397
2023-07-02 10:34:02,904 [mcmc] - Condition number = 8.94406
2023-07-02 10:34:02,904 [mcmc] - Eigenvalues = array([0.00573545, 0.05129817])
2023-07-02 10:34:02,904 [mcmc] - Convergence of means: R-1 = 0.051298 after 320 accepted steps
2023-07-02 10:34:02,904 [mcmc] - Updated covariance matrix of proposal pdf.
2023-07-02 10:34:02,904 [mcmc] array([[ 9.22576354e-05, -1.28600163e-04],
[-1.28600163e-04, 3.31754404e-04]])
2023-07-02 10:34:02,915 [mcmc] Dumped checkpoint and progress info, and current covmat.
2023-07-02 10:34:02,915 [model] Posterior to be computed for parameters {'Omega_m': 0.31017443128197053, 'b1': 0.5135466724413341}
2023-07-02 10:34:02,915 [prior] Evaluating prior at array([0.31017443, 0.51354667])
2023-07-02 10:34:02,915 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:02,915 [model] Got input parameters: {'Omega_m': 0.31017443128197053, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5135466724413341, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:02,915 [classy] Got parameters {'Omega_m': 0.31017443128197053, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:02,915 [classy] Computing new state
2023-07-02 10:34:02,915 [classy] Setting parameters: {'Omega_m': 0.31017443128197053, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:02,960 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.53895190519492}
2023-07-02 10:34:02,960 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:02,962 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000531381
2023-07-02 10:34:02,962 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5135466724413341, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:02,962 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:02,983 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.72914
2023-07-02 10:34:02,983 [model] Computed derived parameters: {}
2023-07-02 10:34:02,983 [mcmc] New sample, #401:
Omega_m:0.3062923, b1:0.5189581
2023-07-02 10:34:02,983 [model] Posterior to be computed for parameters {'Omega_m': 0.31017443128197053, 'b1': 0.5575680079258327}
2023-07-02 10:34:02,983 [prior] Evaluating prior at array([0.31017443, 0.55756801])
2023-07-02 10:34:02,983 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:02,983 [model] Got input parameters: {'Omega_m': 0.31017443128197053, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5575680079258327, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:02,984 [classy] Got parameters {'Omega_m': 0.31017443128197053, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:02,984 [classy] Re-using computed results
2023-07-02 10:34:02,984 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.53895190519492}
2023-07-02 10:34:02,984 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:02,984 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5575680079258327, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:02,984 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:03,003 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.82942
2023-07-02 10:34:03,003 [model] Computed derived parameters: {}
2023-07-02 10:34:03,004 [model] Posterior to be computed for parameters {'Omega_m': 0.3218555963834205, 'b1': 0.4972640121345697}
2023-07-02 10:34:03,004 [prior] Evaluating prior at array([0.3218556 , 0.49726401])
2023-07-02 10:34:03,004 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:03,004 [model] Got input parameters: {'Omega_m': 0.3218555963834205, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4972640121345697, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:03,004 [classy] Got parameters {'Omega_m': 0.3218555963834205, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:03,004 [classy] Computing new state
2023-07-02 10:34:03,004 [classy] Setting parameters: {'Omega_m': 0.3218555963834205, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:03,049 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.14726683867943}
2023-07-02 10:34:03,049 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:03,050 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00546453
2023-07-02 10:34:03,051 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4972640121345697, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:03,051 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:03,071 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.4442
2023-07-02 10:34:03,071 [model] Computed derived parameters: {}
2023-07-02 10:34:03,071 [mcmc] New sample, #402:
Omega_m:0.3101744, b1:0.5135467
2023-07-02 10:34:03,071 [model] Posterior to be computed for parameters {'Omega_m': 0.3218555963834205, 'b1': 0.6015576710679337}
2023-07-02 10:34:03,071 [prior] Evaluating prior at array([0.3218556 , 0.60155767])
2023-07-02 10:34:03,071 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:03,071 [model] Got input parameters: {'Omega_m': 0.3218555963834205, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6015576710679337, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:03,071 [classy] Got parameters {'Omega_m': 0.3218555963834205, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:03,072 [classy] Re-using computed results
2023-07-02 10:34:03,072 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.14726683867943}
2023-07-02 10:34:03,072 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:03,072 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6015576710679337, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:03,072 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:03,091 [fs_likelihood.fslikelihood] Computed log-likelihood = -36.5354
2023-07-02 10:34:03,091 [model] Computed derived parameters: {}
2023-07-02 10:34:03,091 [model] Posterior to be computed for parameters {'Omega_m': 0.3304105002249723, 'b1': 0.4853391234784089}
2023-07-02 10:34:03,091 [prior] Evaluating prior at array([0.3304105 , 0.48533912])
2023-07-02 10:34:03,091 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:03,091 [model] Got input parameters: {'Omega_m': 0.3304105002249723, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4853391234784089, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:03,091 [classy] Got parameters {'Omega_m': 0.3304105002249723, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:03,091 [classy] Computing new state
2023-07-02 10:34:03,091 [classy] Setting parameters: {'Omega_m': 0.3304105002249723, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:03,139 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.15639222109297}
2023-07-02 10:34:03,139 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:03,140 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0190632
2023-07-02 10:34:03,141 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4853391234784089, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:03,141 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:03,160 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.24262
2023-07-02 10:34:03,160 [model] Computed derived parameters: {}
2023-07-02 10:34:03,161 [model] Posterior to be computed for parameters {'Omega_m': 0.3218555963834205, 'b1': 0.5380688891278057}
2023-07-02 10:34:03,161 [prior] Evaluating prior at array([0.3218556 , 0.53806889])
2023-07-02 10:34:03,161 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:03,161 [model] Got input parameters: {'Omega_m': 0.3218555963834205, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5380688891278057, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:03,161 [classy] Got parameters {'Omega_m': 0.3218555963834205, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:03,161 [classy] Re-using computed results
2023-07-02 10:34:03,161 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.14726683867943}
2023-07-02 10:34:03,161 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:03,161 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5380688891278057, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:03,161 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:03,182 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.49411
2023-07-02 10:34:03,182 [model] Computed derived parameters: {}
2023-07-02 10:34:03,182 [model] Posterior to be computed for parameters {'Omega_m': 0.2157161208066216, 'b1': 0.6452144101424373}
2023-07-02 10:34:03,182 [prior] Evaluating prior at array([0.21571612, 0.64521441])
2023-07-02 10:34:03,182 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:03,182 [model] Got input parameters: {'Omega_m': 0.2157161208066216, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6452144101424373, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:03,182 [classy] Got parameters {'Omega_m': 0.2157161208066216, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:03,182 [classy] Computing new state
2023-07-02 10:34:03,182 [classy] Setting parameters: {'Omega_m': 0.2157161208066216, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:03,226 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 160.82231608225342}
2023-07-02 10:34:03,226 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:03,228 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.749984
2023-07-02 10:34:03,228 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6452144101424373, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:03,228 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:03,247 [fs_likelihood.fslikelihood] Computed log-likelihood = -82.9647
2023-07-02 10:34:03,247 [model] Computed derived parameters: {}
2023-07-02 10:34:03,248 [model] Posterior to be computed for parameters {'Omega_m': 0.3218555963834205, 'b1': 0.5331885403459865}
2023-07-02 10:34:03,248 [prior] Evaluating prior at array([0.3218556 , 0.53318854])
2023-07-02 10:34:03,248 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:03,248 [model] Got input parameters: {'Omega_m': 0.3218555963834205, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5331885403459865, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:03,248 [classy] Got parameters {'Omega_m': 0.3218555963834205, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:03,248 [classy] Re-using computed results
2023-07-02 10:34:03,248 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.14726683867943}
2023-07-02 10:34:03,248 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:03,248 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5331885403459865, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:03,248 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:03,267 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.13703
2023-07-02 10:34:03,267 [model] Computed derived parameters: {}
2023-07-02 10:34:03,267 [model] Posterior to be computed for parameters {'Omega_m': 0.29615937932145253, 'b1': 0.5330825944382281}
2023-07-02 10:34:03,267 [prior] Evaluating prior at array([0.29615938, 0.53308259])
2023-07-02 10:34:03,268 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:03,268 [model] Got input parameters: {'Omega_m': 0.29615937932145253, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5330825944382281, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:03,268 [classy] Got parameters {'Omega_m': 0.29615937932145253, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:03,268 [classy] Computing new state
2023-07-02 10:34:03,268 [classy] Setting parameters: {'Omega_m': 0.29615937932145253, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:03,312 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.27123176153495}
2023-07-02 10:34:03,312 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:03,314 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0172325
2023-07-02 10:34:03,314 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5330825944382281, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:03,314 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:03,335 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.714806
2023-07-02 10:34:03,335 [model] Computed derived parameters: {}
2023-07-02 10:34:03,335 [mcmc] New sample, #403:
Omega_m:0.3218556, b1:0.497264
2023-07-02 10:34:03,335 [model] Posterior to be computed for parameters {'Omega_m': 0.29615937932145253, 'b1': 0.5346933179969885}
2023-07-02 10:34:03,335 [prior] Evaluating prior at array([0.29615938, 0.53469332])
2023-07-02 10:34:03,335 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:03,335 [model] Got input parameters: {'Omega_m': 0.29615937932145253, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5346933179969885, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:03,335 [classy] Got parameters {'Omega_m': 0.29615937932145253, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:03,335 [classy] Re-using computed results
2023-07-02 10:34:03,335 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.27123176153495}
2023-07-02 10:34:03,335 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:03,335 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5346933179969885, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:03,335 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:03,355 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.720472
2023-07-02 10:34:03,355 [model] Computed derived parameters: {}
2023-07-02 10:34:03,355 [mcmc] New sample, #404:
Omega_m:0.2961594, b1:0.5330826
2023-07-02 10:34:03,355 [model] Posterior to be computed for parameters {'Omega_m': 0.3471174283873723, 'b1': 0.46366165329319864}
2023-07-02 10:34:03,355 [prior] Evaluating prior at array([0.34711743, 0.46366165])
2023-07-02 10:34:03,355 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:03,355 [model] Got input parameters: {'Omega_m': 0.3471174283873723, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46366165329319864, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:03,355 [classy] Got parameters {'Omega_m': 0.3471174283873723, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:03,355 [classy] Computing new state
2023-07-02 10:34:03,355 [classy] Setting parameters: {'Omega_m': 0.3471174283873723, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:03,399 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.2865128906438}
2023-07-02 10:34:03,400 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:03,401 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0678676
2023-07-02 10:34:03,401 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46366165329319864, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:03,401 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:03,421 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.37284
2023-07-02 10:34:03,421 [model] Computed derived parameters: {}
2023-07-02 10:34:03,421 [model] Posterior to be computed for parameters {'Omega_m': 0.29615937932145253, 'b1': 0.5273613487766589}
2023-07-02 10:34:03,421 [prior] Evaluating prior at array([0.29615938, 0.52736135])
2023-07-02 10:34:03,422 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:03,422 [model] Got input parameters: {'Omega_m': 0.29615937932145253, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5273613487766589, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:03,422 [classy] Got parameters {'Omega_m': 0.29615937932145253, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:03,422 [classy] Re-using computed results
2023-07-02 10:34:03,422 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.27123176153495}
2023-07-02 10:34:03,422 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:03,422 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5273613487766589, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:03,422 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:03,441 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.584704
2023-07-02 10:34:03,441 [model] Computed derived parameters: {}
2023-07-02 10:34:03,442 [mcmc] New sample, #405:
Omega_m:0.2961594, b1:0.5346933
2023-07-02 10:34:03,442 [model] Posterior to be computed for parameters {'Omega_m': 0.25207010974626076, 'b1': 0.5888184545902818}
2023-07-02 10:34:03,442 [prior] Evaluating prior at array([0.25207011, 0.58881845])
2023-07-02 10:34:03,442 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:03,442 [model] Got input parameters: {'Omega_m': 0.25207010974626076, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5888184545902818, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:03,442 [classy] Got parameters {'Omega_m': 0.25207010974626076, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:03,442 [classy] Computing new state
2023-07-02 10:34:03,442 [classy] Setting parameters: {'Omega_m': 0.25207010974626076, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:03,486 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 155.22467187139597}
2023-07-02 10:34:03,486 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:03,488 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.262812
2023-07-02 10:34:03,488 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5888184545902818, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:03,488 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:03,508 [fs_likelihood.fslikelihood] Computed log-likelihood = -27.6965
2023-07-02 10:34:03,508 [model] Computed derived parameters: {}
2023-07-02 10:34:03,508 [model] Posterior to be computed for parameters {'Omega_m': 0.29615937932145253, 'b1': 0.5098061155898931}
2023-07-02 10:34:03,508 [prior] Evaluating prior at array([0.29615938, 0.50980612])
2023-07-02 10:34:03,508 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:03,508 [model] Got input parameters: {'Omega_m': 0.29615937932145253, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5098061155898931, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:03,509 [classy] Got parameters {'Omega_m': 0.29615937932145253, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:03,509 [classy] Re-using computed results
2023-07-02 10:34:03,509 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.27123176153495}
2023-07-02 10:34:03,509 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:03,509 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5098061155898931, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:03,509 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:03,529 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.85939
2023-07-02 10:34:03,529 [model] Computed derived parameters: {}
2023-07-02 10:34:03,529 [mcmc] New sample, #406:
Omega_m:0.2961594, b1:0.5273613
2023-07-02 10:34:03,529 [model] Posterior to be computed for parameters {'Omega_m': 0.31369469783500453, 'b1': 0.4853632083758137}
2023-07-02 10:34:03,529 [prior] Evaluating prior at array([0.3136947 , 0.48536321])
2023-07-02 10:34:03,529 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:03,529 [model] Got input parameters: {'Omega_m': 0.31369469783500453, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4853632083758137, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:03,529 [classy] Got parameters {'Omega_m': 0.31369469783500453, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:03,529 [classy] Computing new state
2023-07-02 10:34:03,530 [classy] Setting parameters: {'Omega_m': 0.31369469783500453, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:03,573 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.11468551525564}
2023-07-02 10:34:03,573 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:03,576 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000292036
2023-07-02 10:34:03,576 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4853632083758137, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:03,576 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:03,595 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.11708
2023-07-02 10:34:03,595 [model] Computed derived parameters: {}
2023-07-02 10:34:03,595 [mcmc] New sample, #407:
Omega_m:0.2961594, b1:0.5098061
2023-07-02 10:34:03,595 [model] Posterior to be computed for parameters {'Omega_m': 0.31369469783500453, 'b1': 0.48668802781481163}
2023-07-02 10:34:03,596 [prior] Evaluating prior at array([0.3136947 , 0.48668803])
2023-07-02 10:34:03,596 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:03,596 [model] Got input parameters: {'Omega_m': 0.31369469783500453, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48668802781481163, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:03,596 [classy] Got parameters {'Omega_m': 0.31369469783500453, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:03,596 [classy] Re-using computed results
2023-07-02 10:34:03,596 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.11468551525564}
2023-07-02 10:34:03,596 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:03,596 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48668802781481163, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:03,596 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:03,616 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.2332
2023-07-02 10:34:03,616 [model] Computed derived parameters: {}
2023-07-02 10:34:03,616 [mcmc] New sample, #408:
Omega_m:0.3136947, b1:0.4853632
2023-07-02 10:34:03,616 [model] Posterior to be computed for parameters {'Omega_m': 0.2942025589156645, 'b1': 0.5138585946135361}
2023-07-02 10:34:03,616 [prior] Evaluating prior at array([0.29420256, 0.51385859])
2023-07-02 10:34:03,616 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:03,616 [model] Got input parameters: {'Omega_m': 0.2942025589156645, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5138585946135361, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:03,616 [classy] Got parameters {'Omega_m': 0.2942025589156645, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:03,616 [classy] Computing new state
2023-07-02 10:34:03,616 [classy] Setting parameters: {'Omega_m': 0.2942025589156645, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:03,660 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.5187925439928}
2023-07-02 10:34:03,660 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:03,662 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.021668
2023-07-02 10:34:03,662 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5138585946135361, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:03,662 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:03,682 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.29218
2023-07-02 10:34:03,682 [model] Computed derived parameters: {}
2023-07-02 10:34:03,682 [model] Posterior to be computed for parameters {'Omega_m': 0.31369469783500453, 'b1': 0.4709718881406779}
2023-07-02 10:34:03,682 [prior] Evaluating prior at array([0.3136947 , 0.47097189])
2023-07-02 10:34:03,683 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:03,683 [model] Got input parameters: {'Omega_m': 0.31369469783500453, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4709718881406779, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:03,683 [classy] Got parameters {'Omega_m': 0.31369469783500453, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:03,683 [classy] Re-using computed results
2023-07-02 10:34:03,683 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.11468551525564}
2023-07-02 10:34:03,683 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:03,683 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4709718881406779, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:03,683 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:03,702 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.285769
2023-07-02 10:34:03,703 [model] Computed derived parameters: {}
2023-07-02 10:34:03,703 [mcmc] New sample, #409:
Omega_m:0.3136947, b1:0.486688
2023-07-02 10:34:03,703 [model] Posterior to be computed for parameters {'Omega_m': 0.33479531142120156, 'b1': 0.44155922936011693}
2023-07-02 10:34:03,703 [prior] Evaluating prior at array([0.33479531, 0.44155923])
2023-07-02 10:34:03,703 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:03,703 [model] Got input parameters: {'Omega_m': 0.33479531142120156, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44155922936011693, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:03,703 [classy] Got parameters {'Omega_m': 0.33479531142120156, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:03,703 [classy] Computing new state
2023-07-02 10:34:03,703 [classy] Setting parameters: {'Omega_m': 0.33479531142120156, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:03,747 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.65748851699811}
2023-07-02 10:34:03,747 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:03,749 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0291117
2023-07-02 10:34:03,749 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44155922936011693, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:03,749 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:03,769 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.469883
2023-07-02 10:34:03,769 [model] Computed derived parameters: {}
2023-07-02 10:34:03,769 [model] Posterior to be computed for parameters {'Omega_m': 0.31369469783500453, 'b1': 0.47282664608364716}
2023-07-02 10:34:03,769 [prior] Evaluating prior at array([0.3136947 , 0.47282665])
2023-07-02 10:34:03,769 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:03,769 [model] Got input parameters: {'Omega_m': 0.31369469783500453, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47282664608364716, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:03,769 [classy] Got parameters {'Omega_m': 0.31369469783500453, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:03,769 [classy] Re-using computed results
2023-07-02 10:34:03,769 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.11468551525564}
2023-07-02 10:34:03,769 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:03,769 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47282664608364716, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:03,769 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:03,789 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.579532
2023-07-02 10:34:03,789 [model] Computed derived parameters: {}
2023-07-02 10:34:03,789 [mcmc] New sample, #410:
Omega_m:0.3136947, b1:0.4709719
2023-07-02 10:34:03,789 [model] Posterior to be computed for parameters {'Omega_m': 0.33172923829776163, 'b1': 0.44768786124554727}
2023-07-02 10:34:03,790 [prior] Evaluating prior at array([0.33172924, 0.44768786])
2023-07-02 10:34:03,790 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:03,790 [model] Got input parameters: {'Omega_m': 0.33172923829776163, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44768786124554727, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:03,790 [classy] Got parameters {'Omega_m': 0.33172923829776163, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:03,790 [classy] Computing new state
2023-07-02 10:34:03,790 [classy] Setting parameters: {'Omega_m': 0.33172923829776163, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:03,834 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.00572306219476}
2023-07-02 10:34:03,834 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:03,835 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.021871
2023-07-02 10:34:03,836 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44768786124554727, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:03,836 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:03,855 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.158559
2023-07-02 10:34:03,855 [model] Computed derived parameters: {}
2023-07-02 10:34:03,855 [model] Posterior to be computed for parameters {'Omega_m': 0.31369469783500453, 'b1': 0.4850288391223774}
2023-07-02 10:34:03,855 [prior] Evaluating prior at array([0.3136947 , 0.48502884])
2023-07-02 10:34:03,855 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:03,855 [model] Got input parameters: {'Omega_m': 0.31369469783500453, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4850288391223774, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:03,855 [classy] Got parameters {'Omega_m': 0.31369469783500453, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:03,855 [classy] Re-using computed results
2023-07-02 10:34:03,855 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.11468551525564}
2023-07-02 10:34:03,855 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:03,856 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4850288391223774, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:03,856 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:03,875 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.08635
2023-07-02 10:34:03,875 [model] Computed derived parameters: {}
2023-07-02 10:34:03,875 [mcmc] New sample, #411:
Omega_m:0.3136947, b1:0.4728266
2023-07-02 10:34:03,875 [model] Posterior to be computed for parameters {'Omega_m': 0.28708113506643673, 'b1': 0.5221261319309135}
2023-07-02 10:34:03,875 [prior] Evaluating prior at array([0.28708114, 0.52212613])
2023-07-02 10:34:03,875 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:03,875 [model] Got input parameters: {'Omega_m': 0.28708113506643673, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5221261319309135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:03,875 [classy] Got parameters {'Omega_m': 0.28708113506643673, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:03,875 [classy] Computing new state
2023-07-02 10:34:03,875 [classy] Setting parameters: {'Omega_m': 0.28708113506643673, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:03,919 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.43194687538517}
2023-07-02 10:34:03,920 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:03,921 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0424211
2023-07-02 10:34:03,922 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5221261319309135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:03,922 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:03,942 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.19147
2023-07-02 10:34:03,942 [model] Computed derived parameters: {}
2023-07-02 10:34:03,942 [model] Posterior to be computed for parameters {'Omega_m': 0.31369469783500453, 'b1': 0.47018105076464906}
2023-07-02 10:34:03,942 [prior] Evaluating prior at array([0.3136947 , 0.47018105])
2023-07-02 10:34:03,943 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:03,943 [model] Got input parameters: {'Omega_m': 0.31369469783500453, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47018105076464906, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:03,943 [classy] Got parameters {'Omega_m': 0.31369469783500453, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:03,943 [classy] Re-using computed results
2023-07-02 10:34:03,943 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.11468551525564}
2023-07-02 10:34:03,943 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:03,943 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47018105076464906, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:03,943 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:03,962 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.1554
2023-07-02 10:34:03,962 [model] Computed derived parameters: {}
2023-07-02 10:34:03,962 [model] Posterior to be computed for parameters {'Omega_m': 0.3325018231474168, 'b1': 0.4588131294607831}
2023-07-02 10:34:03,962 [prior] Evaluating prior at array([0.33250182, 0.45881313])
2023-07-02 10:34:03,962 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:03,963 [model] Got input parameters: {'Omega_m': 0.3325018231474168, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4588131294607831, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:03,963 [classy] Got parameters {'Omega_m': 0.3325018231474168, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:03,963 [classy] Computing new state
2023-07-02 10:34:03,963 [classy] Setting parameters: {'Omega_m': 0.3325018231474168, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:04,007 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.9177020218677}
2023-07-02 10:34:04,007 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:04,009 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0236021
2023-07-02 10:34:04,009 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4588131294607831, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,009 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:04,028 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.10002
2023-07-02 10:34:04,028 [model] Computed derived parameters: {}
2023-07-02 10:34:04,028 [mcmc] New sample, #412:
Omega_m:0.3136947, b1:0.4850288
2023-07-02 10:34:04,028 [model] Posterior to be computed for parameters {'Omega_m': 0.3325018231474168, 'b1': 0.49525029698126866}
2023-07-02 10:34:04,028 [prior] Evaluating prior at array([0.33250182, 0.4952503 ])
2023-07-02 10:34:04,029 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:04,029 [model] Got input parameters: {'Omega_m': 0.3325018231474168, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49525029698126866, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,029 [classy] Got parameters {'Omega_m': 0.3325018231474168, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:04,029 [classy] Re-using computed results
2023-07-02 10:34:04,029 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.9177020218677}
2023-07-02 10:34:04,029 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:04,029 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49525029698126866, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,029 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:04,049 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.633015
2023-07-02 10:34:04,049 [model] Computed derived parameters: {}
2023-07-02 10:34:04,049 [model] Posterior to be computed for parameters {'Omega_m': 0.3336984615857981, 'b1': 0.45714510602023084}
2023-07-02 10:34:04,049 [prior] Evaluating prior at array([0.33369846, 0.45714511])
2023-07-02 10:34:04,050 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:04,050 [model] Got input parameters: {'Omega_m': 0.3336984615857981, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45714510602023084, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,050 [classy] Got parameters {'Omega_m': 0.3336984615857981, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:04,050 [classy] Computing new state
2023-07-02 10:34:04,050 [classy] Setting parameters: {'Omega_m': 0.3336984615857981, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:04,094 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.781732909058}
2023-07-02 10:34:04,094 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:04,096 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0264079
2023-07-02 10:34:04,096 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45714510602023084, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,096 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:04,116 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.910473
2023-07-02 10:34:04,116 [model] Computed derived parameters: {}
2023-07-02 10:34:04,116 [model] Posterior to be computed for parameters {'Omega_m': 0.3325018231474168, 'b1': 0.4499738188870939}
2023-07-02 10:34:04,116 [prior] Evaluating prior at array([0.33250182, 0.44997382])
2023-07-02 10:34:04,116 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:04,116 [model] Got input parameters: {'Omega_m': 0.3325018231474168, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4499738188870939, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,116 [classy] Got parameters {'Omega_m': 0.3325018231474168, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:04,116 [classy] Re-using computed results
2023-07-02 10:34:04,116 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.9177020218677}
2023-07-02 10:34:04,116 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:04,116 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4499738188870939, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,116 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:04,139 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.426352
2023-07-02 10:34:04,139 [model] Computed derived parameters: {}
2023-07-02 10:34:04,139 [model] Posterior to be computed for parameters {'Omega_m': 0.2894712871703308, 'b1': 0.5187944407467544}
2023-07-02 10:34:04,139 [prior] Evaluating prior at array([0.28947129, 0.51879444])
2023-07-02 10:34:04,139 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:04,139 [model] Got input parameters: {'Omega_m': 0.2894712871703308, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5187944407467544, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,139 [classy] Got parameters {'Omega_m': 0.2894712871703308, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:04,139 [classy] Computing new state
2023-07-02 10:34:04,140 [classy] Setting parameters: {'Omega_m': 0.2894712871703308, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:04,184 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.12330670930834}
2023-07-02 10:34:04,184 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:04,185 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0346354
2023-07-02 10:34:04,186 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5187944407467544, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,186 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:04,205 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.20028
2023-07-02 10:34:04,205 [model] Computed derived parameters: {}
2023-07-02 10:34:04,205 [model] Posterior to be computed for parameters {'Omega_m': 0.3325018231474168, 'b1': 0.46032603935392774}
2023-07-02 10:34:04,205 [prior] Evaluating prior at array([0.33250182, 0.46032604])
2023-07-02 10:34:04,205 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:04,205 [model] Got input parameters: {'Omega_m': 0.3325018231474168, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46032603935392774, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,205 [classy] Got parameters {'Omega_m': 0.3325018231474168, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:04,205 [classy] Re-using computed results
2023-07-02 10:34:04,206 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.9177020218677}
2023-07-02 10:34:04,206 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:04,206 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46032603935392774, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,206 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:04,225 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.17402
2023-07-02 10:34:04,225 [model] Computed derived parameters: {}
2023-07-02 10:34:04,225 [mcmc] New sample, #413:
Omega_m:0.3325018, b1:0.4588131
2023-07-02 10:34:04,225 [model] Posterior to be computed for parameters {'Omega_m': 0.33611141766540426, 'b1': 0.4552945377125158}
2023-07-02 10:34:04,225 [prior] Evaluating prior at array([0.33611142, 0.45529454])
2023-07-02 10:34:04,225 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:04,225 [model] Got input parameters: {'Omega_m': 0.33611141766540426, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4552945377125158, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,225 [classy] Got parameters {'Omega_m': 0.33611141766540426, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:04,225 [classy] Computing new state
2023-07-02 10:34:04,225 [classy] Setting parameters: {'Omega_m': 0.33611141766540426, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:04,269 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.50889172454458}
2023-07-02 10:34:04,269 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:04,271 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0325213
2023-07-02 10:34:04,271 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4552945377125158, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,271 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:04,291 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.548363
2023-07-02 10:34:04,292 [model] Computed derived parameters: {}
2023-07-02 10:34:04,292 [model] Posterior to be computed for parameters {'Omega_m': 0.3325018231474168, 'b1': 0.47424111391339085}
2023-07-02 10:34:04,292 [prior] Evaluating prior at array([0.33250182, 0.47424111])
2023-07-02 10:34:04,292 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:04,292 [model] Got input parameters: {'Omega_m': 0.3325018231474168, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47424111391339085, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,292 [classy] Got parameters {'Omega_m': 0.3325018231474168, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:04,292 [classy] Re-using computed results
2023-07-02 10:34:04,292 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.9177020218677}
2023-07-02 10:34:04,292 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:04,292 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47424111391339085, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,292 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:04,312 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.27417
2023-07-02 10:34:04,312 [model] Computed derived parameters: {}
2023-07-02 10:34:04,312 [mcmc] New sample, #414:
Omega_m:0.3325018, b1:0.460326
2023-07-02 10:34:04,312 [model] Posterior to be computed for parameters {'Omega_m': 0.3276120072437892, 'b1': 0.4810571472996067}
2023-07-02 10:34:04,312 [prior] Evaluating prior at array([0.32761201, 0.48105715])
2023-07-02 10:34:04,312 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:04,312 [model] Got input parameters: {'Omega_m': 0.3276120072437892, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4810571472996067, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,312 [classy] Got parameters {'Omega_m': 0.3276120072437892, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:04,313 [classy] Computing new state
2023-07-02 10:34:04,313 [classy] Setting parameters: {'Omega_m': 0.3276120072437892, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:04,357 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.47796346563553}
2023-07-02 10:34:04,357 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:04,359 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0137248
2023-07-02 10:34:04,359 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4810571472996067, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,359 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:04,379 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.06864
2023-07-02 10:34:04,379 [model] Computed derived parameters: {}
2023-07-02 10:34:04,379 [mcmc] New sample, #415:
Omega_m:0.3325018, b1:0.4742411
2023-07-02 10:34:04,379 [model] Posterior to be computed for parameters {'Omega_m': 0.3276120072437892, 'b1': 0.4690397551553866}
2023-07-02 10:34:04,379 [prior] Evaluating prior at array([0.32761201, 0.46903976])
2023-07-02 10:34:04,379 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:04,379 [model] Got input parameters: {'Omega_m': 0.3276120072437892, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4690397551553866, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,379 [classy] Got parameters {'Omega_m': 0.3276120072437892, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:04,379 [classy] Re-using computed results
2023-07-02 10:34:04,380 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.47796346563553}
2023-07-02 10:34:04,380 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:04,380 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4690397551553866, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,380 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:04,400 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.91142
2023-07-02 10:34:04,400 [model] Computed derived parameters: {}
2023-07-02 10:34:04,400 [mcmc] New sample, #416:
Omega_m:0.327612, b1:0.4810571
2023-07-02 10:34:04,401 [model] Posterior to be computed for parameters {'Omega_m': 0.328201062498136, 'b1': 0.4682186567011533}
2023-07-02 10:34:04,401 [prior] Evaluating prior at array([0.32820106, 0.46821866])
2023-07-02 10:34:04,401 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:04,401 [model] Got input parameters: {'Omega_m': 0.328201062498136, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4682186567011533, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,401 [classy] Got parameters {'Omega_m': 0.328201062498136, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:04,401 [classy] Computing new state
2023-07-02 10:34:04,401 [classy] Setting parameters: {'Omega_m': 0.328201062498136, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:04,446 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.41006973419633}
2023-07-02 10:34:04,446 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:04,448 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0147777
2023-07-02 10:34:04,448 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4682186567011533, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,448 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:04,468 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.84466
2023-07-02 10:34:04,468 [model] Computed derived parameters: {}
2023-07-02 10:34:04,468 [mcmc] New sample, #417:
Omega_m:0.327612, b1:0.4690398
2023-07-02 10:34:04,468 [model] Posterior to be computed for parameters {'Omega_m': 0.328201062498136, 'b1': 0.5211384272590601}
2023-07-02 10:34:04,468 [prior] Evaluating prior at array([0.32820106, 0.52113843])
2023-07-02 10:34:04,468 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:04,468 [model] Got input parameters: {'Omega_m': 0.328201062498136, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5211384272590601, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,468 [classy] Got parameters {'Omega_m': 0.328201062498136, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:04,468 [classy] Re-using computed results
2023-07-02 10:34:04,468 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.41006973419633}
2023-07-02 10:34:04,468 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:04,468 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5211384272590601, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,468 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:04,490 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.68378
2023-07-02 10:34:04,490 [model] Computed derived parameters: {}
2023-07-02 10:34:04,490 [model] Posterior to be computed for parameters {'Omega_m': 0.3169489977851921, 'b1': 0.4839031835338281}
2023-07-02 10:34:04,490 [prior] Evaluating prior at array([0.316949 , 0.48390318])
2023-07-02 10:34:04,491 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:04,491 [model] Got input parameters: {'Omega_m': 0.3169489977851921, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4839031835338281, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,491 [classy] Got parameters {'Omega_m': 0.3169489977851921, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:04,491 [classy] Computing new state
2023-07-02 10:34:04,491 [classy] Setting parameters: {'Omega_m': 0.3169489977851921, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:04,536 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.72624883210472}
2023-07-02 10:34:04,536 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:04,539 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00141142
2023-07-02 10:34:04,539 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4839031835338281, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,539 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:04,560 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.46536
2023-07-02 10:34:04,560 [model] Computed derived parameters: {}
2023-07-02 10:34:04,560 [mcmc] New sample, #418:
Omega_m:0.3282011, b1:0.4682187
2023-07-02 10:34:04,560 [model] Posterior to be computed for parameters {'Omega_m': 0.3169489977851921, 'b1': 0.450033837881795}
2023-07-02 10:34:04,560 [prior] Evaluating prior at array([0.316949 , 0.45003384])
2023-07-02 10:34:04,561 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:04,561 [model] Got input parameters: {'Omega_m': 0.3169489977851921, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.450033837881795, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,561 [classy] Got parameters {'Omega_m': 0.3169489977851921, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:04,561 [classy] Re-using computed results
2023-07-02 10:34:04,561 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.72624883210472}
2023-07-02 10:34:04,561 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:04,561 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.450033837881795, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,561 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:04,581 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.72717
2023-07-02 10:34:04,581 [model] Computed derived parameters: {}
2023-07-02 10:34:04,581 [model] Posterior to be computed for parameters {'Omega_m': 0.32589804097134906, 'b1': 0.47142889445348024}
2023-07-02 10:34:04,581 [prior] Evaluating prior at array([0.32589804, 0.47142889])
2023-07-02 10:34:04,581 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:04,581 [model] Got input parameters: {'Omega_m': 0.32589804097134906, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47142889445348024, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,581 [classy] Got parameters {'Omega_m': 0.32589804097134906, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:04,581 [classy] Computing new state
2023-07-02 10:34:04,581 [classy] Setting parameters: {'Omega_m': 0.32589804097134906, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:04,626 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.67614014801873}
2023-07-02 10:34:04,626 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:04,628 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0108782
2023-07-02 10:34:04,628 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47142889445348024, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,628 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:04,648 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.08489
2023-07-02 10:34:04,648 [model] Computed derived parameters: {}
2023-07-02 10:34:04,648 [mcmc] New sample, #419:
Omega_m:0.316949, b1:0.4839032
2023-07-02 10:34:04,648 [model] Posterior to be computed for parameters {'Omega_m': 0.32589804097134906, 'b1': 0.5137782996889283}
2023-07-02 10:34:04,648 [prior] Evaluating prior at array([0.32589804, 0.5137783 ])
2023-07-02 10:34:04,649 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:04,649 [model] Got input parameters: {'Omega_m': 0.32589804097134906, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5137782996889283, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,649 [classy] Got parameters {'Omega_m': 0.32589804097134906, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:04,649 [classy] Re-using computed results
2023-07-02 10:34:04,649 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.67614014801873}
2023-07-02 10:34:04,649 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:04,649 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5137782996889283, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,649 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:04,668 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.792217
2023-07-02 10:34:04,668 [model] Computed derived parameters: {}
2023-07-02 10:34:04,668 [model] Posterior to be computed for parameters {'Omega_m': 0.31637086296363076, 'b1': 0.48470905973104295}
2023-07-02 10:34:04,668 [prior] Evaluating prior at array([0.31637086, 0.48470906])
2023-07-02 10:34:04,669 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:04,669 [model] Got input parameters: {'Omega_m': 0.31637086296363076, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48470905973104295, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,669 [classy] Got parameters {'Omega_m': 0.31637086296363076, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:04,669 [classy] Computing new state
2023-07-02 10:34:04,669 [classy] Setting parameters: {'Omega_m': 0.31637086296363076, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:04,714 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.79499221964272}
2023-07-02 10:34:04,714 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:04,716 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00111996
2023-07-02 10:34:04,716 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48470905973104295, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,716 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:04,735 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.45826
2023-07-02 10:34:04,736 [model] Computed derived parameters: {}
2023-07-02 10:34:04,736 [mcmc] New sample, #420:
Omega_m:0.325898, b1:0.4714289
2023-07-02 10:34:04,736 [model] Posterior to be computed for parameters {'Omega_m': 0.31637086296363076, 'b1': 0.48312182821580857}
2023-07-02 10:34:04,736 [prior] Evaluating prior at array([0.31637086, 0.48312183])
2023-07-02 10:34:04,736 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:04,736 [model] Got input parameters: {'Omega_m': 0.31637086296363076, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48312182821580857, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,736 [classy] Got parameters {'Omega_m': 0.31637086296363076, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:04,736 [classy] Re-using computed results
2023-07-02 10:34:04,736 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.79499221964272}
2023-07-02 10:34:04,736 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:04,736 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48312182821580857, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,736 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:04,756 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.34126
2023-07-02 10:34:04,756 [model] Computed derived parameters: {}
2023-07-02 10:34:04,756 [mcmc] New sample, #421:
Omega_m:0.3163709, b1:0.4847091
2023-07-02 10:34:04,756 [model] Posterior to be computed for parameters {'Omega_m': 0.3083662635758382, 'b1': 0.4942796341017114}
2023-07-02 10:34:04,756 [prior] Evaluating prior at array([0.30836626, 0.49427963])
2023-07-02 10:34:04,757 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:04,757 [model] Got input parameters: {'Omega_m': 0.3083662635758382, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4942796341017114, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,757 [classy] Got parameters {'Omega_m': 0.3083662635758382, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:04,757 [classy] Computing new state
2023-07-02 10:34:04,757 [classy] Setting parameters: {'Omega_m': 0.3083662635758382, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:04,801 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.7585251002326}
2023-07-02 10:34:04,801 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:04,803 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00125294
2023-07-02 10:34:04,803 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4942796341017114, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,803 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:04,822 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.794
2023-07-02 10:34:04,822 [model] Computed derived parameters: {}
2023-07-02 10:34:04,822 [model] Posterior to be computed for parameters {'Omega_m': 0.31637086296363076, 'b1': 0.4737469066584642}
2023-07-02 10:34:04,822 [prior] Evaluating prior at array([0.31637086, 0.47374691])
2023-07-02 10:34:04,823 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:04,823 [model] Got input parameters: {'Omega_m': 0.31637086296363076, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4737469066584642, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,823 [classy] Got parameters {'Omega_m': 0.31637086296363076, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:04,823 [classy] Re-using computed results
2023-07-02 10:34:04,823 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.79499221964272}
2023-07-02 10:34:04,823 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:04,823 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4737469066584642, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,823 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:04,843 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.3871
2023-07-02 10:34:04,843 [model] Computed derived parameters: {}
2023-07-02 10:34:04,843 [model] Posterior to be computed for parameters {'Omega_m': 0.2934834937149975, 'b1': 0.5150250891965752}
2023-07-02 10:34:04,843 [prior] Evaluating prior at array([0.29348349, 0.51502509])
2023-07-02 10:34:04,843 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:04,843 [model] Got input parameters: {'Omega_m': 0.2934834937149975, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5150250891965752, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,843 [classy] Got parameters {'Omega_m': 0.2934834937149975, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:04,843 [classy] Computing new state
2023-07-02 10:34:04,843 [classy] Setting parameters: {'Omega_m': 0.2934834937149975, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:04,887 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.61012445332122}
2023-07-02 10:34:04,887 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:04,889 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0234329
2023-07-02 10:34:04,889 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5150250891965752, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,889 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:04,909 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.50512
2023-07-02 10:34:04,909 [model] Computed derived parameters: {}
2023-07-02 10:34:04,909 [model] Posterior to be computed for parameters {'Omega_m': 0.31637086296363076, 'b1': 0.5371521561629854}
2023-07-02 10:34:04,909 [prior] Evaluating prior at array([0.31637086, 0.53715216])
2023-07-02 10:34:04,910 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:04,910 [model] Got input parameters: {'Omega_m': 0.31637086296363076, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5371521561629854, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,910 [classy] Got parameters {'Omega_m': 0.31637086296363076, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:04,910 [classy] Re-using computed results
2023-07-02 10:34:04,910 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.79499221964272}
2023-07-02 10:34:04,910 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:04,910 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5371521561629854, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,910 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:04,929 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.41567
2023-07-02 10:34:04,929 [model] Computed derived parameters: {}
2023-07-02 10:34:04,929 [model] Posterior to be computed for parameters {'Omega_m': 0.33604736747089414, 'b1': 0.4556942697373722}
2023-07-02 10:34:04,929 [prior] Evaluating prior at array([0.33604737, 0.45569427])
2023-07-02 10:34:04,929 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:04,929 [model] Got input parameters: {'Omega_m': 0.33604736747089414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4556942697373722, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,930 [classy] Got parameters {'Omega_m': 0.33604736747089414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:04,930 [classy] Computing new state
2023-07-02 10:34:04,930 [classy] Setting parameters: {'Omega_m': 0.33604736747089414, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:04,974 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.51610835098884}
2023-07-02 10:34:04,974 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:04,976 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0323514
2023-07-02 10:34:04,976 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4556942697373722, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,976 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:04,996 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.571823
2023-07-02 10:34:04,996 [model] Computed derived parameters: {}
2023-07-02 10:34:04,997 [mcmc] New sample, #422:
Omega_m:0.3163709, b1:0.4831218
2023-07-02 10:34:04,997 [model] Posterior to be computed for parameters {'Omega_m': 0.33604736747089414, 'b1': 0.4223908499530782}
2023-07-02 10:34:04,997 [prior] Evaluating prior at array([0.33604737, 0.42239085])
2023-07-02 10:34:04,997 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:04,997 [model] Got input parameters: {'Omega_m': 0.33604736747089414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4223908499530782, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,997 [classy] Got parameters {'Omega_m': 0.33604736747089414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:04,997 [classy] Re-using computed results
2023-07-02 10:34:04,997 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.51610835098884}
2023-07-02 10:34:04,997 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:04,997 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4223908499530782, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:04,997 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:05,016 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.49459
2023-07-02 10:34:05,017 [model] Computed derived parameters: {}
2023-07-02 10:34:05,017 [model] Posterior to be computed for parameters {'Omega_m': 0.32777508261564975, 'b1': 0.46722520891072716}
2023-07-02 10:34:05,017 [prior] Evaluating prior at array([0.32777508, 0.46722521])
2023-07-02 10:34:05,017 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:05,017 [model] Got input parameters: {'Omega_m': 0.32777508261564975, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46722520891072716, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:05,017 [classy] Got parameters {'Omega_m': 0.32777508261564975, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:05,017 [classy] Computing new state
2023-07-02 10:34:05,017 [classy] Setting parameters: {'Omega_m': 0.32777508261564975, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:05,061 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.45915602990453}
2023-07-02 10:34:05,061 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:05,063 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0140125
2023-07-02 10:34:05,063 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46722520891072716, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:05,063 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:05,082 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.81509
2023-07-02 10:34:05,083 [model] Computed derived parameters: {}
2023-07-02 10:34:05,083 [mcmc] New sample, #423:
Omega_m:0.3360474, b1:0.4556943
2023-07-02 10:34:05,083 [model] Posterior to be computed for parameters {'Omega_m': 0.32777508261564975, 'b1': 0.5099399218688974}
2023-07-02 10:34:05,083 [prior] Evaluating prior at array([0.32777508, 0.50993992])
2023-07-02 10:34:05,083 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:05,083 [model] Got input parameters: {'Omega_m': 0.32777508261564975, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5099399218688974, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:05,083 [classy] Got parameters {'Omega_m': 0.32777508261564975, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:05,083 [classy] Re-using computed results
2023-07-02 10:34:05,083 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.45915602990453}
2023-07-02 10:34:05,083 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:05,083 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5099399218688974, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:05,083 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:05,103 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.942709
2023-07-02 10:34:05,103 [model] Computed derived parameters: {}
2023-07-02 10:34:05,104 [model] Posterior to be computed for parameters {'Omega_m': 0.35809088608210493, 'b1': 0.424967272695987}
2023-07-02 10:34:05,104 [prior] Evaluating prior at array([0.35809089, 0.42496727])
2023-07-02 10:34:05,104 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:05,104 [model] Got input parameters: {'Omega_m': 0.35809088608210493, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.424967272695987, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:05,104 [classy] Got parameters {'Omega_m': 0.35809088608210493, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:05,104 [classy] Computing new state
2023-07-02 10:34:05,104 [classy] Setting parameters: {'Omega_m': 0.35809088608210493, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:05,150 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.10258903764918}
2023-07-02 10:34:05,151 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:05,152 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.114603
2023-07-02 10:34:05,152 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.424967272695987, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:05,153 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:05,172 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.7109
2023-07-02 10:34:05,172 [model] Computed derived parameters: {}
2023-07-02 10:34:05,172 [model] Posterior to be computed for parameters {'Omega_m': 0.32777508261564975, 'b1': 0.48630417432039663}
2023-07-02 10:34:05,172 [prior] Evaluating prior at array([0.32777508, 0.48630417])
2023-07-02 10:34:05,172 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:05,172 [model] Got input parameters: {'Omega_m': 0.32777508261564975, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48630417432039663, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:05,172 [classy] Got parameters {'Omega_m': 0.32777508261564975, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:05,172 [classy] Re-using computed results
2023-07-02 10:34:05,172 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.45915602990453}
2023-07-02 10:34:05,172 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:05,172 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48630417432039663, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:05,172 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:05,191 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.85339
2023-07-02 10:34:05,191 [model] Computed derived parameters: {}
2023-07-02 10:34:05,191 [mcmc] New sample, #424:
Omega_m:0.3277751, b1:0.4672252
2023-07-02 10:34:05,191 [model] Posterior to be computed for parameters {'Omega_m': 0.3425830189674795, 'b1': 0.46566303147488514}
2023-07-02 10:34:05,191 [prior] Evaluating prior at array([0.34258302, 0.46566303])
2023-07-02 10:34:05,192 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:05,192 [model] Got input parameters: {'Omega_m': 0.3425830189674795, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46566303147488514, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:05,192 [classy] Got parameters {'Omega_m': 0.3425830189674795, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:05,192 [classy] Computing new state
2023-07-02 10:34:05,192 [classy] Setting parameters: {'Omega_m': 0.3425830189674795, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:05,236 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.78577393074937}
2023-07-02 10:34:05,236 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:05,238 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0518552
2023-07-02 10:34:05,238 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46566303147488514, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:05,238 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:05,258 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.47966
2023-07-02 10:34:05,258 [model] Computed derived parameters: {}
2023-07-02 10:34:05,258 [model] Posterior to be computed for parameters {'Omega_m': 0.32777508261564975, 'b1': 0.5763700021532966}
2023-07-02 10:34:05,258 [prior] Evaluating prior at array([0.32777508, 0.57637 ])
2023-07-02 10:34:05,258 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:05,259 [model] Got input parameters: {'Omega_m': 0.32777508261564975, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5763700021532966, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:05,259 [classy] Got parameters {'Omega_m': 0.32777508261564975, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:05,259 [classy] Re-using computed results
2023-07-02 10:34:05,259 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.45915602990453}
2023-07-02 10:34:05,259 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:05,259 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5763700021532966, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:05,259 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:05,278 [fs_likelihood.fslikelihood] Computed log-likelihood = -27.5378
2023-07-02 10:34:05,278 [model] Computed derived parameters: {}
2023-07-02 10:34:05,278 [model] Posterior to be computed for parameters {'Omega_m': 0.31312902878619187, 'b1': 0.5067196651784145}
2023-07-02 10:34:05,278 [prior] Evaluating prior at array([0.31312903, 0.50671967])
2023-07-02 10:34:05,279 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:05,279 [model] Got input parameters: {'Omega_m': 0.31312902878619187, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5067196651784145, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:05,279 [classy] Got parameters {'Omega_m': 0.31312902878619187, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:05,279 [classy] Computing new state
2023-07-02 10:34:05,279 [classy] Setting parameters: {'Omega_m': 0.31312902878619187, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:05,324 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.1825790993551}
2023-07-02 10:34:05,324 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:05,325 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000227853
2023-07-02 10:34:05,325 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5067196651784145, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:05,325 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:05,345 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.87872
2023-07-02 10:34:05,345 [model] Computed derived parameters: {}
2023-07-02 10:34:05,345 [mcmc] New sample, #425:
Omega_m:0.3277751, b1:0.4863042
2023-07-02 10:34:05,345 [model] Posterior to be computed for parameters {'Omega_m': 0.31312902878619187, 'b1': 0.5295502551689203}
2023-07-02 10:34:05,345 [prior] Evaluating prior at array([0.31312903, 0.52955026])
2023-07-02 10:34:05,345 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:05,345 [model] Got input parameters: {'Omega_m': 0.31312902878619187, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5295502551689203, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:05,345 [classy] Got parameters {'Omega_m': 0.31312902878619187, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:05,346 [classy] Re-using computed results
2023-07-02 10:34:05,346 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.1825790993551}
2023-07-02 10:34:05,346 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:05,346 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5295502551689203, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:05,346 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:05,366 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.06376
2023-07-02 10:34:05,366 [model] Computed derived parameters: {}
2023-07-02 10:34:05,366 [model] Posterior to be computed for parameters {'Omega_m': 0.32429834429198673, 'b1': 0.49115048447936255}
2023-07-02 10:34:05,366 [prior] Evaluating prior at array([0.32429834, 0.49115048])
2023-07-02 10:34:05,366 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:05,366 [model] Got input parameters: {'Omega_m': 0.32429834429198673, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49115048447936255, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:05,366 [classy] Got parameters {'Omega_m': 0.32429834429198673, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:05,366 [classy] Computing new state
2023-07-02 10:34:05,366 [classy] Setting parameters: {'Omega_m': 0.32429834429198673, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:05,411 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.86195116969452}
2023-07-02 10:34:05,411 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:05,413 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00851573
2023-07-02 10:34:05,413 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49115048447936255, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:05,413 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:05,432 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.31677
2023-07-02 10:34:05,432 [model] Computed derived parameters: {}
2023-07-02 10:34:05,433 [mcmc] New sample, #426:
Omega_m:0.313129, b1:0.5067197
2023-07-02 10:34:05,433 [model] Posterior to be computed for parameters {'Omega_m': 0.32429834429198673, 'b1': 0.48479078979105206}
2023-07-02 10:34:05,433 [prior] Evaluating prior at array([0.32429834, 0.48479079])
2023-07-02 10:34:05,433 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:05,433 [model] Got input parameters: {'Omega_m': 0.32429834429198673, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48479078979105206, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:05,433 [classy] Got parameters {'Omega_m': 0.32429834429198673, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:05,433 [classy] Re-using computed results
2023-07-02 10:34:05,433 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.86195116969452}
2023-07-02 10:34:05,433 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:05,433 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48479078979105206, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:05,433 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:05,453 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.47338
2023-07-02 10:34:05,453 [model] Computed derived parameters: {}
2023-07-02 10:34:05,453 [mcmc] New sample, #427:
Omega_m:0.3242983, b1:0.4911505
2023-07-02 10:34:05,453 [model] Posterior to be computed for parameters {'Omega_m': 0.3014323398031338, 'b1': 0.5166642699132299}
2023-07-02 10:34:05,453 [prior] Evaluating prior at array([0.30143234, 0.51666427])
2023-07-02 10:34:05,453 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:05,453 [model] Got input parameters: {'Omega_m': 0.3014323398031338, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5166642699132299, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:05,453 [classy] Got parameters {'Omega_m': 0.3014323398031338, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:05,453 [classy] Computing new state
2023-07-02 10:34:05,454 [classy] Setting parameters: {'Omega_m': 0.3014323398031338, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:05,497 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.6111806003106}
2023-07-02 10:34:05,497 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:05,499 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00790283
2023-07-02 10:34:05,499 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5166642699132299, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:05,499 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:05,519 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.61623
2023-07-02 10:34:05,520 [model] Computed derived parameters: {}
2023-07-02 10:34:05,520 [model] Posterior to be computed for parameters {'Omega_m': 0.32429834429198673, 'b1': 0.47656639997746075}
2023-07-02 10:34:05,520 [prior] Evaluating prior at array([0.32429834, 0.4765664 ])
2023-07-02 10:34:05,520 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:05,520 [model] Got input parameters: {'Omega_m': 0.32429834429198673, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47656639997746075, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:05,520 [classy] Got parameters {'Omega_m': 0.32429834429198673, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:05,520 [classy] Re-using computed results
2023-07-02 10:34:05,520 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.86195116969452}
2023-07-02 10:34:05,520 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:05,520 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47656639997746075, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:05,520 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:05,539 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.34907
2023-07-02 10:34:05,539 [model] Computed derived parameters: {}
2023-07-02 10:34:05,539 [mcmc] New sample, #428:
Omega_m:0.3242983, b1:0.4847908
2023-07-02 10:34:05,539 [model] Posterior to be computed for parameters {'Omega_m': 0.3360538096699194, 'b1': 0.46018017070714184}
2023-07-02 10:34:05,539 [prior] Evaluating prior at array([0.33605381, 0.46018017])
2023-07-02 10:34:05,539 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:05,539 [model] Got input parameters: {'Omega_m': 0.3360538096699194, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46018017070714184, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:05,539 [classy] Got parameters {'Omega_m': 0.3360538096699194, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:05,539 [classy] Computing new state
2023-07-02 10:34:05,539 [classy] Setting parameters: {'Omega_m': 0.3360538096699194, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:05,583 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.5153848597415}
2023-07-02 10:34:05,584 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:05,585 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0323683
2023-07-02 10:34:05,585 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46018017070714184, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:05,585 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:05,605 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.675345
2023-07-02 10:34:05,606 [model] Computed derived parameters: {}
2023-07-02 10:34:05,606 [model] Posterior to be computed for parameters {'Omega_m': 0.32429834429198673, 'b1': 0.44185797451107567}
2023-07-02 10:34:05,606 [prior] Evaluating prior at array([0.32429834, 0.44185797])
2023-07-02 10:34:05,606 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:05,606 [model] Got input parameters: {'Omega_m': 0.32429834429198673, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44185797451107567, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:05,606 [classy] Got parameters {'Omega_m': 0.32429834429198673, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:05,606 [classy] Re-using computed results
2023-07-02 10:34:05,606 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.86195116969452}
2023-07-02 10:34:05,606 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:05,606 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44185797451107567, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:05,606 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:05,626 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.03735
2023-07-02 10:34:05,626 [model] Computed derived parameters: {}
2023-07-02 10:34:05,626 [model] Posterior to be computed for parameters {'Omega_m': 0.3220460171658156, 'b1': 0.4797059735710746}
2023-07-02 10:34:05,626 [prior] Evaluating prior at array([0.32204602, 0.47970597])
2023-07-02 10:34:05,626 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:05,626 [model] Got input parameters: {'Omega_m': 0.3220460171658156, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4797059735710746, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:05,626 [classy] Got parameters {'Omega_m': 0.3220460171658156, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:05,626 [classy] Computing new state
2023-07-02 10:34:05,626 [classy] Setting parameters: {'Omega_m': 0.3220460171658156, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:05,671 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.12495502141198}
2023-07-02 10:34:05,671 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:05,672 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00567803
2023-07-02 10:34:05,673 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4797059735710746, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:05,673 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:05,692 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.50397
2023-07-02 10:34:05,692 [model] Computed derived parameters: {}
2023-07-02 10:34:05,692 [mcmc] New sample, #429:
Omega_m:0.3242983, b1:0.4765664
2023-07-02 10:34:05,692 [model] Posterior to be computed for parameters {'Omega_m': 0.3220460171658156, 'b1': 0.4908066089867971}
2023-07-02 10:34:05,692 [prior] Evaluating prior at array([0.32204602, 0.49080661])
2023-07-02 10:34:05,692 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:05,692 [model] Got input parameters: {'Omega_m': 0.3220460171658156, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4908066089867971, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:05,692 [classy] Got parameters {'Omega_m': 0.3220460171658156, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:05,692 [classy] Re-using computed results
2023-07-02 10:34:05,692 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.12495502141198}
2023-07-02 10:34:05,692 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:05,692 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4908066089867971, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:05,692 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:05,713 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.64146
2023-07-02 10:34:05,713 [model] Computed derived parameters: {}
2023-07-02 10:34:05,713 [mcmc] New sample, #430:
Omega_m:0.322046, b1:0.479706
2023-07-02 10:34:05,713 [model] Posterior to be computed for parameters {'Omega_m': 0.32222984978187114, 'b1': 0.4905503602295422}
2023-07-02 10:34:05,713 [prior] Evaluating prior at array([0.32222985, 0.49055036])
2023-07-02 10:34:05,714 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:05,714 [model] Got input parameters: {'Omega_m': 0.32222984978187114, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4905503602295422, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:05,714 [classy] Got parameters {'Omega_m': 0.32222984978187114, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:05,714 [classy] Computing new state
2023-07-02 10:34:05,714 [classy] Setting parameters: {'Omega_m': 0.32222984978187114, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:05,758 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.10342687864693}
2023-07-02 10:34:05,758 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:05,760 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00588806
2023-07-02 10:34:05,760 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4905503602295422, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:05,760 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:05,779 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.62634
2023-07-02 10:34:05,779 [model] Computed derived parameters: {}
2023-07-02 10:34:05,779 [mcmc] New sample, #431:
Omega_m:0.322046, b1:0.4908066
2023-07-02 10:34:05,779 [model] Posterior to be computed for parameters {'Omega_m': 0.32222984978187114, 'b1': 0.4386008599452459}
2023-07-02 10:34:05,779 [prior] Evaluating prior at array([0.32222985, 0.43860086])
2023-07-02 10:34:05,780 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:05,780 [model] Got input parameters: {'Omega_m': 0.32222984978187114, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4386008599452459, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:05,780 [classy] Got parameters {'Omega_m': 0.32222984978187114, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:05,780 [classy] Re-using computed results
2023-07-02 10:34:05,780 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.10342687864693}
2023-07-02 10:34:05,780 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:05,780 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4386008599452459, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:05,780 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:05,799 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.4526
2023-07-02 10:34:05,799 [model] Computed derived parameters: {}
2023-07-02 10:34:05,799 [model] Posterior to be computed for parameters {'Omega_m': 0.31001672479907816, 'b1': 0.5075745323606417}
2023-07-02 10:34:05,799 [prior] Evaluating prior at array([0.31001672, 0.50757453])
2023-07-02 10:34:05,799 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:05,799 [model] Got input parameters: {'Omega_m': 0.31001672479907816, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5075745323606417, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:05,799 [classy] Got parameters {'Omega_m': 0.31001672479907816, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:05,799 [classy] Computing new state
2023-07-02 10:34:05,799 [classy] Setting parameters: {'Omega_m': 0.31001672479907816, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:05,844 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.55805680382596}
2023-07-02 10:34:05,844 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:05,845 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000577993
2023-07-02 10:34:05,846 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5075745323606417, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:05,846 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:05,866 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.76395
2023-07-02 10:34:05,866 [model] Computed derived parameters: {}
2023-07-02 10:34:05,866 [mcmc] New sample, #432:
Omega_m:0.3222298, b1:0.4905504
2023-07-02 10:34:05,866 [model] Posterior to be computed for parameters {'Omega_m': 0.31001672479907816, 'b1': 0.5143342659358193}
2023-07-02 10:34:05,866 [prior] Evaluating prior at array([0.31001672, 0.51433427])
2023-07-02 10:34:05,866 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:05,866 [model] Got input parameters: {'Omega_m': 0.31001672479907816, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5143342659358193, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:05,866 [classy] Got parameters {'Omega_m': 0.31001672479907816, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:05,866 [classy] Re-using computed results
2023-07-02 10:34:05,866 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.55805680382596}
2023-07-02 10:34:05,866 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:05,866 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5143342659358193, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:05,866 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:05,885 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.70712
2023-07-02 10:34:05,886 [model] Computed derived parameters: {}
2023-07-02 10:34:05,886 [mcmc] New sample, #433:
Omega_m:0.3100167, b1:0.5075745
2023-07-02 10:34:05,886 [model] Posterior to be computed for parameters {'Omega_m': 0.30989425902720447, 'b1': 0.5145049739555508}
2023-07-02 10:34:05,886 [prior] Evaluating prior at array([0.30989426, 0.51450497])
2023-07-02 10:34:05,886 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:05,886 [model] Got input parameters: {'Omega_m': 0.30989425902720447, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5145049739555508, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:05,886 [classy] Got parameters {'Omega_m': 0.30989425902720447, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:05,886 [classy] Computing new state
2023-07-02 10:34:05,886 [classy] Setting parameters: {'Omega_m': 0.30989425902720447, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:05,931 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.57289880602522}
2023-07-02 10:34:05,931 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:05,933 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000616333
2023-07-02 10:34:05,933 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5145049739555508, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:05,933 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:05,952 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.70105
2023-07-02 10:34:05,952 [model] Computed derived parameters: {}
2023-07-02 10:34:05,952 [model] Posterior to be computed for parameters {'Omega_m': 0.31001672479907816, 'b1': 0.538817009340583}
2023-07-02 10:34:05,952 [prior] Evaluating prior at array([0.31001672, 0.53881701])
2023-07-02 10:34:05,952 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:05,952 [model] Got input parameters: {'Omega_m': 0.31001672479907816, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.538817009340583, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:05,953 [classy] Got parameters {'Omega_m': 0.31001672479907816, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:05,953 [classy] Re-using computed results
2023-07-02 10:34:05,953 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.55805680382596}
2023-07-02 10:34:05,953 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:05,953 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.538817009340583, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:05,953 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:05,973 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.381591
2023-07-02 10:34:05,973 [model] Computed derived parameters: {}
2023-07-02 10:34:05,973 [model] Posterior to be computed for parameters {'Omega_m': 0.27608633747569594, 'b1': 0.5616306585529394}
2023-07-02 10:34:05,973 [prior] Evaluating prior at array([0.27608634, 0.56163066])
2023-07-02 10:34:05,973 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:05,973 [model] Got input parameters: {'Omega_m': 0.27608633747569594, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5616306585529394, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:05,973 [classy] Got parameters {'Omega_m': 0.27608633747569594, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:05,973 [classy] Computing new state
2023-07-02 10:34:05,973 [classy] Setting parameters: {'Omega_m': 0.27608633747569594, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:06,018 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.8809625887398}
2023-07-02 10:34:06,018 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:06,020 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0894367
2023-07-02 10:34:06,020 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5616306585529394, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:06,020 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:06,039 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.41703
2023-07-02 10:34:06,039 [model] Computed derived parameters: {}
2023-07-02 10:34:06,039 [model] Posterior to be computed for parameters {'Omega_m': 0.31001672479907816, 'b1': 0.49940547469073926}
2023-07-02 10:34:06,040 [prior] Evaluating prior at array([0.31001672, 0.49940547])
2023-07-02 10:34:06,040 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:06,040 [model] Got input parameters: {'Omega_m': 0.31001672479907816, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49940547469073926, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:06,040 [classy] Got parameters {'Omega_m': 0.31001672479907816, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:06,040 [classy] Re-using computed results
2023-07-02 10:34:06,040 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.55805680382596}
2023-07-02 10:34:06,040 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:06,040 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49940547469073926, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:06,040 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:06,060 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.50766
2023-07-02 10:34:06,060 [model] Computed derived parameters: {}
2023-07-02 10:34:06,060 [mcmc] New sample, #434:
Omega_m:0.3100167, b1:0.5143343
2023-07-02 10:34:06,060 [model] Posterior to be computed for parameters {'Omega_m': 0.3249515500374706, 'b1': 0.47858745833829075}
2023-07-02 10:34:06,060 [prior] Evaluating prior at array([0.32495155, 0.47858746])
2023-07-02 10:34:06,060 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:06,060 [model] Got input parameters: {'Omega_m': 0.3249515500374706, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47858745833829075, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:06,060 [classy] Got parameters {'Omega_m': 0.3249515500374706, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:06,060 [classy] Computing new state
2023-07-02 10:34:06,061 [classy] Setting parameters: {'Omega_m': 0.3249515500374706, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:06,104 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.78597883720485}
2023-07-02 10:34:06,104 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:06,105 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00944588
2023-07-02 10:34:06,105 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47858745833829075, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:06,106 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:06,128 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.37557
2023-07-02 10:34:06,128 [model] Computed derived parameters: {}
2023-07-02 10:34:06,128 [mcmc] New sample, #435:
Omega_m:0.3100167, b1:0.4994055
2023-07-02 10:34:06,128 [model] Posterior to be computed for parameters {'Omega_m': 0.3249515500374706, 'b1': 0.5088432835794311}
2023-07-02 10:34:06,128 [prior] Evaluating prior at array([0.32495155, 0.50884328])
2023-07-02 10:34:06,128 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:06,128 [model] Got input parameters: {'Omega_m': 0.3249515500374706, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5088432835794311, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:06,128 [classy] Got parameters {'Omega_m': 0.3249515500374706, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:06,128 [classy] Re-using computed results
2023-07-02 10:34:06,128 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.78597883720485}
2023-07-02 10:34:06,128 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:06,128 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5088432835794311, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:06,128 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:06,148 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.443267
2023-07-02 10:34:06,148 [model] Computed derived parameters: {}
2023-07-02 10:34:06,148 [model] Posterior to be computed for parameters {'Omega_m': 0.3118271771316707, 'b1': 0.4968818411253225}
2023-07-02 10:34:06,149 [prior] Evaluating prior at array([0.31182718, 0.49688184])
2023-07-02 10:34:06,149 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:06,149 [model] Got input parameters: {'Omega_m': 0.3118271771316707, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4968818411253225, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:06,149 [classy] Got parameters {'Omega_m': 0.3118271771316707, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:06,149 [classy] Computing new state
2023-07-02 10:34:06,149 [classy] Setting parameters: {'Omega_m': 0.3118271771316707, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:06,193 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.3392356478298}
2023-07-02 10:34:06,193 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:06,194 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000228865
2023-07-02 10:34:06,195 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4968818411253225, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:06,195 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:06,215 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.63544
2023-07-02 10:34:06,215 [model] Computed derived parameters: {}
2023-07-02 10:34:06,215 [mcmc] New sample, #436:
Omega_m:0.3249516, b1:0.4785875
2023-07-02 10:34:06,215 [model] Posterior to be computed for parameters {'Omega_m': 0.3118271771316707, 'b1': 0.4760947075359782}
2023-07-02 10:34:06,215 [prior] Evaluating prior at array([0.31182718, 0.47609471])
2023-07-02 10:34:06,215 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:06,215 [model] Got input parameters: {'Omega_m': 0.3118271771316707, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4760947075359782, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:06,215 [classy] Got parameters {'Omega_m': 0.3118271771316707, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:06,215 [classy] Re-using computed results
2023-07-02 10:34:06,215 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.3392356478298}
2023-07-02 10:34:06,215 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:06,215 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4760947075359782, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:06,215 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:06,235 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.512868
2023-07-02 10:34:06,235 [model] Computed derived parameters: {}
2023-07-02 10:34:06,235 [model] Posterior to be computed for parameters {'Omega_m': 0.3014546849732174, 'b1': 0.5113403103690889}
2023-07-02 10:34:06,235 [prior] Evaluating prior at array([0.30145468, 0.51134031])
2023-07-02 10:34:06,235 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:06,235 [model] Got input parameters: {'Omega_m': 0.3014546849732174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5113403103690889, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:06,235 [classy] Got parameters {'Omega_m': 0.3014546849732174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:06,235 [classy] Computing new state
2023-07-02 10:34:06,235 [classy] Setting parameters: {'Omega_m': 0.3014546849732174, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:06,279 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.60840226177444}
2023-07-02 10:34:06,279 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:06,281 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00787122
2023-07-02 10:34:06,281 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5113403103690889, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:06,281 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:06,300 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.31702
2023-07-02 10:34:06,301 [model] Computed derived parameters: {}
2023-07-02 10:34:06,301 [model] Posterior to be computed for parameters {'Omega_m': 0.3118271771316707, 'b1': 0.5152149635920344}
2023-07-02 10:34:06,301 [prior] Evaluating prior at array([0.31182718, 0.51521496])
2023-07-02 10:34:06,301 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:06,301 [model] Got input parameters: {'Omega_m': 0.3118271771316707, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5152149635920344, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:06,301 [classy] Got parameters {'Omega_m': 0.3118271771316707, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:06,301 [classy] Re-using computed results
2023-07-02 10:34:06,301 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.3392356478298}
2023-07-02 10:34:06,301 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:06,301 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5152149635920344, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:06,301 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:06,321 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.63729
2023-07-02 10:34:06,321 [model] Computed derived parameters: {}
2023-07-02 10:34:06,322 [mcmc] New sample, #437:
Omega_m:0.3118272, b1:0.4968818
2023-07-02 10:34:06,322 [model] Posterior to be computed for parameters {'Omega_m': 0.3082950458812129, 'b1': 0.5201384872996971}
2023-07-02 10:34:06,322 [prior] Evaluating prior at array([0.30829505, 0.52013849])
2023-07-02 10:34:06,322 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:06,322 [model] Got input parameters: {'Omega_m': 0.3082950458812129, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5201384872996971, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:06,322 [classy] Got parameters {'Omega_m': 0.3082950458812129, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:06,322 [classy] Computing new state
2023-07-02 10:34:06,322 [classy] Setting parameters: {'Omega_m': 0.3082950458812129, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:06,366 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.76719924405833}
2023-07-02 10:34:06,366 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:06,368 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0012898
2023-07-02 10:34:06,368 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5201384872996971, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:06,368 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:06,387 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.49495
2023-07-02 10:34:06,387 [model] Computed derived parameters: {}
2023-07-02 10:34:06,387 [mcmc] New sample, #438:
Omega_m:0.3118272, b1:0.515215
2023-07-02 10:34:06,388 [model] Posterior to be computed for parameters {'Omega_m': 0.3082950458812129, 'b1': 0.5858109236054713}
2023-07-02 10:34:06,388 [prior] Evaluating prior at array([0.30829505, 0.58581092])
2023-07-02 10:34:06,388 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:06,388 [model] Got input parameters: {'Omega_m': 0.3082950458812129, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5858109236054713, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:06,388 [classy] Got parameters {'Omega_m': 0.3082950458812129, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:06,388 [classy] Re-using computed results
2023-07-02 10:34:06,388 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.76719924405833}
2023-07-02 10:34:06,388 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:06,388 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5858109236054713, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:06,388 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:06,407 [fs_likelihood.fslikelihood] Computed log-likelihood = -12.8145
2023-07-02 10:34:06,407 [model] Computed derived parameters: {}
2023-07-02 10:34:06,407 [model] Posterior to be computed for parameters {'Omega_m': 0.3229214023340386, 'b1': 0.49975045309432065}
2023-07-02 10:34:06,407 [prior] Evaluating prior at array([0.3229214 , 0.49975045])
2023-07-02 10:34:06,407 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:06,407 [model] Got input parameters: {'Omega_m': 0.3229214023340386, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49975045309432065, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:06,407 [classy] Got parameters {'Omega_m': 0.3229214023340386, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:06,407 [classy] Computing new state
2023-07-02 10:34:06,407 [classy] Setting parameters: {'Omega_m': 0.3229214023340386, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:06,452 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.02254152886198}
2023-07-02 10:34:06,452 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:06,454 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00671259
2023-07-02 10:34:06,454 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49975045309432065, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:06,454 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:06,474 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.07901
2023-07-02 10:34:06,474 [model] Computed derived parameters: {}
2023-07-02 10:34:06,474 [mcmc] New sample, #439:
Omega_m:0.308295, b1:0.5201385
2023-07-02 10:34:06,474 [model] Posterior to be computed for parameters {'Omega_m': 0.3229214023340386, 'b1': 0.5044271318857968}
2023-07-02 10:34:06,474 [prior] Evaluating prior at array([0.3229214 , 0.50442713])
2023-07-02 10:34:06,474 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:06,474 [model] Got input parameters: {'Omega_m': 0.3229214023340386, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5044271318857968, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:06,474 [classy] Got parameters {'Omega_m': 0.3229214023340386, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:06,474 [classy] Re-using computed results
2023-07-02 10:34:06,474 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.02254152886198}
2023-07-02 10:34:06,474 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:06,474 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5044271318857968, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:06,474 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:06,494 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.65956
2023-07-02 10:34:06,494 [model] Computed derived parameters: {}
2023-07-02 10:34:06,494 [mcmc] New sample, #440:
Omega_m:0.3229214, b1:0.4997505
2023-07-02 10:34:06,494 [model] Posterior to be computed for parameters {'Omega_m': 0.34910255453412325, 'b1': 0.4679325866917767}
2023-07-02 10:34:06,494 [prior] Evaluating prior at array([0.34910255, 0.46793259])
2023-07-02 10:34:06,494 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:06,494 [model] Got input parameters: {'Omega_m': 0.34910255453412325, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4679325866917767, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:06,494 [classy] Got parameters {'Omega_m': 0.34910255453412325, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:06,494 [classy] Computing new state
2023-07-02 10:34:06,494 [classy] Setting parameters: {'Omega_m': 0.34910255453412325, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:06,539 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.0698249072638}
2023-07-02 10:34:06,539 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:06,541 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0754971
2023-07-02 10:34:06,541 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4679325866917767, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:06,541 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:06,560 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.11247
2023-07-02 10:34:06,560 [model] Computed derived parameters: {}
2023-07-02 10:34:06,560 [model] Posterior to be computed for parameters {'Omega_m': 0.3229214023340386, 'b1': 0.49478342003794146}
2023-07-02 10:34:06,560 [prior] Evaluating prior at array([0.3229214 , 0.49478342])
2023-07-02 10:34:06,561 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:06,561 [model] Got input parameters: {'Omega_m': 0.3229214023340386, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49478342003794146, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:06,561 [classy] Got parameters {'Omega_m': 0.3229214023340386, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:06,561 [classy] Re-using computed results
2023-07-02 10:34:06,561 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.02254152886198}
2023-07-02 10:34:06,561 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:06,561 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49478342003794146, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:06,561 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:06,581 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.38898
2023-07-02 10:34:06,581 [model] Computed derived parameters: {}
2023-07-02 10:34:06,581 [mcmc] New sample, #441:
Omega_m:0.3229214, b1:0.5044271
2023-07-02 10:34:06,581 [model] Posterior to be computed for parameters {'Omega_m': 0.3315148786976918, 'b1': 0.4828047642045259}
2023-07-02 10:34:06,581 [prior] Evaluating prior at array([0.33151488, 0.48280476])
2023-07-02 10:34:06,581 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:06,581 [model] Got input parameters: {'Omega_m': 0.3315148786976918, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4828047642045259, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:06,581 [classy] Got parameters {'Omega_m': 0.3315148786976918, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:06,581 [classy] Computing new state
2023-07-02 10:34:06,581 [classy] Setting parameters: {'Omega_m': 0.3315148786976918, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:06,630 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.03017721815698}
2023-07-02 10:34:06,631 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:06,633 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0214019
2023-07-02 10:34:06,633 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4828047642045259, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:06,633 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:06,653 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.10299
2023-07-02 10:34:06,653 [model] Computed derived parameters: {}
2023-07-02 10:34:06,653 [model] Posterior to be computed for parameters {'Omega_m': 0.3229214023340386, 'b1': 0.5185863690684723}
2023-07-02 10:34:06,653 [prior] Evaluating prior at array([0.3229214 , 0.51858637])
2023-07-02 10:34:06,653 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:06,653 [model] Got input parameters: {'Omega_m': 0.3229214023340386, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5185863690684723, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:06,653 [classy] Got parameters {'Omega_m': 0.3229214023340386, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:06,653 [classy] Re-using computed results
2023-07-02 10:34:06,653 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.02254152886198}
2023-07-02 10:34:06,653 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:06,653 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5185863690684723, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:06,653 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:06,673 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.382806
2023-07-02 10:34:06,673 [model] Computed derived parameters: {}
2023-07-02 10:34:06,673 [model] Posterior to be computed for parameters {'Omega_m': 0.3497890450650079, 'b1': 0.4573319589865453}
2023-07-02 10:34:06,673 [prior] Evaluating prior at array([0.34978905, 0.45733196])
2023-07-02 10:34:06,674 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:06,674 [model] Got input parameters: {'Omega_m': 0.3497890450650079, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4573319589865453, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:06,674 [classy] Got parameters {'Omega_m': 0.3497890450650079, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:06,674 [classy] Computing new state
2023-07-02 10:34:06,674 [classy] Setting parameters: {'Omega_m': 0.3497890450650079, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:06,718 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.99515005443737}
2023-07-02 10:34:06,718 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:06,720 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0782222
2023-07-02 10:34:06,720 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4573319589865453, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:06,720 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:06,739 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.00041
2023-07-02 10:34:06,739 [model] Computed derived parameters: {}
2023-07-02 10:34:06,739 [model] Posterior to be computed for parameters {'Omega_m': 0.3229214023340386, 'b1': 0.49499917217634587}
2023-07-02 10:34:06,739 [prior] Evaluating prior at array([0.3229214 , 0.49499917])
2023-07-02 10:34:06,740 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:06,740 [model] Got input parameters: {'Omega_m': 0.3229214023340386, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49499917217634587, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:06,740 [classy] Got parameters {'Omega_m': 0.3229214023340386, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:06,740 [classy] Re-using computed results
2023-07-02 10:34:06,740 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.02254152886198}
2023-07-02 10:34:06,740 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:06,740 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49499917217634587, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:06,740 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:06,759 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.37839
2023-07-02 10:34:06,759 [model] Computed derived parameters: {}
2023-07-02 10:34:06,759 [mcmc] New sample, #442:
Omega_m:0.3229214, b1:0.4947834
2023-07-02 10:34:06,759 [model] Posterior to be computed for parameters {'Omega_m': 0.3681696713573728, 'b1': 0.43192650882664385}
2023-07-02 10:34:06,759 [prior] Evaluating prior at array([0.36816967, 0.43192651])
2023-07-02 10:34:06,759 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:06,759 [model] Got input parameters: {'Omega_m': 0.3681696713573728, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.43192650882664385, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:06,759 [classy] Got parameters {'Omega_m': 0.3681696713573728, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:06,759 [classy] Computing new state
2023-07-02 10:34:06,759 [classy] Setting parameters: {'Omega_m': 0.3681696713573728, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:06,804 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.04436631648474}
2023-07-02 10:34:06,804 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:06,806 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.166897
2023-07-02 10:34:06,806 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.43192650882664385, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:06,806 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:06,826 [fs_likelihood.fslikelihood] Computed log-likelihood = -11.8114
2023-07-02 10:34:06,826 [model] Computed derived parameters: {}
2023-07-02 10:34:06,827 [model] Posterior to be computed for parameters {'Omega_m': 0.3229214023340386, 'b1': 0.5261150297188976}
2023-07-02 10:34:06,827 [prior] Evaluating prior at array([0.3229214 , 0.52611503])
2023-07-02 10:34:06,827 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:06,827 [model] Got input parameters: {'Omega_m': 0.3229214023340386, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5261150297188976, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:06,827 [classy] Got parameters {'Omega_m': 0.3229214023340386, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:06,827 [classy] Re-using computed results
2023-07-02 10:34:06,827 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.02254152886198}
2023-07-02 10:34:06,827 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:06,827 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5261150297188976, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:06,827 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:06,846 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.95387
2023-07-02 10:34:06,846 [model] Computed derived parameters: {}
2023-07-02 10:34:06,847 [model] Posterior to be computed for parameters {'Omega_m': 0.2980687567885744, 'b1': 0.5296418796140641}
2023-07-02 10:34:06,847 [prior] Evaluating prior at array([0.29806876, 0.52964188])
2023-07-02 10:34:06,847 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:06,847 [model] Got input parameters: {'Omega_m': 0.2980687567885744, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5296418796140641, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:06,847 [classy] Got parameters {'Omega_m': 0.2980687567885744, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:06,847 [classy] Computing new state
2023-07-02 10:34:06,847 [classy] Setting parameters: {'Omega_m': 0.2980687567885744, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:06,891 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.031043964446}
2023-07-02 10:34:06,891 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:06,893 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0134167
2023-07-02 10:34:06,893 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5296418796140641, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:06,893 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:06,912 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.14966
2023-07-02 10:34:06,913 [model] Computed derived parameters: {}
2023-07-02 10:34:06,913 [mcmc] New sample, #443:
Omega_m:0.3229214, b1:0.4949992
2023-07-02 10:34:06,913 [model] Posterior to be computed for parameters {'Omega_m': 0.2980687567885744, 'b1': 0.5079828640795473}
2023-07-02 10:34:06,913 [prior] Evaluating prior at array([0.29806876, 0.50798286])
2023-07-02 10:34:06,913 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:06,913 [model] Got input parameters: {'Omega_m': 0.2980687567885744, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5079828640795473, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:06,913 [classy] Got parameters {'Omega_m': 0.2980687567885744, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:06,913 [classy] Re-using computed results
2023-07-02 10:34:06,913 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.031043964446}
2023-07-02 10:34:06,913 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:06,913 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5079828640795473, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:06,913 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:06,933 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.227347
2023-07-02 10:34:06,934 [model] Computed derived parameters: {}
2023-07-02 10:34:06,934 [model] Posterior to be computed for parameters {'Omega_m': 0.32804150869379534, 'b1': 0.48786213131900236}
2023-07-02 10:34:06,934 [prior] Evaluating prior at array([0.32804151, 0.48786213])
2023-07-02 10:34:06,934 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:06,934 [model] Got input parameters: {'Omega_m': 0.32804150869379534, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48786213131900236, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:06,934 [classy] Got parameters {'Omega_m': 0.32804150869379534, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:06,934 [classy] Computing new state
2023-07-02 10:34:06,934 [classy] Setting parameters: {'Omega_m': 0.32804150869379534, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:06,979 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.4284475517667}
2023-07-02 10:34:06,979 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:06,980 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0144888
2023-07-02 10:34:06,980 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48786213131900236, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:06,981 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:07,000 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.70351
2023-07-02 10:34:07,000 [model] Computed derived parameters: {}
2023-07-02 10:34:07,000 [mcmc] New sample, #444:
Omega_m:0.2980688, b1:0.5296419
2023-07-02 10:34:07,000 [model] Posterior to be computed for parameters {'Omega_m': 0.32804150869379534, 'b1': 0.463989468971631}
2023-07-02 10:34:07,000 [prior] Evaluating prior at array([0.32804151, 0.46398947])
2023-07-02 10:34:07,000 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:07,000 [model] Got input parameters: {'Omega_m': 0.32804150869379534, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.463989468971631, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,000 [classy] Got parameters {'Omega_m': 0.32804150869379534, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:07,000 [classy] Re-using computed results
2023-07-02 10:34:07,000 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.4284475517667}
2023-07-02 10:34:07,000 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:07,000 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.463989468971631, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,000 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:07,022 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.61262
2023-07-02 10:34:07,022 [model] Computed derived parameters: {}
2023-07-02 10:34:07,022 [mcmc] New sample, #445:
Omega_m:0.3280415, b1:0.4878621
2023-07-02 10:34:07,022 [model] Posterior to be computed for parameters {'Omega_m': 0.3717712235667876, 'b1': 0.4030335552074969}
2023-07-02 10:34:07,022 [prior] Evaluating prior at array([0.37177122, 0.40303356])
2023-07-02 10:34:07,023 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:07,023 [model] Got input parameters: {'Omega_m': 0.3717712235667876, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4030335552074969, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,023 [classy] Got parameters {'Omega_m': 0.3717712235667876, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:07,023 [classy] Computing new state
2023-07-02 10:34:07,023 [classy] Setting parameters: {'Omega_m': 0.3717712235667876, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:07,067 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.67272794665297}
2023-07-02 10:34:07,067 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:07,069 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.187639
2023-07-02 10:34:07,069 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4030335552074969, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,069 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:07,089 [fs_likelihood.fslikelihood] Computed log-likelihood = -11.2787
2023-07-02 10:34:07,089 [model] Computed derived parameters: {}
2023-07-02 10:34:07,089 [model] Posterior to be computed for parameters {'Omega_m': 0.32804150869379534, 'b1': 0.4672750152650727}
2023-07-02 10:34:07,089 [prior] Evaluating prior at array([0.32804151, 0.46727502])
2023-07-02 10:34:07,089 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:07,090 [model] Got input parameters: {'Omega_m': 0.32804150869379534, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4672750152650727, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,090 [classy] Got parameters {'Omega_m': 0.32804150869379534, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:07,090 [classy] Re-using computed results
2023-07-02 10:34:07,090 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.4284475517667}
2023-07-02 10:34:07,090 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:07,090 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4672750152650727, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,090 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:07,109 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.80762
2023-07-02 10:34:07,109 [model] Computed derived parameters: {}
2023-07-02 10:34:07,109 [mcmc] New sample, #446:
Omega_m:0.3280415, b1:0.4639895
2023-07-02 10:34:07,109 [model] Posterior to be computed for parameters {'Omega_m': 0.36920293127548787, 'b1': 0.40989910662752693}
2023-07-02 10:34:07,109 [prior] Evaluating prior at array([0.36920293, 0.40989911])
2023-07-02 10:34:07,109 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:07,109 [model] Got input parameters: {'Omega_m': 0.36920293127548787, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.40989910662752693, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,109 [classy] Got parameters {'Omega_m': 0.36920293127548787, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:07,109 [classy] Computing new state
2023-07-02 10:34:07,109 [classy] Setting parameters: {'Omega_m': 0.36920293127548787, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:07,156 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.9374004605944}
2023-07-02 10:34:07,156 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:07,158 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.17274
2023-07-02 10:34:07,158 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.40989910662752693, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,158 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:07,179 [fs_likelihood.fslikelihood] Computed log-likelihood = -10.2447
2023-07-02 10:34:07,179 [model] Computed derived parameters: {}
2023-07-02 10:34:07,179 [model] Posterior to be computed for parameters {'Omega_m': 0.32804150869379534, 'b1': 0.4434428287146425}
2023-07-02 10:34:07,179 [prior] Evaluating prior at array([0.32804151, 0.44344283])
2023-07-02 10:34:07,179 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:07,179 [model] Got input parameters: {'Omega_m': 0.32804150869379534, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4434428287146425, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,179 [classy] Got parameters {'Omega_m': 0.32804150869379534, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:07,179 [classy] Re-using computed results
2023-07-02 10:34:07,180 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.4284475517667}
2023-07-02 10:34:07,180 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:07,180 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4434428287146425, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,180 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:07,199 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.868996
2023-07-02 10:34:07,199 [model] Computed derived parameters: {}
2023-07-02 10:34:07,200 [model] Posterior to be computed for parameters {'Omega_m': 0.278283244623468, 'b1': 0.5366342704656394}
2023-07-02 10:34:07,200 [prior] Evaluating prior at array([0.27828324, 0.53663427])
2023-07-02 10:34:07,200 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:07,200 [model] Got input parameters: {'Omega_m': 0.278283244623468, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5366342704656394, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,200 [classy] Got parameters {'Omega_m': 0.278283244623468, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:07,200 [classy] Computing new state
2023-07-02 10:34:07,200 [classy] Setting parameters: {'Omega_m': 0.278283244623468, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:07,244 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.58753461005762}
2023-07-02 10:34:07,245 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:07,246 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0785294
2023-07-02 10:34:07,246 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5366342704656394, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,246 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:07,265 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.30916
2023-07-02 10:34:07,266 [model] Computed derived parameters: {}
2023-07-02 10:34:07,266 [model] Posterior to be computed for parameters {'Omega_m': 0.32804150869379534, 'b1': 0.5094437424078074}
2023-07-02 10:34:07,266 [prior] Evaluating prior at array([0.32804151, 0.50944374])
2023-07-02 10:34:07,266 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:07,266 [model] Got input parameters: {'Omega_m': 0.32804150869379534, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5094437424078074, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,266 [classy] Got parameters {'Omega_m': 0.32804150869379534, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:07,266 [classy] Re-using computed results
2023-07-02 10:34:07,266 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.4284475517667}
2023-07-02 10:34:07,266 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:07,266 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5094437424078074, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,266 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:07,287 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.975973
2023-07-02 10:34:07,287 [model] Computed derived parameters: {}
2023-07-02 10:34:07,287 [model] Posterior to be computed for parameters {'Omega_m': 0.30635373500913804, 'b1': 0.4975061307959563}
2023-07-02 10:34:07,287 [prior] Evaluating prior at array([0.30635374, 0.49750613])
2023-07-02 10:34:07,287 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:07,287 [model] Got input parameters: {'Omega_m': 0.30635373500913804, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4975061307959563, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,287 [classy] Got parameters {'Omega_m': 0.30635373500913804, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:07,287 [classy] Computing new state
2023-07-02 10:34:07,287 [classy] Setting parameters: {'Omega_m': 0.30635373500913804, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:07,332 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.00425673038194}
2023-07-02 10:34:07,332 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:07,333 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00254259
2023-07-02 10:34:07,333 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4975061307959563, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,334 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:07,353 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.56866
2023-07-02 10:34:07,353 [model] Computed derived parameters: {}
2023-07-02 10:34:07,353 [mcmc] New sample, #447:
Omega_m:0.3280415, b1:0.467275
2023-07-02 10:34:07,353 [model] Posterior to be computed for parameters {'Omega_m': 0.30635373500913804, 'b1': 0.5207632374945664}
2023-07-02 10:34:07,353 [prior] Evaluating prior at array([0.30635374, 0.52076324])
2023-07-02 10:34:07,353 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:07,353 [model] Got input parameters: {'Omega_m': 0.30635373500913804, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5207632374945664, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,353 [classy] Got parameters {'Omega_m': 0.30635373500913804, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:07,353 [classy] Re-using computed results
2023-07-02 10:34:07,353 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.00425673038194}
2023-07-02 10:34:07,353 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:07,353 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5207632374945664, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,353 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:07,373 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.41125
2023-07-02 10:34:07,373 [model] Computed derived parameters: {}
2023-07-02 10:34:07,373 [mcmc] New sample, #448:
Omega_m:0.3063537, b1:0.4975061
2023-07-02 10:34:07,373 [model] Posterior to be computed for parameters {'Omega_m': 0.30239269898826976, 'b1': 0.5262846219994948}
2023-07-02 10:34:07,373 [prior] Evaluating prior at array([0.3023927 , 0.52628462])
2023-07-02 10:34:07,373 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:07,373 [model] Got input parameters: {'Omega_m': 0.30239269898826976, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5262846219994948, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,374 [classy] Got parameters {'Omega_m': 0.30239269898826976, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:07,374 [classy] Computing new state
2023-07-02 10:34:07,374 [classy] Setting parameters: {'Omega_m': 0.30239269898826976, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:07,417 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.49206689192476}
2023-07-02 10:34:07,417 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:07,419 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00660716
2023-07-02 10:34:07,419 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5262846219994948, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,419 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:07,439 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.93003
2023-07-02 10:34:07,439 [model] Computed derived parameters: {}
2023-07-02 10:34:07,440 [mcmc] New sample, #449:
Omega_m:0.3063537, b1:0.5207632
2023-07-02 10:34:07,440 [model] Posterior to be computed for parameters {'Omega_m': 0.30239269898826976, 'b1': 0.5255810476511051}
2023-07-02 10:34:07,440 [prior] Evaluating prior at array([0.3023927 , 0.52558105])
2023-07-02 10:34:07,440 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:07,440 [model] Got input parameters: {'Omega_m': 0.30239269898826976, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5255810476511051, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,440 [classy] Got parameters {'Omega_m': 0.30239269898826976, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:07,440 [classy] Re-using computed results
2023-07-02 10:34:07,440 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.49206689192476}
2023-07-02 10:34:07,440 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:07,440 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5255810476511051, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,440 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:07,459 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.94015
2023-07-02 10:34:07,459 [model] Computed derived parameters: {}
2023-07-02 10:34:07,459 [mcmc] New sample, #450:
Omega_m:0.3023927, b1:0.5262846
2023-07-02 10:34:07,460 [model] Posterior to be computed for parameters {'Omega_m': 0.3110372197472623, 'b1': 0.5135312397928139}
2023-07-02 10:34:07,460 [prior] Evaluating prior at array([0.31103722, 0.51353124])
2023-07-02 10:34:07,460 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:07,460 [model] Got input parameters: {'Omega_m': 0.3110372197472623, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5135312397928139, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,460 [classy] Got parameters {'Omega_m': 0.3110372197472623, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:07,460 [classy] Computing new state
2023-07-02 10:34:07,460 [classy] Setting parameters: {'Omega_m': 0.3110372197472623, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:07,504 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.43457593930566}
2023-07-02 10:34:07,504 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:07,506 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000331196
2023-07-02 10:34:07,506 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5135312397928139, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,506 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:07,527 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.73112
2023-07-02 10:34:07,527 [model] Computed derived parameters: {}
2023-07-02 10:34:07,527 [mcmc] New sample, #451:
Omega_m:0.3023927, b1:0.525581
2023-07-02 10:34:07,527 [model] Posterior to be computed for parameters {'Omega_m': 0.3110372197472623, 'b1': 0.4879755084585546}
2023-07-02 10:34:07,527 [prior] Evaluating prior at array([0.31103722, 0.48797551])
2023-07-02 10:34:07,527 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:07,527 [model] Got input parameters: {'Omega_m': 0.3110372197472623, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4879755084585546, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,527 [classy] Got parameters {'Omega_m': 0.3110372197472623, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:07,527 [classy] Re-using computed results
2023-07-02 10:34:07,527 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.43457593930566}
2023-07-02 10:34:07,527 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:07,527 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4879755084585546, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,528 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:07,547 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.81958
2023-07-02 10:34:07,547 [model] Computed derived parameters: {}
2023-07-02 10:34:07,547 [mcmc] New sample, #452:
Omega_m:0.3110372, b1:0.5135312
2023-07-02 10:34:07,547 [model] Posterior to be computed for parameters {'Omega_m': 0.30338869797634427, 'b1': 0.498636969088821}
2023-07-02 10:34:07,547 [prior] Evaluating prior at array([0.3033887 , 0.49863697])
2023-07-02 10:34:07,547 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:07,547 [model] Got input parameters: {'Omega_m': 0.30338869797634427, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.498636969088821, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,547 [classy] Got parameters {'Omega_m': 0.30338869797634427, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:07,547 [classy] Computing new state
2023-07-02 10:34:07,547 [classy] Setting parameters: {'Omega_m': 0.30338869797634427, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:07,592 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.368882695798}
2023-07-02 10:34:07,592 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:07,594 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00539225
2023-07-02 10:34:07,594 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.498636969088821, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,594 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:07,613 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.749875
2023-07-02 10:34:07,613 [model] Computed derived parameters: {}
2023-07-02 10:34:07,613 [model] Posterior to be computed for parameters {'Omega_m': 0.3110372197472623, 'b1': 0.5493828810266157}
2023-07-02 10:34:07,613 [prior] Evaluating prior at array([0.31103722, 0.54938288])
2023-07-02 10:34:07,614 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:07,614 [model] Got input parameters: {'Omega_m': 0.3110372197472623, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5493828810266157, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,614 [classy] Got parameters {'Omega_m': 0.3110372197472623, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:07,614 [classy] Re-using computed results
2023-07-02 10:34:07,614 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.43457593930566}
2023-07-02 10:34:07,614 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:07,614 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5493828810266157, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,614 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:07,634 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.07315
2023-07-02 10:34:07,635 [model] Computed derived parameters: {}
2023-07-02 10:34:07,635 [model] Posterior to be computed for parameters {'Omega_m': 0.3379322051051616, 'b1': 0.4504859338540728}
2023-07-02 10:34:07,635 [prior] Evaluating prior at array([0.33793221, 0.45048593])
2023-07-02 10:34:07,635 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:07,635 [model] Got input parameters: {'Omega_m': 0.3379322051051616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4504859338540728, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,635 [classy] Got parameters {'Omega_m': 0.3379322051051616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:07,635 [classy] Computing new state
2023-07-02 10:34:07,635 [classy] Setting parameters: {'Omega_m': 0.3379322051051616, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:07,679 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.30417414125947}
2023-07-02 10:34:07,679 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:07,681 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0375328
2023-07-02 10:34:07,681 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4504859338540728, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,681 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:07,700 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.0970122
2023-07-02 10:34:07,700 [model] Computed derived parameters: {}
2023-07-02 10:34:07,700 [model] Posterior to be computed for parameters {'Omega_m': 0.3110372197472623, 'b1': 0.5325258213647103}
2023-07-02 10:34:07,700 [prior] Evaluating prior at array([0.31103722, 0.53252582])
2023-07-02 10:34:07,701 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:07,701 [model] Got input parameters: {'Omega_m': 0.3110372197472623, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5325258213647103, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,701 [classy] Got parameters {'Omega_m': 0.3110372197472623, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:07,701 [classy] Re-using computed results
2023-07-02 10:34:07,701 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.43457593930566}
2023-07-02 10:34:07,701 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:07,701 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5325258213647103, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,701 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:07,720 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.10955
2023-07-02 10:34:07,720 [model] Computed derived parameters: {}
2023-07-02 10:34:07,720 [model] Posterior to be computed for parameters {'Omega_m': 0.2871598831280164, 'b1': 0.521258709048981}
2023-07-02 10:34:07,720 [prior] Evaluating prior at array([0.28715988, 0.52125871])
2023-07-02 10:34:07,720 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:07,721 [model] Got input parameters: {'Omega_m': 0.2871598831280164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.521258709048981, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,721 [classy] Got parameters {'Omega_m': 0.2871598831280164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:07,721 [classy] Computing new state
2023-07-02 10:34:07,721 [classy] Setting parameters: {'Omega_m': 0.2871598831280164, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:07,764 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.4217437303083}
2023-07-02 10:34:07,764 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:07,766 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0421512
2023-07-02 10:34:07,766 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.521258709048981, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,766 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:07,787 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.26823
2023-07-02 10:34:07,787 [model] Computed derived parameters: {}
2023-07-02 10:34:07,787 [model] Posterior to be computed for parameters {'Omega_m': 0.3110372197472623, 'b1': 0.5249017809726502}
2023-07-02 10:34:07,787 [prior] Evaluating prior at array([0.31103722, 0.52490178])
2023-07-02 10:34:07,787 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:07,787 [model] Got input parameters: {'Omega_m': 0.3110372197472623, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5249017809726502, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,787 [classy] Got parameters {'Omega_m': 0.3110372197472623, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:07,787 [classy] Re-using computed results
2023-07-02 10:34:07,787 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.43457593930566}
2023-07-02 10:34:07,787 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:07,787 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5249017809726502, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,787 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:07,807 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.00464
2023-07-02 10:34:07,807 [model] Computed derived parameters: {}
2023-07-02 10:34:07,807 [mcmc] New sample, #453:
Omega_m:0.3110372, b1:0.4879755
2023-07-02 10:34:07,807 [model] Posterior to be computed for parameters {'Omega_m': 0.3266178453905202, 'b1': 0.5031835677197153}
2023-07-02 10:34:07,807 [prior] Evaluating prior at array([0.32661785, 0.50318357])
2023-07-02 10:34:07,807 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:07,807 [model] Got input parameters: {'Omega_m': 0.3266178453905202, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5031835677197153, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,807 [classy] Got parameters {'Omega_m': 0.3266178453905202, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:07,807 [classy] Computing new state
2023-07-02 10:34:07,807 [classy] Setting parameters: {'Omega_m': 0.3266178453905202, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:07,851 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.59280016794216}
2023-07-02 10:34:07,851 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:07,853 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0120341
2023-07-02 10:34:07,853 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5031835677197153, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,853 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:07,872 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.631904
2023-07-02 10:34:07,872 [model] Computed derived parameters: {}
2023-07-02 10:34:07,873 [mcmc] New sample, #454:
Omega_m:0.3110372, b1:0.5249018
2023-07-02 10:34:07,873 [model] Posterior to be computed for parameters {'Omega_m': 0.3266178453905202, 'b1': 0.47002167763955904}
2023-07-02 10:34:07,873 [prior] Evaluating prior at array([0.32661785, 0.47002168])
2023-07-02 10:34:07,873 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:07,873 [model] Got input parameters: {'Omega_m': 0.3266178453905202, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47002167763955904, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,873 [classy] Got parameters {'Omega_m': 0.3266178453905202, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:07,873 [classy] Re-using computed results
2023-07-02 10:34:07,873 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.59280016794216}
2023-07-02 10:34:07,873 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:07,873 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47002167763955904, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,873 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:07,893 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.99618
2023-07-02 10:34:07,893 [model] Computed derived parameters: {}
2023-07-02 10:34:07,893 [mcmc] New sample, #455:
Omega_m:0.3266178, b1:0.5031836
2023-07-02 10:34:07,893 [model] Posterior to be computed for parameters {'Omega_m': 0.34749887478940467, 'b1': 0.4409151026014754}
2023-07-02 10:34:07,893 [prior] Evaluating prior at array([0.34749887, 0.4409151 ])
2023-07-02 10:34:07,893 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:07,893 [model] Got input parameters: {'Omega_m': 0.34749887478940467, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4409151026014754, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,893 [classy] Got parameters {'Omega_m': 0.34749887478940467, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:07,894 [classy] Computing new state
2023-07-02 10:34:07,894 [classy] Setting parameters: {'Omega_m': 0.34749887478940467, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:07,939 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.24478953215723}
2023-07-02 10:34:07,939 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:07,941 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0693046
2023-07-02 10:34:07,941 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4409151026014754, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,941 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:07,960 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.19119
2023-07-02 10:34:07,960 [model] Computed derived parameters: {}
2023-07-02 10:34:07,961 [model] Posterior to be computed for parameters {'Omega_m': 0.3266178453905202, 'b1': 0.4556503657235575}
2023-07-02 10:34:07,961 [prior] Evaluating prior at array([0.32661785, 0.45565037])
2023-07-02 10:34:07,961 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:07,961 [model] Got input parameters: {'Omega_m': 0.3266178453905202, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4556503657235575, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,961 [classy] Got parameters {'Omega_m': 0.3266178453905202, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:07,961 [classy] Re-using computed results
2023-07-02 10:34:07,961 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.59280016794216}
2023-07-02 10:34:07,961 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:07,961 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4556503657235575, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,961 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:07,980 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.742583
2023-07-02 10:34:07,980 [model] Computed derived parameters: {}
2023-07-02 10:34:07,980 [model] Posterior to be computed for parameters {'Omega_m': 0.3135297999833939, 'b1': 0.4882654226421267}
2023-07-02 10:34:07,980 [prior] Evaluating prior at array([0.3135298 , 0.48826542])
2023-07-02 10:34:07,980 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:07,980 [model] Got input parameters: {'Omega_m': 0.3135297999833939, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4882654226421267, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:07,981 [classy] Got parameters {'Omega_m': 0.3135297999833939, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:07,981 [classy] Computing new state
2023-07-02 10:34:07,981 [classy] Setting parameters: {'Omega_m': 0.3135297999833939, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:08,025 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.13446721869096}
2023-07-02 10:34:08,025 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:08,026 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000269295
2023-07-02 10:34:08,026 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4882654226421267, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:08,026 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:08,047 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.33383
2023-07-02 10:34:08,047 [model] Computed derived parameters: {}
2023-07-02 10:34:08,047 [mcmc] New sample, #456:
Omega_m:0.3266178, b1:0.4700217
2023-07-02 10:34:08,047 [model] Posterior to be computed for parameters {'Omega_m': 0.3135297999833939, 'b1': 0.46425771952517236}
2023-07-02 10:34:08,047 [prior] Evaluating prior at array([0.3135298 , 0.46425772])
2023-07-02 10:34:08,047 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:08,047 [model] Got input parameters: {'Omega_m': 0.3135297999833939, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46425771952517236, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:08,047 [classy] Got parameters {'Omega_m': 0.3135297999833939, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:08,047 [classy] Re-using computed results
2023-07-02 10:34:08,047 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.13446721869096}
2023-07-02 10:34:08,047 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:08,047 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46425771952517236, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:08,047 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:08,067 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.978433
2023-07-02 10:34:08,067 [model] Computed derived parameters: {}
2023-07-02 10:34:08,067 [model] Posterior to be computed for parameters {'Omega_m': 0.3508758858819358, 'b1': 0.4362078046569378}
2023-07-02 10:34:08,067 [prior] Evaluating prior at array([0.35087589, 0.4362078 ])
2023-07-02 10:34:08,067 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:08,067 [model] Got input parameters: {'Omega_m': 0.3508758858819358, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4362078046569378, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:08,067 [classy] Got parameters {'Omega_m': 0.3508758858819358, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:08,067 [classy] Computing new state
2023-07-02 10:34:08,067 [classy] Setting parameters: {'Omega_m': 0.3508758858819358, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:08,112 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.8772028708634}
2023-07-02 10:34:08,112 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:08,114 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0826262
2023-07-02 10:34:08,114 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4362078046569378, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:08,114 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:08,137 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.22742
2023-07-02 10:34:08,138 [model] Computed derived parameters: {}
2023-07-02 10:34:08,138 [model] Posterior to be computed for parameters {'Omega_m': 0.3135297999833939, 'b1': 0.521294504371664}
2023-07-02 10:34:08,138 [prior] Evaluating prior at array([0.3135298, 0.5212945])
2023-07-02 10:34:08,138 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:08,138 [model] Got input parameters: {'Omega_m': 0.3135297999833939, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.521294504371664, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:08,138 [classy] Got parameters {'Omega_m': 0.3135297999833939, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:08,138 [classy] Re-using computed results
2023-07-02 10:34:08,138 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.13446721869096}
2023-07-02 10:34:08,138 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:08,138 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.521294504371664, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:08,138 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:08,158 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.99517
2023-07-02 10:34:08,158 [model] Computed derived parameters: {}
2023-07-02 10:34:08,158 [mcmc] New sample, #457:
Omega_m:0.3135298, b1:0.4882654
2023-07-02 10:34:08,158 [model] Posterior to be computed for parameters {'Omega_m': 0.3101394708996452, 'b1': 0.5260203665882652}
2023-07-02 10:34:08,158 [prior] Evaluating prior at array([0.31013947, 0.52602037])
2023-07-02 10:34:08,158 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:08,159 [model] Got input parameters: {'Omega_m': 0.3101394708996452, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5260203665882652, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:08,159 [classy] Got parameters {'Omega_m': 0.3101394708996452, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:08,159 [classy] Computing new state
2023-07-02 10:34:08,159 [classy] Setting parameters: {'Omega_m': 0.3101394708996452, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:08,202 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.54318704291524}
2023-07-02 10:34:08,202 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:08,204 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000541448
2023-07-02 10:34:08,204 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5260203665882652, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:08,204 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:08,223 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.00572
2023-07-02 10:34:08,223 [model] Computed derived parameters: {}
2023-07-02 10:34:08,223 [mcmc] New sample, #458:
Omega_m:0.3135298, b1:0.5212945
2023-07-02 10:34:08,224 [model] Posterior to be computed for parameters {'Omega_m': 0.3101394708996452, 'b1': 0.4906648537369532}
2023-07-02 10:34:08,224 [prior] Evaluating prior at array([0.31013947, 0.49066485])
2023-07-02 10:34:08,224 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:08,224 [model] Got input parameters: {'Omega_m': 0.3101394708996452, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4906648537369532, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:08,224 [classy] Got parameters {'Omega_m': 0.3101394708996452, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:08,224 [classy] Re-using computed results
2023-07-02 10:34:08,224 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.54318704291524}
2023-07-02 10:34:08,224 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:08,224 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4906648537369532, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:08,224 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:08,244 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.87776
2023-07-02 10:34:08,244 [model] Computed derived parameters: {}
2023-07-02 10:34:08,244 [mcmc] New sample, #459:
Omega_m:0.3101395, b1:0.5260204
2023-07-02 10:34:08,244 [model] Posterior to be computed for parameters {'Omega_m': 0.31180231686296445, 'b1': 0.48834697228180274}
2023-07-02 10:34:08,244 [prior] Evaluating prior at array([0.31180232, 0.48834697])
2023-07-02 10:34:08,244 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:08,244 [model] Got input parameters: {'Omega_m': 0.31180231686296445, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48834697228180274, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:08,244 [classy] Got parameters {'Omega_m': 0.31180231686296445, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:08,244 [classy] Computing new state
2023-07-02 10:34:08,244 [classy] Setting parameters: {'Omega_m': 0.31180231686296445, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:08,288 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.34223258208854}
2023-07-02 10:34:08,288 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:08,290 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000230911
2023-07-02 10:34:08,290 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48834697228180274, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:08,290 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:08,310 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.02403
2023-07-02 10:34:08,310 [model] Computed derived parameters: {}
2023-07-02 10:34:08,310 [mcmc] New sample, #460:
Omega_m:0.3101395, b1:0.4906649
2023-07-02 10:34:08,310 [model] Posterior to be computed for parameters {'Omega_m': 0.31180231686296445, 'b1': 0.5132131556706865}
2023-07-02 10:34:08,310 [prior] Evaluating prior at array([0.31180232, 0.51321316])
2023-07-02 10:34:08,310 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:08,310 [model] Got input parameters: {'Omega_m': 0.31180231686296445, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5132131556706865, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:08,310 [classy] Got parameters {'Omega_m': 0.31180231686296445, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:08,310 [classy] Re-using computed results
2023-07-02 10:34:08,310 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.34223258208854}
2023-07-02 10:34:08,310 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:08,310 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5132131556706865, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:08,310 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:08,330 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.72635
2023-07-02 10:34:08,330 [model] Computed derived parameters: {}
2023-07-02 10:34:08,330 [mcmc] New sample, #461:
Omega_m:0.3118023, b1:0.488347
2023-07-02 10:34:08,330 [model] Posterior to be computed for parameters {'Omega_m': 0.29556709457055186, 'b1': 0.5358438271230872}
2023-07-02 10:34:08,330 [prior] Evaluating prior at array([0.29556709, 0.53584383])
2023-07-02 10:34:08,330 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:08,330 [model] Got input parameters: {'Omega_m': 0.29556709457055186, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5358438271230872, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:08,330 [classy] Got parameters {'Omega_m': 0.29556709457055186, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:08,330 [classy] Computing new state
2023-07-02 10:34:08,330 [classy] Setting parameters: {'Omega_m': 0.29556709457055186, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:08,374 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.3460123446448}
2023-07-02 10:34:08,374 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:08,376 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0185186
2023-07-02 10:34:08,376 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5358438271230872, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:08,376 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:08,395 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.575124
2023-07-02 10:34:08,396 [model] Computed derived parameters: {}
2023-07-02 10:34:08,396 [model] Posterior to be computed for parameters {'Omega_m': 0.31180231686296445, 'b1': 0.5022504517628039}
2023-07-02 10:34:08,396 [prior] Evaluating prior at array([0.31180232, 0.50225045])
2023-07-02 10:34:08,396 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:08,396 [model] Got input parameters: {'Omega_m': 0.31180231686296445, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5022504517628039, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:08,396 [classy] Got parameters {'Omega_m': 0.31180231686296445, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:08,396 [classy] Re-using computed results
2023-07-02 10:34:08,396 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.34223258208854}
2023-07-02 10:34:08,396 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:08,396 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5022504517628039, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:08,396 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:08,415 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.82041
2023-07-02 10:34:08,415 [model] Computed derived parameters: {}
2023-07-02 10:34:08,415 [mcmc] New sample, #462:
Omega_m:0.3118023, b1:0.5132132
2023-07-02 10:34:08,415 [model] Posterior to be computed for parameters {'Omega_m': 0.30310313650768933, 'b1': 0.5143764509625448}
2023-07-02 10:34:08,415 [prior] Evaluating prior at array([0.30310314, 0.51437645])
2023-07-02 10:34:08,416 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:08,416 [model] Got input parameters: {'Omega_m': 0.30310313650768933, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5143764509625448, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:08,416 [classy] Got parameters {'Omega_m': 0.30310313650768933, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:08,416 [classy] Computing new state
2023-07-02 10:34:08,416 [classy] Setting parameters: {'Omega_m': 0.30310313650768933, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:08,460 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.4041634860662}
2023-07-02 10:34:08,460 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:08,462 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0057272
2023-07-02 10:34:08,462 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5143764509625448, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:08,462 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:08,481 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.91048
2023-07-02 10:34:08,481 [model] Computed derived parameters: {}
2023-07-02 10:34:08,481 [mcmc] New sample, #463:
Omega_m:0.3118023, b1:0.5022505
2023-07-02 10:34:08,481 [model] Posterior to be computed for parameters {'Omega_m': 0.30310313650768933, 'b1': 0.543863615547758}
2023-07-02 10:34:08,481 [prior] Evaluating prior at array([0.30310314, 0.54386362])
2023-07-02 10:34:08,481 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:08,482 [model] Got input parameters: {'Omega_m': 0.30310313650768933, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.543863615547758, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:08,482 [classy] Got parameters {'Omega_m': 0.30310313650768933, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:08,482 [classy] Re-using computed results
2023-07-02 10:34:08,482 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.4041634860662}
2023-07-02 10:34:08,482 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:08,482 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.543863615547758, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:08,482 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:08,501 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.755095
2023-07-02 10:34:08,502 [model] Computed derived parameters: {}
2023-07-02 10:34:08,502 [mcmc] New sample, #464:
Omega_m:0.3031031, b1:0.5143765
2023-07-02 10:34:08,502 [model] Posterior to be computed for parameters {'Omega_m': 0.29592397021648037, 'b1': 0.5538708301526624}
2023-07-02 10:34:08,502 [prior] Evaluating prior at array([0.29592397, 0.55387083])
2023-07-02 10:34:08,502 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:08,502 [model] Got input parameters: {'Omega_m': 0.29592397021648037, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5538708301526624, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:08,502 [classy] Got parameters {'Omega_m': 0.29592397021648037, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:08,502 [classy] Computing new state
2023-07-02 10:34:08,502 [classy] Setting parameters: {'Omega_m': 0.29592397021648037, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:08,546 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.3009404056425}
2023-07-02 10:34:08,546 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:08,548 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0177379
2023-07-02 10:34:08,548 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5538708301526624, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:08,548 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:08,568 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.297594
2023-07-02 10:34:08,568 [model] Computed derived parameters: {}
2023-07-02 10:34:08,568 [model] Posterior to be computed for parameters {'Omega_m': 0.30310313650768933, 'b1': 0.5374354436810272}
2023-07-02 10:34:08,568 [prior] Evaluating prior at array([0.30310314, 0.53743544])
2023-07-02 10:34:08,568 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:08,568 [model] Got input parameters: {'Omega_m': 0.30310313650768933, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5374354436810272, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:08,568 [classy] Got parameters {'Omega_m': 0.30310313650768933, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:08,568 [classy] Re-using computed results
2023-07-02 10:34:08,568 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.4041634860662}
2023-07-02 10:34:08,568 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:08,568 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5374354436810272, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:08,568 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:08,587 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.4137
2023-07-02 10:34:08,587 [model] Computed derived parameters: {}
2023-07-02 10:34:08,587 [mcmc] New sample, #465:
Omega_m:0.3031031, b1:0.5438636
2023-07-02 10:34:08,588 [model] Posterior to be computed for parameters {'Omega_m': 0.2757534248458676, 'b1': 0.5755588723467275}
2023-07-02 10:34:08,588 [prior] Evaluating prior at array([0.27575342, 0.57555887])
2023-07-02 10:34:08,588 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:08,588 [model] Got input parameters: {'Omega_m': 0.2757534248458676, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5755588723467275, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:08,588 [classy] Got parameters {'Omega_m': 0.2757534248458676, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:08,588 [classy] Computing new state
2023-07-02 10:34:08,588 [classy] Setting parameters: {'Omega_m': 0.2757534248458676, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:08,632 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.92560334376802}
2023-07-02 10:34:08,632 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:08,634 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0911576
2023-07-02 10:34:08,634 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5755588723467275, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:08,634 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:08,654 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.43262
2023-07-02 10:34:08,654 [model] Computed derived parameters: {}
2023-07-02 10:34:08,654 [model] Posterior to be computed for parameters {'Omega_m': 0.30310313650768933, 'b1': 0.5263009532115862}
2023-07-02 10:34:08,654 [prior] Evaluating prior at array([0.30310314, 0.52630095])
2023-07-02 10:34:08,655 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:08,655 [model] Got input parameters: {'Omega_m': 0.30310313650768933, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5263009532115862, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:08,655 [classy] Got parameters {'Omega_m': 0.30310313650768933, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:08,655 [classy] Re-using computed results
2023-07-02 10:34:08,655 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.4041634860662}
2023-07-02 10:34:08,655 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:08,655 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5263009532115862, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:08,655 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:08,675 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.01164
2023-07-02 10:34:08,676 [model] Computed derived parameters: {}
2023-07-02 10:34:08,676 [mcmc] New sample, #466:
Omega_m:0.3031031, b1:0.5374354
2023-07-02 10:34:08,676 [model] Posterior to be computed for parameters {'Omega_m': 0.29899894701923985, 'b1': 0.5320218828187468}
2023-07-02 10:34:08,676 [prior] Evaluating prior at array([0.29899895, 0.53202188])
2023-07-02 10:34:08,676 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:08,676 [model] Got input parameters: {'Omega_m': 0.29899894701923985, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5320218828187468, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:08,676 [classy] Got parameters {'Omega_m': 0.29899894701923985, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:08,676 [classy] Computing new state
2023-07-02 10:34:08,676 [classy] Setting parameters: {'Omega_m': 0.29899894701923985, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:08,722 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.91451154378714}
2023-07-02 10:34:08,722 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:08,724 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0117386
2023-07-02 10:34:08,724 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5320218828187468, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:08,724 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:08,746 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.33038
2023-07-02 10:34:08,746 [model] Computed derived parameters: {}
2023-07-02 10:34:08,746 [mcmc] New sample, #467:
Omega_m:0.3031031, b1:0.526301
2023-07-02 10:34:08,746 [model] Posterior to be computed for parameters {'Omega_m': 0.29899894701923985, 'b1': 0.5507527163785765}
2023-07-02 10:34:08,746 [prior] Evaluating prior at array([0.29899895, 0.55075272])
2023-07-02 10:34:08,746 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:08,746 [model] Got input parameters: {'Omega_m': 0.29899894701923985, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5507527163785765, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:08,746 [classy] Got parameters {'Omega_m': 0.29899894701923985, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:08,746 [classy] Re-using computed results
2023-07-02 10:34:08,746 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.91451154378714}
2023-07-02 10:34:08,746 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:08,746 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5507527163785765, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:08,746 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:08,767 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.113778
2023-07-02 10:34:08,767 [model] Computed derived parameters: {}
2023-07-02 10:34:08,767 [model] Posterior to be computed for parameters {'Omega_m': 0.33098383397328834, 'b1': 0.4874373705119748}
2023-07-02 10:34:08,767 [prior] Evaluating prior at array([0.33098383, 0.48743737])
2023-07-02 10:34:08,767 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:08,767 [model] Got input parameters: {'Omega_m': 0.33098383397328834, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4874373705119748, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:08,767 [classy] Got parameters {'Omega_m': 0.33098383397328834, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:08,767 [classy] Computing new state
2023-07-02 10:34:08,768 [classy] Setting parameters: {'Omega_m': 0.33098383397328834, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:08,812 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.09082234795068}
2023-07-02 10:34:08,812 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:08,814 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.020261
2023-07-02 10:34:08,814 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4874373705119748, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:08,814 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:08,833 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.897659
2023-07-02 10:34:08,833 [model] Computed derived parameters: {}
2023-07-02 10:34:08,833 [mcmc] New sample, #468:
Omega_m:0.2989989, b1:0.5320219
2023-07-02 10:34:08,834 [model] Posterior to be computed for parameters {'Omega_m': 0.33098383397328834, 'b1': 0.5321954594474464}
2023-07-02 10:34:08,834 [prior] Evaluating prior at array([0.33098383, 0.53219546])
2023-07-02 10:34:08,834 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:08,834 [model] Got input parameters: {'Omega_m': 0.33098383397328834, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5321954594474464, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:08,834 [classy] Got parameters {'Omega_m': 0.33098383397328834, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:08,834 [classy] Re-using computed results
2023-07-02 10:34:08,834 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.09082234795068}
2023-07-02 10:34:08,834 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:08,834 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5321954594474464, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:08,834 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:08,854 [fs_likelihood.fslikelihood] Computed log-likelihood = -9.13937
2023-07-02 10:34:08,854 [model] Computed derived parameters: {}
2023-07-02 10:34:08,854 [model] Posterior to be computed for parameters {'Omega_m': 0.3494752394501789, 'b1': 0.46166175041244567}
2023-07-02 10:34:08,854 [prior] Evaluating prior at array([0.34947524, 0.46166175])
2023-07-02 10:34:08,854 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:08,854 [model] Got input parameters: {'Omega_m': 0.3494752394501789, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46166175041244567, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:08,854 [classy] Got parameters {'Omega_m': 0.3494752394501789, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:08,854 [classy] Computing new state
2023-07-02 10:34:08,854 [classy] Setting parameters: {'Omega_m': 0.3494752394501789, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:08,898 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.02926686384663}
2023-07-02 10:34:08,898 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:08,899 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0769712
2023-07-02 10:34:08,899 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46166175041244567, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:08,899 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:08,920 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.37258
2023-07-02 10:34:08,920 [model] Computed derived parameters: {}
2023-07-02 10:34:08,920 [model] Posterior to be computed for parameters {'Omega_m': 0.33098383397328834, 'b1': 0.4711131968498434}
2023-07-02 10:34:08,920 [prior] Evaluating prior at array([0.33098383, 0.4711132 ])
2023-07-02 10:34:08,920 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:08,920 [model] Got input parameters: {'Omega_m': 0.33098383397328834, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4711131968498434, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:08,920 [classy] Got parameters {'Omega_m': 0.33098383397328834, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:08,920 [classy] Re-using computed results
2023-07-02 10:34:08,920 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.09082234795068}
2023-07-02 10:34:08,920 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:08,920 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4711131968498434, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:08,920 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:08,940 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.61499
2023-07-02 10:34:08,940 [model] Computed derived parameters: {}
2023-07-02 10:34:08,940 [mcmc] New sample, #469:
Omega_m:0.3309838, b1:0.4874374
2023-07-02 10:34:08,941 [model] Posterior to be computed for parameters {'Omega_m': 0.34089936033326, 'b1': 0.45729170335326175}
2023-07-02 10:34:08,941 [prior] Evaluating prior at array([0.34089936, 0.4572917 ])
2023-07-02 10:34:08,941 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:08,941 [model] Got input parameters: {'Omega_m': 0.34089936033326, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45729170335326175, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:08,941 [classy] Got parameters {'Omega_m': 0.34089936033326, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:08,941 [classy] Computing new state
2023-07-02 10:34:08,941 [classy] Setting parameters: {'Omega_m': 0.34089936033326, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:08,985 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.97270017554806}
2023-07-02 10:34:08,985 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:08,987 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0464206
2023-07-02 10:34:08,987 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45729170335326175, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:08,987 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:09,007 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.446025
2023-07-02 10:34:09,007 [model] Computed derived parameters: {}
2023-07-02 10:34:09,007 [model] Posterior to be computed for parameters {'Omega_m': 0.33098383397328834, 'b1': 0.4428598989777455}
2023-07-02 10:34:09,007 [prior] Evaluating prior at array([0.33098383, 0.4428599 ])
2023-07-02 10:34:09,007 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:09,008 [model] Got input parameters: {'Omega_m': 0.33098383397328834, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4428598989777455, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,008 [classy] Got parameters {'Omega_m': 0.33098383397328834, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:09,008 [classy] Re-using computed results
2023-07-02 10:34:09,008 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.09082234795068}
2023-07-02 10:34:09,008 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:09,008 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4428598989777455, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,008 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:09,027 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.544369
2023-07-02 10:34:09,027 [model] Computed derived parameters: {}
2023-07-02 10:34:09,027 [mcmc] New sample, #470:
Omega_m:0.3309838, b1:0.4711132
2023-07-02 10:34:09,027 [model] Posterior to be computed for parameters {'Omega_m': 0.34686776026927474, 'b1': 0.42071890756387315}
2023-07-02 10:34:09,027 [prior] Evaluating prior at array([0.34686776, 0.42071891])
2023-07-02 10:34:09,027 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:09,027 [model] Got input parameters: {'Omega_m': 0.34686776026927474, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42071890756387315, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,028 [classy] Got parameters {'Omega_m': 0.34686776026927474, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:09,028 [classy] Computing new state
2023-07-02 10:34:09,028 [classy] Setting parameters: {'Omega_m': 0.34686776026927474, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:09,072 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.31384640482958}
2023-07-02 10:34:09,072 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:09,074 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0669345
2023-07-02 10:34:09,074 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42071890756387315, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,074 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:09,093 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.31617
2023-07-02 10:34:09,093 [model] Computed derived parameters: {}
2023-07-02 10:34:09,093 [model] Posterior to be computed for parameters {'Omega_m': 0.33098383397328834, 'b1': 0.5052090479049207}
2023-07-02 10:34:09,093 [prior] Evaluating prior at array([0.33098383, 0.50520905])
2023-07-02 10:34:09,093 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:09,093 [model] Got input parameters: {'Omega_m': 0.33098383397328834, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5052090479049207, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,093 [classy] Got parameters {'Omega_m': 0.33098383397328834, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:09,093 [classy] Re-using computed results
2023-07-02 10:34:09,093 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.09082234795068}
2023-07-02 10:34:09,093 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:09,093 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5052090479049207, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,093 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:09,113 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.62486
2023-07-02 10:34:09,113 [model] Computed derived parameters: {}
2023-07-02 10:34:09,113 [model] Posterior to be computed for parameters {'Omega_m': 0.32374866619499143, 'b1': 0.4529451754183492}
2023-07-02 10:34:09,113 [prior] Evaluating prior at array([0.32374867, 0.45294518])
2023-07-02 10:34:09,113 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:09,114 [model] Got input parameters: {'Omega_m': 0.32374866619499143, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4529451754183492, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,114 [classy] Got parameters {'Omega_m': 0.32374866619499143, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:09,114 [classy] Computing new state
2023-07-02 10:34:09,114 [classy] Setting parameters: {'Omega_m': 0.32374866619499143, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:09,160 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.92598632718128}
2023-07-02 10:34:09,160 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:09,162 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00777023
2023-07-02 10:34:09,162 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4529451754183492, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,162 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:09,181 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.087198
2023-07-02 10:34:09,181 [model] Computed derived parameters: {}
2023-07-02 10:34:09,182 [mcmc] New sample, #471:
Omega_m:0.3309838, b1:0.4428599
2023-07-02 10:34:09,182 [model] Posterior to be computed for parameters {'Omega_m': 0.32374866619499143, 'b1': 0.43206677367818797}
2023-07-02 10:34:09,182 [prior] Evaluating prior at array([0.32374867, 0.43206677])
2023-07-02 10:34:09,182 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:09,182 [model] Got input parameters: {'Omega_m': 0.32374866619499143, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.43206677367818797, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,182 [classy] Got parameters {'Omega_m': 0.32374866619499143, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:09,182 [classy] Re-using computed results
2023-07-02 10:34:09,182 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.92598632718128}
2023-07-02 10:34:09,182 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:09,182 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.43206677367818797, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,182 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:09,202 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.54795
2023-07-02 10:34:09,202 [model] Computed derived parameters: {}
2023-07-02 10:34:09,202 [model] Posterior to be computed for parameters {'Omega_m': 0.3336503038364659, 'b1': 0.43914304174447555}
2023-07-02 10:34:09,202 [prior] Evaluating prior at array([0.3336503 , 0.43914304])
2023-07-02 10:34:09,202 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:09,202 [model] Got input parameters: {'Omega_m': 0.3336503038364659, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.43914304174447555, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,202 [classy] Got parameters {'Omega_m': 0.3336503038364659, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:09,202 [classy] Computing new state
2023-07-02 10:34:09,202 [classy] Setting parameters: {'Omega_m': 0.3336503038364659, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:09,246 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.7871979380322}
2023-07-02 10:34:09,246 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:09,248 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.026292
2023-07-02 10:34:09,248 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.43914304174447555, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,248 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:09,268 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.846923
2023-07-02 10:34:09,268 [model] Computed derived parameters: {}
2023-07-02 10:34:09,268 [mcmc] New sample, #472:
Omega_m:0.3237487, b1:0.4529452
2023-07-02 10:34:09,268 [model] Posterior to be computed for parameters {'Omega_m': 0.3336503038364659, 'b1': 0.38514090415126606}
2023-07-02 10:34:09,268 [prior] Evaluating prior at array([0.3336503, 0.3851409])
2023-07-02 10:34:09,268 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:09,268 [model] Got input parameters: {'Omega_m': 0.3336503038364659, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.38514090415126606, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,268 [classy] Got parameters {'Omega_m': 0.3336503038364659, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:09,268 [classy] Re-using computed results
2023-07-02 10:34:09,268 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.7871979380322}
2023-07-02 10:34:09,268 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:09,268 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.38514090415126606, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,268 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:09,288 [fs_likelihood.fslikelihood] Computed log-likelihood = -15.5553
2023-07-02 10:34:09,288 [model] Computed derived parameters: {}
2023-07-02 10:34:09,288 [model] Posterior to be computed for parameters {'Omega_m': 0.34371613926958433, 'b1': 0.42511202877292564}
2023-07-02 10:34:09,288 [prior] Evaluating prior at array([0.34371614, 0.42511203])
2023-07-02 10:34:09,288 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:09,288 [model] Got input parameters: {'Omega_m': 0.34371613926958433, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42511202877292564, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,288 [classy] Got parameters {'Omega_m': 0.34371613926958433, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:09,288 [classy] Computing new state
2023-07-02 10:34:09,288 [classy] Setting parameters: {'Omega_m': 0.34371613926958433, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:09,332 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.66044241927366}
2023-07-02 10:34:09,332 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:09,334 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.05567
2023-07-02 10:34:09,334 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42511202877292564, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,334 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:09,354 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.58869
2023-07-02 10:34:09,354 [model] Computed derived parameters: {}
2023-07-02 10:34:09,354 [model] Posterior to be computed for parameters {'Omega_m': 0.3336503038364659, 'b1': 0.467354445036929}
2023-07-02 10:34:09,354 [prior] Evaluating prior at array([0.3336503 , 0.46735445])
2023-07-02 10:34:09,354 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:09,354 [model] Got input parameters: {'Omega_m': 0.3336503038364659, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.467354445036929, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,354 [classy] Got parameters {'Omega_m': 0.3336503038364659, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:09,355 [classy] Re-using computed results
2023-07-02 10:34:09,355 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.7871979380322}
2023-07-02 10:34:09,355 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:09,355 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.467354445036929, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,355 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:09,374 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.15325
2023-07-02 10:34:09,374 [model] Computed derived parameters: {}
2023-07-02 10:34:09,374 [mcmc] New sample, #473:
Omega_m:0.3336503, b1:0.439143
2023-07-02 10:34:09,374 [model] Posterior to be computed for parameters {'Omega_m': 0.30785972658723815, 'b1': 0.5033045583019504}
2023-07-02 10:34:09,374 [prior] Evaluating prior at array([0.30785973, 0.50330456])
2023-07-02 10:34:09,374 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:09,374 [model] Got input parameters: {'Omega_m': 0.30785972658723815, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5033045583019504, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,374 [classy] Got parameters {'Omega_m': 0.30785972658723815, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:09,375 [classy] Computing new state
2023-07-02 10:34:09,375 [classy] Setting parameters: {'Omega_m': 0.30785972658723815, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:09,418 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.8202415108137}
2023-07-02 10:34:09,418 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:09,420 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.001529
2023-07-02 10:34:09,420 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5033045583019504, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,420 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:09,440 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.34942
2023-07-02 10:34:09,440 [model] Computed derived parameters: {}
2023-07-02 10:34:09,440 [mcmc] New sample, #474:
Omega_m:0.3336503, b1:0.4673544
2023-07-02 10:34:09,440 [model] Posterior to be computed for parameters {'Omega_m': 0.30785972658723815, 'b1': 0.5246063922512886}
2023-07-02 10:34:09,440 [prior] Evaluating prior at array([0.30785973, 0.52460639])
2023-07-02 10:34:09,440 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:09,440 [model] Got input parameters: {'Omega_m': 0.30785972658723815, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5246063922512886, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,440 [classy] Got parameters {'Omega_m': 0.30785972658723815, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:09,440 [classy] Re-using computed results
2023-07-02 10:34:09,440 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.8202415108137}
2023-07-02 10:34:09,440 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:09,440 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5246063922512886, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,440 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:09,460 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.26979
2023-07-02 10:34:09,460 [model] Computed derived parameters: {}
2023-07-02 10:34:09,460 [mcmc] New sample, #475:
Omega_m:0.3078597, b1:0.5033046
2023-07-02 10:34:09,460 [model] Posterior to be computed for parameters {'Omega_m': 0.31177813781673414, 'b1': 0.5191444234803674}
2023-07-02 10:34:09,460 [prior] Evaluating prior at array([0.31177814, 0.51914442])
2023-07-02 10:34:09,461 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:09,461 [model] Got input parameters: {'Omega_m': 0.31177813781673414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5191444234803674, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,461 [classy] Got parameters {'Omega_m': 0.31177813781673414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:09,461 [classy] Computing new state
2023-07-02 10:34:09,461 [classy] Setting parameters: {'Omega_m': 0.31177813781673414, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:09,504 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.34514685583906}
2023-07-02 10:34:09,504 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:09,506 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000232975
2023-07-02 10:34:09,506 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5191444234803674, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,506 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:09,526 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.40395
2023-07-02 10:34:09,526 [model] Computed derived parameters: {}
2023-07-02 10:34:09,526 [mcmc] New sample, #476:
Omega_m:0.3078597, b1:0.5246064
2023-07-02 10:34:09,526 [model] Posterior to be computed for parameters {'Omega_m': 0.31177813781673414, 'b1': 0.5406754199151753}
2023-07-02 10:34:09,526 [prior] Evaluating prior at array([0.31177814, 0.54067542])
2023-07-02 10:34:09,526 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:09,526 [model] Got input parameters: {'Omega_m': 0.31177813781673414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5406754199151753, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,526 [classy] Got parameters {'Omega_m': 0.31177813781673414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:09,526 [classy] Re-using computed results
2023-07-02 10:34:09,526 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.34514685583906}
2023-07-02 10:34:09,527 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:09,527 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5406754199151753, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,527 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:09,546 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.446116
2023-07-02 10:34:09,546 [model] Computed derived parameters: {}
2023-07-02 10:34:09,546 [model] Posterior to be computed for parameters {'Omega_m': 0.3004490386855843, 'b1': 0.5349363304632826}
2023-07-02 10:34:09,546 [prior] Evaluating prior at array([0.30044904, 0.53493633])
2023-07-02 10:34:09,547 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:09,547 [model] Got input parameters: {'Omega_m': 0.3004490386855843, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5349363304632826, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,547 [classy] Got parameters {'Omega_m': 0.3004490386855843, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:09,547 [classy] Computing new state
2023-07-02 10:34:09,547 [classy] Setting parameters: {'Omega_m': 0.3004490386855843, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:09,590 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.73348283010247}
2023-07-02 10:34:09,591 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:09,592 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00935672
2023-07-02 10:34:09,592 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5349363304632826, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,593 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:09,612 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.44798
2023-07-02 10:34:09,613 [model] Computed derived parameters: {}
2023-07-02 10:34:09,613 [model] Posterior to be computed for parameters {'Omega_m': 0.31177813781673414, 'b1': 0.5463018317387807}
2023-07-02 10:34:09,613 [prior] Evaluating prior at array([0.31177814, 0.54630183])
2023-07-02 10:34:09,613 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:09,613 [model] Got input parameters: {'Omega_m': 0.31177813781673414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5463018317387807, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,613 [classy] Got parameters {'Omega_m': 0.31177813781673414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:09,613 [classy] Re-using computed results
2023-07-02 10:34:09,613 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.34514685583906}
2023-07-02 10:34:09,613 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:09,613 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5463018317387807, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,613 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:09,632 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.63832
2023-07-02 10:34:09,632 [model] Computed derived parameters: {}
2023-07-02 10:34:09,633 [model] Posterior to be computed for parameters {'Omega_m': 0.288658377585924, 'b1': 0.5513716199066377}
2023-07-02 10:34:09,633 [prior] Evaluating prior at array([0.28865838, 0.55137162])
2023-07-02 10:34:09,633 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:09,633 [model] Got input parameters: {'Omega_m': 0.288658377585924, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5513716199066377, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,633 [classy] Got parameters {'Omega_m': 0.288658377585924, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:09,633 [classy] Computing new state
2023-07-02 10:34:09,633 [classy] Setting parameters: {'Omega_m': 0.288658377585924, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:09,676 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.22802773929757}
2023-07-02 10:34:09,677 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:09,678 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0371889
2023-07-02 10:34:09,678 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5513716199066377, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,679 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:09,698 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.52523
2023-07-02 10:34:09,698 [model] Computed derived parameters: {}
2023-07-02 10:34:09,698 [model] Posterior to be computed for parameters {'Omega_m': 0.31177813781673414, 'b1': 0.5282927642057617}
2023-07-02 10:34:09,698 [prior] Evaluating prior at array([0.31177814, 0.52829276])
2023-07-02 10:34:09,698 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:09,698 [model] Got input parameters: {'Omega_m': 0.31177813781673414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5282927642057617, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,698 [classy] Got parameters {'Omega_m': 0.31177813781673414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:09,698 [classy] Re-using computed results
2023-07-02 10:34:09,698 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.34514685583906}
2023-07-02 10:34:09,698 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:09,698 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5282927642057617, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,698 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:09,718 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.519
2023-07-02 10:34:09,718 [model] Computed derived parameters: {}
2023-07-02 10:34:09,718 [model] Posterior to be computed for parameters {'Omega_m': 0.3000758128080709, 'b1': 0.5354565790967422}
2023-07-02 10:34:09,718 [prior] Evaluating prior at array([0.30007581, 0.53545658])
2023-07-02 10:34:09,719 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:09,719 [model] Got input parameters: {'Omega_m': 0.3000758128080709, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5354565790967422, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,719 [classy] Got parameters {'Omega_m': 0.3000758128080709, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:09,719 [classy] Computing new state
2023-07-02 10:34:09,719 [classy] Setting parameters: {'Omega_m': 0.3000758128080709, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:09,764 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.78000381652717}
2023-07-02 10:34:09,764 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:09,765 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00994268
2023-07-02 10:34:09,766 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5354565790967422, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,766 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:09,785 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.38608
2023-07-02 10:34:09,785 [model] Computed derived parameters: {}
2023-07-02 10:34:09,785 [mcmc] New sample, #477:
Omega_m:0.3117781, b1:0.5191444
2023-07-02 10:34:09,785 [model] Posterior to be computed for parameters {'Omega_m': 0.3000758128080709, 'b1': 0.5070957897741949}
2023-07-02 10:34:09,785 [prior] Evaluating prior at array([0.30007581, 0.50709579])
2023-07-02 10:34:09,785 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:09,785 [model] Got input parameters: {'Omega_m': 0.3000758128080709, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5070957897741949, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,785 [classy] Got parameters {'Omega_m': 0.3000758128080709, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:09,785 [classy] Re-using computed results
2023-07-02 10:34:09,785 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.78000381652717}
2023-07-02 10:34:09,785 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:09,785 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5070957897741949, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,785 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:09,805 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.479917
2023-07-02 10:34:09,805 [model] Computed derived parameters: {}
2023-07-02 10:34:09,805 [model] Posterior to be computed for parameters {'Omega_m': 0.2979747866710345, 'b1': 0.5383852505595529}
2023-07-02 10:34:09,805 [prior] Evaluating prior at array([0.29797479, 0.53838525])
2023-07-02 10:34:09,805 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:09,805 [model] Got input parameters: {'Omega_m': 0.2979747866710345, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5383852505595529, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,805 [classy] Got parameters {'Omega_m': 0.2979747866710345, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:09,805 [classy] Computing new state
2023-07-02 10:34:09,805 [classy] Setting parameters: {'Omega_m': 0.2979747866710345, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:09,849 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.0428329909519}
2023-07-02 10:34:09,849 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:09,851 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0135927
2023-07-02 10:34:09,851 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5383852505595529, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,851 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:09,870 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.99959
2023-07-02 10:34:09,870 [model] Computed derived parameters: {}
2023-07-02 10:34:09,870 [model] Posterior to be computed for parameters {'Omega_m': 0.3000758128080709, 'b1': 0.5428226601527582}
2023-07-02 10:34:09,871 [prior] Evaluating prior at array([0.30007581, 0.54282266])
2023-07-02 10:34:09,871 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:09,871 [model] Got input parameters: {'Omega_m': 0.3000758128080709, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5428226601527582, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,871 [classy] Got parameters {'Omega_m': 0.3000758128080709, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:09,871 [classy] Re-using computed results
2023-07-02 10:34:09,871 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.78000381652717}
2023-07-02 10:34:09,871 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:09,871 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5428226601527582, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,871 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:09,890 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.920418
2023-07-02 10:34:09,890 [model] Computed derived parameters: {}
2023-07-02 10:34:09,890 [mcmc] New sample, #478:
Omega_m:0.3000758, b1:0.5354566
2023-07-02 10:34:09,890 [model] Posterior to be computed for parameters {'Omega_m': 0.28648010184992745, 'b1': 0.5617740525213949}
2023-07-02 10:34:09,890 [prior] Evaluating prior at array([0.2864801 , 0.56177405])
2023-07-02 10:34:09,890 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:09,890 [model] Got input parameters: {'Omega_m': 0.28648010184992745, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5617740525213949, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,891 [classy] Got parameters {'Omega_m': 0.28648010184992745, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:09,891 [classy] Computing new state
2023-07-02 10:34:09,891 [classy] Setting parameters: {'Omega_m': 0.28648010184992745, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:09,935 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.50990461007672}
2023-07-02 10:34:09,935 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:09,937 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0445118
2023-07-02 10:34:09,937 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5617740525213949, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,937 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:09,957 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.54927
2023-07-02 10:34:09,957 [model] Computed derived parameters: {}
2023-07-02 10:34:09,957 [model] Posterior to be computed for parameters {'Omega_m': 0.3000758128080709, 'b1': 0.571768274655137}
2023-07-02 10:34:09,957 [prior] Evaluating prior at array([0.30007581, 0.57176827])
2023-07-02 10:34:09,957 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:09,957 [model] Got input parameters: {'Omega_m': 0.3000758128080709, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.571768274655137, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,957 [classy] Got parameters {'Omega_m': 0.3000758128080709, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:09,957 [classy] Re-using computed results
2023-07-02 10:34:09,957 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.78000381652717}
2023-07-02 10:34:09,957 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:09,957 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.571768274655137, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,957 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:09,977 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.89166
2023-07-02 10:34:09,977 [model] Computed derived parameters: {}
2023-07-02 10:34:09,977 [model] Posterior to be computed for parameters {'Omega_m': 0.30977281475773333, 'b1': 0.5293057731496983}
2023-07-02 10:34:09,977 [prior] Evaluating prior at array([0.30977281, 0.52930577])
2023-07-02 10:34:09,977 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:09,977 [model] Got input parameters: {'Omega_m': 0.30977281475773333, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5293057731496983, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:09,977 [classy] Got parameters {'Omega_m': 0.30977281475773333, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:09,977 [classy] Computing new state
2023-07-02 10:34:09,978 [classy] Setting parameters: {'Omega_m': 0.30977281475773333, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:10,021 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.5876236222148}
2023-07-02 10:34:10,021 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:10,023 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000656209
2023-07-02 10:34:10,023 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5293057731496983, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:10,023 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:10,043 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.72153
2023-07-02 10:34:10,043 [model] Computed derived parameters: {}
2023-07-02 10:34:10,043 [mcmc] New sample, #479:
Omega_m:0.3000758, b1:0.5428227
2023-07-02 10:34:10,043 [model] Posterior to be computed for parameters {'Omega_m': 0.30977281475773333, 'b1': 0.48830271168512285}
2023-07-02 10:34:10,043 [prior] Evaluating prior at array([0.30977281, 0.48830271])
2023-07-02 10:34:10,043 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:10,043 [model] Got input parameters: {'Omega_m': 0.30977281475773333, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48830271168512285, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:10,043 [classy] Got parameters {'Omega_m': 0.30977281475773333, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:10,043 [classy] Re-using computed results
2023-07-02 10:34:10,043 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.5876236222148}
2023-07-02 10:34:10,043 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:10,043 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48830271168512285, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:10,043 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:10,063 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.5402
2023-07-02 10:34:10,063 [model] Computed derived parameters: {}
2023-07-02 10:34:10,063 [mcmc] New sample, #480:
Omega_m:0.3097728, b1:0.5293058
2023-07-02 10:34:10,063 [mcmc] Learn + convergence test @ 480 samples accepted.
2023-07-02 10:34:10,063 [mcmc] Ready to check convergence and learn a new proposal covmat
2023-07-02 10:34:10,068 [mcmc] - Acceptance rate: 0.440
2023-07-02 10:34:10,068 [mcmc] - Condition number = 7.86485
2023-07-02 10:34:10,069 [mcmc] - Eigenvalues = array([0.00964271, 0.07583844])
2023-07-02 10:34:10,069 [mcmc] - Convergence of means: R-1 = 0.075838 after 384 accepted steps
2023-07-02 10:34:10,069 [mcmc] - Updated covariance matrix of proposal pdf.
2023-07-02 10:34:10,069 [mcmc] array([[ 9.88650245e-05, -1.53620379e-04],
[-1.53620379e-04, 4.09152797e-04]])
2023-07-02 10:34:10,079 [mcmc] Dumped checkpoint and progress info, and current covmat.
2023-07-02 10:34:10,079 [model] Posterior to be computed for parameters {'Omega_m': 0.2876550464192195, 'b1': 0.5226701734133745}
2023-07-02 10:34:10,079 [prior] Evaluating prior at array([0.28765505, 0.52267017])
2023-07-02 10:34:10,079 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:10,079 [model] Got input parameters: {'Omega_m': 0.2876550464192195, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5226701734133745, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:10,079 [classy] Got parameters {'Omega_m': 0.2876550464192195, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:10,079 [classy] Computing new state
2023-07-02 10:34:10,079 [classy] Setting parameters: {'Omega_m': 0.2876550464192195, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:10,127 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.35763533817433}
2023-07-02 10:34:10,127 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:10,129 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0404747
2023-07-02 10:34:10,129 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5226701734133745, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:10,129 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:10,153 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.75636
2023-07-02 10:34:10,153 [model] Computed derived parameters: {}
2023-07-02 10:34:10,153 [model] Posterior to be computed for parameters {'Omega_m': 0.30977281475773333, 'b1': 0.4973908866124182}
2023-07-02 10:34:10,153 [prior] Evaluating prior at array([0.30977281, 0.49739089])
2023-07-02 10:34:10,153 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:10,153 [model] Got input parameters: {'Omega_m': 0.30977281475773333, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4973908866124182, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:10,153 [classy] Got parameters {'Omega_m': 0.30977281475773333, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:10,153 [classy] Re-using computed results
2023-07-02 10:34:10,153 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.5876236222148}
2023-07-02 10:34:10,153 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:10,153 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4973908866124182, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:10,153 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:10,174 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.34726
2023-07-02 10:34:10,174 [model] Computed derived parameters: {}
2023-07-02 10:34:10,175 [mcmc] New sample, #481:
Omega_m:0.3097728, b1:0.4883027
2023-07-02 10:34:10,175 [model] Posterior to be computed for parameters {'Omega_m': 0.3212122803526875, 'b1': 0.47961579330240944}
2023-07-02 10:34:10,175 [prior] Evaluating prior at array([0.32121228, 0.47961579])
2023-07-02 10:34:10,175 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:10,175 [model] Got input parameters: {'Omega_m': 0.3212122803526875, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47961579330240944, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:10,175 [classy] Got parameters {'Omega_m': 0.3212122803526875, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:10,175 [classy] Computing new state
2023-07-02 10:34:10,175 [classy] Setting parameters: {'Omega_m': 0.3212122803526875, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:10,219 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.2227280707689}
2023-07-02 10:34:10,219 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:10,221 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00477407
2023-07-02 10:34:10,221 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47961579330240944, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:10,221 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:10,241 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.48778
2023-07-02 10:34:10,241 [model] Computed derived parameters: {}
2023-07-02 10:34:10,241 [mcmc] New sample, #482:
Omega_m:0.3097728, b1:0.4973909
2023-07-02 10:34:10,241 [model] Posterior to be computed for parameters {'Omega_m': 0.3212122803526875, 'b1': 0.5077719680531204}
2023-07-02 10:34:10,241 [prior] Evaluating prior at array([0.32121228, 0.50777197])
2023-07-02 10:34:10,242 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:10,242 [model] Got input parameters: {'Omega_m': 0.3212122803526875, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5077719680531204, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:10,242 [classy] Got parameters {'Omega_m': 0.3212122803526875, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:10,242 [classy] Re-using computed results
2023-07-02 10:34:10,242 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.2227280707689}
2023-07-02 10:34:10,242 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:10,242 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5077719680531204, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:10,242 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:10,261 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.76207
2023-07-02 10:34:10,261 [model] Computed derived parameters: {}
2023-07-02 10:34:10,261 [mcmc] New sample, #483:
Omega_m:0.3212123, b1:0.4796158
2023-07-02 10:34:10,262 [model] Posterior to be computed for parameters {'Omega_m': 0.3402567719919574, 'b1': 0.4781798850034525}
2023-07-02 10:34:10,262 [prior] Evaluating prior at array([0.34025677, 0.47817989])
2023-07-02 10:34:10,262 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:10,262 [model] Got input parameters: {'Omega_m': 0.3402567719919574, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4781798850034525, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:10,262 [classy] Got parameters {'Omega_m': 0.3402567719919574, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:10,262 [classy] Computing new state
2023-07-02 10:34:10,262 [classy] Setting parameters: {'Omega_m': 0.3402567719919574, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:10,306 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.04426597993017}
2023-07-02 10:34:10,306 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:10,308 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0444206
2023-07-02 10:34:10,308 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4781798850034525, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:10,308 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:10,328 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.81572
2023-07-02 10:34:10,328 [model] Computed derived parameters: {}
2023-07-02 10:34:10,328 [model] Posterior to be computed for parameters {'Omega_m': 0.3212122803526875, 'b1': 0.4868622028069739}
2023-07-02 10:34:10,328 [prior] Evaluating prior at array([0.32121228, 0.4868622 ])
2023-07-02 10:34:10,329 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:10,329 [model] Got input parameters: {'Omega_m': 0.3212122803526875, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4868622028069739, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:10,329 [classy] Got parameters {'Omega_m': 0.3212122803526875, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:10,329 [classy] Re-using computed results
2023-07-02 10:34:10,329 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.2227280707689}
2023-07-02 10:34:10,329 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:10,329 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4868622028069739, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:10,329 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:10,351 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.71482
2023-07-02 10:34:10,351 [model] Computed derived parameters: {}
2023-07-02 10:34:10,351 [mcmc] New sample, #484:
Omega_m:0.3212123, b1:0.507772
2023-07-02 10:34:10,351 [model] Posterior to be computed for parameters {'Omega_m': 0.35616082891674833, 'b1': 0.4325577681619182}
2023-07-02 10:34:10,351 [prior] Evaluating prior at array([0.35616083, 0.43255777])
2023-07-02 10:34:10,351 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:10,351 [model] Got input parameters: {'Omega_m': 0.35616082891674833, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4325577681619182, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:10,351 [classy] Got parameters {'Omega_m': 0.35616082891674833, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:10,351 [classy] Computing new state
2023-07-02 10:34:10,351 [classy] Setting parameters: {'Omega_m': 0.35616082891674833, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:10,395 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.30838816793508}
2023-07-02 10:34:10,395 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:10,397 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.105589
2023-07-02 10:34:10,397 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4325577681619182, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:10,397 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:10,417 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.12066
2023-07-02 10:34:10,417 [model] Computed derived parameters: {}
2023-07-02 10:34:10,417 [model] Posterior to be computed for parameters {'Omega_m': 0.3212122803526875, 'b1': 0.5094937997039449}
2023-07-02 10:34:10,417 [prior] Evaluating prior at array([0.32121228, 0.5094938 ])
2023-07-02 10:34:10,417 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:10,417 [model] Got input parameters: {'Omega_m': 0.3212122803526875, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5094937997039449, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:10,417 [classy] Got parameters {'Omega_m': 0.3212122803526875, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:10,417 [classy] Re-using computed results
2023-07-02 10:34:10,418 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.2227280707689}
2023-07-02 10:34:10,418 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:10,418 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5094937997039449, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:10,418 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:10,437 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.57398
2023-07-02 10:34:10,437 [model] Computed derived parameters: {}
2023-07-02 10:34:10,437 [model] Posterior to be computed for parameters {'Omega_m': 0.2786443602881498, 'b1': 0.5530059177278788}
2023-07-02 10:34:10,437 [prior] Evaluating prior at array([0.27864436, 0.55300592])
2023-07-02 10:34:10,437 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:10,437 [model] Got input parameters: {'Omega_m': 0.2786443602881498, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5530059177278788, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:10,437 [classy] Got parameters {'Omega_m': 0.2786443602881498, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:10,437 [classy] Computing new state
2023-07-02 10:34:10,437 [classy] Setting parameters: {'Omega_m': 0.2786443602881498, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:10,481 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.53949171478558}
2023-07-02 10:34:10,481 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:10,483 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0768105
2023-07-02 10:34:10,483 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5530059177278788, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:10,483 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:10,502 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.27204
2023-07-02 10:34:10,502 [model] Computed derived parameters: {}
2023-07-02 10:34:10,502 [model] Posterior to be computed for parameters {'Omega_m': 0.3212122803526875, 'b1': 0.4402588014552185}
2023-07-02 10:34:10,502 [prior] Evaluating prior at array([0.32121228, 0.4402588 ])
2023-07-02 10:34:10,503 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:10,503 [model] Got input parameters: {'Omega_m': 0.3212122803526875, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4402588014552185, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:10,503 [classy] Got parameters {'Omega_m': 0.3212122803526875, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:10,503 [classy] Re-using computed results
2023-07-02 10:34:10,503 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.2227280707689}
2023-07-02 10:34:10,503 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:10,503 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4402588014552185, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:10,503 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:10,523 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.42149
2023-07-02 10:34:10,523 [model] Computed derived parameters: {}
2023-07-02 10:34:10,523 [model] Posterior to be computed for parameters {'Omega_m': 0.34374748760247814, 'b1': 0.4518461080164884}
2023-07-02 10:34:10,523 [prior] Evaluating prior at array([0.34374749, 0.45184611])
2023-07-02 10:34:10,523 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:10,523 [model] Got input parameters: {'Omega_m': 0.34374748760247814, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4518461080164884, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:10,523 [classy] Got parameters {'Omega_m': 0.34374748760247814, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:10,523 [classy] Computing new state
2023-07-02 10:34:10,523 [classy] Setting parameters: {'Omega_m': 0.34374748760247814, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:10,568 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.65697863221948}
2023-07-02 10:34:10,568 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:10,570 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0557774
2023-07-02 10:34:10,570 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4518461080164884, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:10,570 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:10,589 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.16934
2023-07-02 10:34:10,589 [model] Computed derived parameters: {}
2023-07-02 10:34:10,589 [model] Posterior to be computed for parameters {'Omega_m': 0.3212122803526875, 'b1': 0.5324665155345822}
2023-07-02 10:34:10,589 [prior] Evaluating prior at array([0.32121228, 0.53246652])
2023-07-02 10:34:10,590 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:10,590 [model] Got input parameters: {'Omega_m': 0.3212122803526875, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5324665155345822, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:10,590 [classy] Got parameters {'Omega_m': 0.3212122803526875, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:10,590 [classy] Re-using computed results
2023-07-02 10:34:10,590 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.2227280707689}
2023-07-02 10:34:10,590 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:10,590 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5324665155345822, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:10,590 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:10,609 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.60425
2023-07-02 10:34:10,609 [model] Computed derived parameters: {}
2023-07-02 10:34:10,609 [model] Posterior to be computed for parameters {'Omega_m': 0.3054329834910202, 'b1': 0.5113806972903333}
2023-07-02 10:34:10,609 [prior] Evaluating prior at array([0.30543298, 0.5113807 ])
2023-07-02 10:34:10,609 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:10,609 [model] Got input parameters: {'Omega_m': 0.3054329834910202, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5113806972903333, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:10,610 [classy] Got parameters {'Omega_m': 0.3054329834910202, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:10,610 [classy] Computing new state
2023-07-02 10:34:10,610 [classy] Setting parameters: {'Omega_m': 0.3054329834910202, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:10,654 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.11715388676632}
2023-07-02 10:34:10,654 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:10,656 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00330551
2023-07-02 10:34:10,656 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5113806972903333, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:10,656 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:10,675 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.26214
2023-07-02 10:34:10,676 [model] Computed derived parameters: {}
2023-07-02 10:34:10,676 [mcmc] New sample, #485:
Omega_m:0.3212123, b1:0.4868622
2023-07-02 10:34:10,676 [model] Posterior to be computed for parameters {'Omega_m': 0.3054329834910202, 'b1': 0.5329205877126157}
2023-07-02 10:34:10,676 [prior] Evaluating prior at array([0.30543298, 0.53292059])
2023-07-02 10:34:10,676 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:10,676 [model] Got input parameters: {'Omega_m': 0.3054329834910202, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5329205877126157, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:10,676 [classy] Got parameters {'Omega_m': 0.3054329834910202, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:10,676 [classy] Re-using computed results
2023-07-02 10:34:10,676 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.11715388676632}
2023-07-02 10:34:10,676 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:10,676 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5329205877126157, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:10,676 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:10,695 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.74253
2023-07-02 10:34:10,695 [model] Computed derived parameters: {}
2023-07-02 10:34:10,696 [mcmc] New sample, #486:
Omega_m:0.305433, b1:0.5113807
2023-07-02 10:34:10,696 [model] Posterior to be computed for parameters {'Omega_m': 0.3466714096573025, 'b1': 0.46884269290370983}
2023-07-02 10:34:10,696 [prior] Evaluating prior at array([0.34667141, 0.46884269])
2023-07-02 10:34:10,696 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:10,696 [model] Got input parameters: {'Omega_m': 0.3466714096573025, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46884269290370983, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:10,696 [classy] Got parameters {'Omega_m': 0.3466714096573025, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:10,696 [classy] Computing new state
2023-07-02 10:34:10,696 [classy] Setting parameters: {'Omega_m': 0.3466714096573025, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:10,739 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.33535407585987}
2023-07-02 10:34:10,739 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:10,741 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0662049
2023-07-02 10:34:10,741 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46884269290370983, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:10,741 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:10,761 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.83556
2023-07-02 10:34:10,761 [model] Computed derived parameters: {}
2023-07-02 10:34:10,761 [model] Posterior to be computed for parameters {'Omega_m': 0.3054329834910202, 'b1': 0.5379059386432731}
2023-07-02 10:34:10,761 [prior] Evaluating prior at array([0.30543298, 0.53790594])
2023-07-02 10:34:10,762 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:10,762 [model] Got input parameters: {'Omega_m': 0.3054329834910202, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5379059386432731, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:10,762 [classy] Got parameters {'Omega_m': 0.3054329834910202, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:10,762 [classy] Re-using computed results
2023-07-02 10:34:10,762 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.11715388676632}
2023-07-02 10:34:10,762 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:10,762 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5379059386432731, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:10,762 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:10,781 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.2588
2023-07-02 10:34:10,782 [model] Computed derived parameters: {}
2023-07-02 10:34:10,782 [model] Posterior to be computed for parameters {'Omega_m': 0.3066714828185073, 'b1': 0.5309961585574482}
2023-07-02 10:34:10,782 [prior] Evaluating prior at array([0.30667148, 0.53099616])
2023-07-02 10:34:10,782 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:10,782 [model] Got input parameters: {'Omega_m': 0.3066714828185073, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5309961585574482, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:10,782 [classy] Got parameters {'Omega_m': 0.3066714828185073, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:10,782 [classy] Computing new state
2023-07-02 10:34:10,782 [classy] Setting parameters: {'Omega_m': 0.3066714828185073, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:10,826 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.96536631029784}
2023-07-02 10:34:10,826 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:10,827 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00230461
2023-07-02 10:34:10,827 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5309961585574482, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:10,828 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:10,847 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.84926
2023-07-02 10:34:10,847 [model] Computed derived parameters: {}
2023-07-02 10:34:10,847 [mcmc] New sample, #487:
Omega_m:0.305433, b1:0.5329206
2023-07-02 10:34:10,848 [model] Posterior to be computed for parameters {'Omega_m': 0.3066714828185073, 'b1': 0.5058593757988544}
2023-07-02 10:34:10,848 [prior] Evaluating prior at array([0.30667148, 0.50585938])
2023-07-02 10:34:10,848 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:10,848 [model] Got input parameters: {'Omega_m': 0.3066714828185073, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5058593757988544, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:10,848 [classy] Got parameters {'Omega_m': 0.3066714828185073, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:10,848 [classy] Re-using computed results
2023-07-02 10:34:10,848 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.96536631029784}
2023-07-02 10:34:10,848 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:10,848 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5058593757988544, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:10,848 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:10,867 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.25892
2023-07-02 10:34:10,867 [model] Computed derived parameters: {}
2023-07-02 10:34:10,868 [mcmc] New sample, #488:
Omega_m:0.3066715, b1:0.5309962
2023-07-02 10:34:10,868 [model] Posterior to be computed for parameters {'Omega_m': 0.31286773444713223, 'b1': 0.49623139536944677}
2023-07-02 10:34:10,868 [prior] Evaluating prior at array([0.31286773, 0.4962314 ])
2023-07-02 10:34:10,868 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:10,868 [model] Got input parameters: {'Omega_m': 0.31286773444713223, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49623139536944677, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:10,868 [classy] Got parameters {'Omega_m': 0.31286773444713223, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:10,868 [classy] Computing new state
2023-07-02 10:34:10,868 [classy] Setting parameters: {'Omega_m': 0.31286773444713223, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:10,912 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.21397528964653}
2023-07-02 10:34:10,912 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:10,914 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000211395
2023-07-02 10:34:10,914 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49623139536944677, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:10,914 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:10,934 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.72575
2023-07-02 10:34:10,934 [model] Computed derived parameters: {}
2023-07-02 10:34:10,934 [mcmc] New sample, #489:
Omega_m:0.3066715, b1:0.5058594
2023-07-02 10:34:10,934 [model] Posterior to be computed for parameters {'Omega_m': 0.31286773444713223, 'b1': 0.44778581706410786}
2023-07-02 10:34:10,934 [prior] Evaluating prior at array([0.31286773, 0.44778582])
2023-07-02 10:34:10,934 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:10,934 [model] Got input parameters: {'Omega_m': 0.31286773444713223, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44778581706410786, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:10,934 [classy] Got parameters {'Omega_m': 0.31286773444713223, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:10,934 [classy] Re-using computed results
2023-07-02 10:34:10,934 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.21397528964653}
2023-07-02 10:34:10,934 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:10,934 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44778581706410786, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:10,934 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:10,956 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.19744
2023-07-02 10:34:10,957 [model] Computed derived parameters: {}
2023-07-02 10:34:10,957 [model] Posterior to be computed for parameters {'Omega_m': 0.31733409461281564, 'b1': 0.48929138859708965}
2023-07-02 10:34:10,957 [prior] Evaluating prior at array([0.31733409, 0.48929139])
2023-07-02 10:34:10,957 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:10,957 [model] Got input parameters: {'Omega_m': 0.31733409461281564, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48929138859708965, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:10,957 [classy] Got parameters {'Omega_m': 0.31733409461281564, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:10,957 [classy] Computing new state
2023-07-02 10:34:10,957 [classy] Setting parameters: {'Omega_m': 0.31733409461281564, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:11,001 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.68051795120985}
2023-07-02 10:34:11,001 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:11,003 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00162761
2023-07-02 10:34:11,003 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48929138859708965, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,003 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:11,022 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.77636
2023-07-02 10:34:11,023 [model] Computed derived parameters: {}
2023-07-02 10:34:11,023 [mcmc] New sample, #490:
Omega_m:0.3128677, b1:0.4962314
2023-07-02 10:34:11,023 [model] Posterior to be computed for parameters {'Omega_m': 0.31733409461281564, 'b1': 0.4502550344028314}
2023-07-02 10:34:11,023 [prior] Evaluating prior at array([0.31733409, 0.45025503])
2023-07-02 10:34:11,023 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:11,023 [model] Got input parameters: {'Omega_m': 0.31733409461281564, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4502550344028314, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,023 [classy] Got parameters {'Omega_m': 0.31733409461281564, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:11,023 [classy] Re-using computed results
2023-07-02 10:34:11,023 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.68051795120985}
2023-07-02 10:34:11,023 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:11,023 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4502550344028314, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,023 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:11,043 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.52291
2023-07-02 10:34:11,043 [model] Computed derived parameters: {}
2023-07-02 10:34:11,043 [model] Posterior to be computed for parameters {'Omega_m': 0.32340872317006497, 'b1': 0.47985239089807324}
2023-07-02 10:34:11,043 [prior] Evaluating prior at array([0.32340872, 0.47985239])
2023-07-02 10:34:11,043 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:11,043 [model] Got input parameters: {'Omega_m': 0.32340872317006497, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47985239089807324, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,043 [classy] Got parameters {'Omega_m': 0.32340872317006497, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:11,043 [classy] Computing new state
2023-07-02 10:34:11,043 [classy] Setting parameters: {'Omega_m': 0.32340872317006497, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:11,087 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.9656353100497}
2023-07-02 10:34:11,088 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:11,089 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00732628
2023-07-02 10:34:11,089 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47985239089807324, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,089 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:11,109 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.4859
2023-07-02 10:34:11,109 [model] Computed derived parameters: {}
2023-07-02 10:34:11,109 [mcmc] New sample, #491:
Omega_m:0.3173341, b1:0.4892914
2023-07-02 10:34:11,109 [model] Posterior to be computed for parameters {'Omega_m': 0.32340872317006497, 'b1': 0.4539720339372655}
2023-07-02 10:34:11,109 [prior] Evaluating prior at array([0.32340872, 0.45397203])
2023-07-02 10:34:11,109 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:11,109 [model] Got input parameters: {'Omega_m': 0.32340872317006497, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4539720339372655, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,109 [classy] Got parameters {'Omega_m': 0.32340872317006497, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:11,109 [classy] Re-using computed results
2023-07-02 10:34:11,109 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.9656353100497}
2023-07-02 10:34:11,109 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:11,109 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4539720339372655, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,109 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:11,131 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.0105943
2023-07-02 10:34:11,131 [model] Computed derived parameters: {}
2023-07-02 10:34:11,131 [mcmc] New sample, #492:
Omega_m:0.3234087, b1:0.4798524
2023-07-02 10:34:11,131 [model] Posterior to be computed for parameters {'Omega_m': 0.32904803702618124, 'b1': 0.44520944540855784}
2023-07-02 10:34:11,131 [prior] Evaluating prior at array([0.32904804, 0.44520945])
2023-07-02 10:34:11,131 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:11,131 [model] Got input parameters: {'Omega_m': 0.32904803702618124, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44520944540855784, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,131 [classy] Got parameters {'Omega_m': 0.32904803702618124, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:11,131 [classy] Computing new state
2023-07-02 10:34:11,131 [classy] Setting parameters: {'Omega_m': 0.32904803702618124, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:11,178 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.3126370430071}
2023-07-02 10:34:11,178 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:11,180 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0163582
2023-07-02 10:34:11,180 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44520944540855784, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,180 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:11,199 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.42269
2023-07-02 10:34:11,199 [model] Computed derived parameters: {}
2023-07-02 10:34:11,200 [mcmc] New sample, #493:
Omega_m:0.3234087, b1:0.453972
2023-07-02 10:34:11,200 [model] Posterior to be computed for parameters {'Omega_m': 0.32904803702618124, 'b1': 0.4245721285514948}
2023-07-02 10:34:11,200 [prior] Evaluating prior at array([0.32904804, 0.42457213])
2023-07-02 10:34:11,200 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:11,200 [model] Got input parameters: {'Omega_m': 0.32904803702618124, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4245721285514948, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,200 [classy] Got parameters {'Omega_m': 0.32904803702618124, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:11,200 [classy] Re-using computed results
2023-07-02 10:34:11,200 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.3126370430071}
2023-07-02 10:34:11,200 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:11,200 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4245721285514948, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,200 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:11,220 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.65487
2023-07-02 10:34:11,220 [model] Computed derived parameters: {}
2023-07-02 10:34:11,220 [model] Posterior to be computed for parameters {'Omega_m': 0.2839196966240372, 'b1': 0.5153316425440403}
2023-07-02 10:34:11,220 [prior] Evaluating prior at array([0.2839197 , 0.51533164])
2023-07-02 10:34:11,220 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:11,220 [model] Got input parameters: {'Omega_m': 0.2839196966240372, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5153316425440403, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,220 [classy] Got parameters {'Omega_m': 0.2839196966240372, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:11,220 [classy] Computing new state
2023-07-02 10:34:11,220 [classy] Setting parameters: {'Omega_m': 0.2839196966240372, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:11,265 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.84364960344837}
2023-07-02 10:34:11,265 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:11,266 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0540292
2023-07-02 10:34:11,266 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5153316425440403, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,266 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:11,287 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.62467
2023-07-02 10:34:11,287 [model] Computed derived parameters: {}
2023-07-02 10:34:11,287 [model] Posterior to be computed for parameters {'Omega_m': 0.32904803702618124, 'b1': 0.4949225915041542}
2023-07-02 10:34:11,287 [prior] Evaluating prior at array([0.32904804, 0.49492259])
2023-07-02 10:34:11,287 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:11,287 [model] Got input parameters: {'Omega_m': 0.32904803702618124, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4949225915041542, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,287 [classy] Got parameters {'Omega_m': 0.32904803702618124, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:11,287 [classy] Re-using computed results
2023-07-02 10:34:11,287 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.3126370430071}
2023-07-02 10:34:11,287 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:11,287 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4949225915041542, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,287 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:11,307 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.788821
2023-07-02 10:34:11,307 [model] Computed derived parameters: {}
2023-07-02 10:34:11,307 [mcmc] New sample, #494:
Omega_m:0.329048, b1:0.4452094
2023-07-02 10:34:11,307 [model] Posterior to be computed for parameters {'Omega_m': 0.2907598772433001, 'b1': 0.5544162459200938}
2023-07-02 10:34:11,307 [prior] Evaluating prior at array([0.29075988, 0.55441625])
2023-07-02 10:34:11,307 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:11,307 [model] Got input parameters: {'Omega_m': 0.2907598772433001, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5544162459200938, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,307 [classy] Got parameters {'Omega_m': 0.2907598772433001, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:11,307 [classy] Computing new state
2023-07-02 10:34:11,307 [classy] Setting parameters: {'Omega_m': 0.2907598772433001, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:11,351 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.95782073641158}
2023-07-02 10:34:11,351 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:11,353 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0307848
2023-07-02 10:34:11,353 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5544162459200938, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,353 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:11,373 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.06137
2023-07-02 10:34:11,373 [model] Computed derived parameters: {}
2023-07-02 10:34:11,373 [model] Posterior to be computed for parameters {'Omega_m': 0.32904803702618124, 'b1': 0.5187889953109394}
2023-07-02 10:34:11,373 [prior] Evaluating prior at array([0.32904804, 0.518789 ])
2023-07-02 10:34:11,373 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:11,373 [model] Got input parameters: {'Omega_m': 0.32904803702618124, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5187889953109394, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,373 [classy] Got parameters {'Omega_m': 0.32904803702618124, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:11,373 [classy] Re-using computed results
2023-07-02 10:34:11,373 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.3126370430071}
2023-07-02 10:34:11,373 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:11,373 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5187889953109394, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,373 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:11,393 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.5944
2023-07-02 10:34:11,393 [model] Computed derived parameters: {}
2023-07-02 10:34:11,393 [model] Posterior to be computed for parameters {'Omega_m': 0.337995520386764, 'b1': 0.4810196385817501}
2023-07-02 10:34:11,393 [prior] Evaluating prior at array([0.33799552, 0.48101964])
2023-07-02 10:34:11,394 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:11,394 [model] Got input parameters: {'Omega_m': 0.337995520386764, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4810196385817501, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,394 [classy] Got parameters {'Omega_m': 0.337995520386764, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:11,394 [classy] Computing new state
2023-07-02 10:34:11,394 [classy] Setting parameters: {'Omega_m': 0.337995520386764, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:11,438 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.29707682698384}
2023-07-02 10:34:11,438 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:11,439 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.037713
2023-07-02 10:34:11,439 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4810196385817501, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,440 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:11,459 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.12921
2023-07-02 10:34:11,459 [model] Computed derived parameters: {}
2023-07-02 10:34:11,459 [model] Posterior to be computed for parameters {'Omega_m': 0.32904803702618124, 'b1': 0.48427276970913385}
2023-07-02 10:34:11,459 [prior] Evaluating prior at array([0.32904804, 0.48427277])
2023-07-02 10:34:11,459 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:11,459 [model] Got input parameters: {'Omega_m': 0.32904803702618124, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48427276970913385, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,459 [classy] Got parameters {'Omega_m': 0.32904803702618124, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:11,460 [classy] Re-using computed results
2023-07-02 10:34:11,460 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.3126370430071}
2023-07-02 10:34:11,460 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:11,460 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48427276970913385, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,460 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:11,479 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.66519
2023-07-02 10:34:11,479 [model] Computed derived parameters: {}
2023-07-02 10:34:11,479 [mcmc] New sample, #495:
Omega_m:0.329048, b1:0.4949226
2023-07-02 10:34:11,479 [model] Posterior to be computed for parameters {'Omega_m': 0.31429874856944495, 'b1': 0.5071907964647161}
2023-07-02 10:34:11,479 [prior] Evaluating prior at array([0.31429875, 0.5071908 ])
2023-07-02 10:34:11,480 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:11,480 [model] Got input parameters: {'Omega_m': 0.31429874856944495, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5071907964647161, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,480 [classy] Got parameters {'Omega_m': 0.31429874856944495, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:11,480 [classy] Computing new state
2023-07-02 10:34:11,480 [classy] Setting parameters: {'Omega_m': 0.31429874856944495, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:11,523 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.04231280591648}
2023-07-02 10:34:11,523 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:11,525 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00040348
2023-07-02 10:34:11,525 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5071907964647161, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,525 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:11,545 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.83819
2023-07-02 10:34:11,545 [model] Computed derived parameters: {}
2023-07-02 10:34:11,545 [mcmc] New sample, #496:
Omega_m:0.329048, b1:0.4842728
2023-07-02 10:34:11,545 [model] Posterior to be computed for parameters {'Omega_m': 0.31429874856944495, 'b1': 0.489110175699167}
2023-07-02 10:34:11,545 [prior] Evaluating prior at array([0.31429875, 0.48911018])
2023-07-02 10:34:11,545 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:11,545 [model] Got input parameters: {'Omega_m': 0.31429874856944495, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.489110175699167, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,546 [classy] Got parameters {'Omega_m': 0.31429874856944495, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:11,546 [classy] Re-using computed results
2023-07-02 10:34:11,546 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.04231280591648}
2023-07-02 10:34:11,546 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:11,546 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.489110175699167, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,546 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:11,567 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.50578
2023-07-02 10:34:11,567 [model] Computed derived parameters: {}
2023-07-02 10:34:11,567 [mcmc] New sample, #497:
Omega_m:0.3142987, b1:0.5071908
2023-07-02 10:34:11,567 [model] Posterior to be computed for parameters {'Omega_m': 0.34191966598971385, 'b1': 0.4461917036448533}
2023-07-02 10:34:11,567 [prior] Evaluating prior at array([0.34191967, 0.4461917 ])
2023-07-02 10:34:11,567 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:11,567 [model] Got input parameters: {'Omega_m': 0.34191966598971385, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4461917036448533, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,567 [classy] Got parameters {'Omega_m': 0.34191966598971385, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:11,567 [classy] Computing new state
2023-07-02 10:34:11,567 [classy] Setting parameters: {'Omega_m': 0.34191966598971385, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:11,611 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.85932444806298}
2023-07-02 10:34:11,611 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:11,613 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0496803
2023-07-02 10:34:11,613 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4461917036448533, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,613 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:11,633 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.740624
2023-07-02 10:34:11,633 [model] Computed derived parameters: {}
2023-07-02 10:34:11,634 [model] Posterior to be computed for parameters {'Omega_m': 0.31429874856944495, 'b1': 0.5011307796774415}
2023-07-02 10:34:11,634 [prior] Evaluating prior at array([0.31429875, 0.50113078])
2023-07-02 10:34:11,634 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:11,634 [model] Got input parameters: {'Omega_m': 0.31429874856944495, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5011307796774415, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,634 [classy] Got parameters {'Omega_m': 0.31429874856944495, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:11,634 [classy] Re-using computed results
2023-07-02 10:34:11,634 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.04231280591648}
2023-07-02 10:34:11,634 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:11,634 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5011307796774415, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,634 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:11,654 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.92159
2023-07-02 10:34:11,654 [model] Computed derived parameters: {}
2023-07-02 10:34:11,654 [mcmc] New sample, #498:
Omega_m:0.3142987, b1:0.4891102
2023-07-02 10:34:11,654 [model] Posterior to be computed for parameters {'Omega_m': 0.3201845618147824, 'b1': 0.4919851706651371}
2023-07-02 10:34:11,654 [prior] Evaluating prior at array([0.32018456, 0.49198517])
2023-07-02 10:34:11,654 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:11,655 [model] Got input parameters: {'Omega_m': 0.3201845618147824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4919851706651371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,655 [classy] Got parameters {'Omega_m': 0.3201845618147824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:11,655 [classy] Computing new state
2023-07-02 10:34:11,655 [classy] Setting parameters: {'Omega_m': 0.3201845618147824, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:11,699 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.34356305948222}
2023-07-02 10:34:11,699 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:11,701 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00376979
2023-07-02 10:34:11,701 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4919851706651371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,701 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:11,720 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.78653
2023-07-02 10:34:11,721 [model] Computed derived parameters: {}
2023-07-02 10:34:11,721 [mcmc] New sample, #499:
Omega_m:0.3142987, b1:0.5011308
2023-07-02 10:34:11,721 [model] Posterior to be computed for parameters {'Omega_m': 0.3201845618147824, 'b1': 0.4578581486724014}
2023-07-02 10:34:11,721 [prior] Evaluating prior at array([0.32018456, 0.45785815])
2023-07-02 10:34:11,721 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:11,721 [model] Got input parameters: {'Omega_m': 0.3201845618147824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4578581486724014, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,721 [classy] Got parameters {'Omega_m': 0.3201845618147824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:11,721 [classy] Re-using computed results
2023-07-02 10:34:11,721 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.34356305948222}
2023-07-02 10:34:11,721 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:11,721 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4578581486724014, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,721 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:11,741 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.0775476
2023-07-02 10:34:11,741 [model] Computed derived parameters: {}
2023-07-02 10:34:11,741 [model] Posterior to be computed for parameters {'Omega_m': 0.3292262943898907, 'b1': 0.47793576959192724}
2023-07-02 10:34:11,741 [prior] Evaluating prior at array([0.32922629, 0.47793577])
2023-07-02 10:34:11,742 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:11,742 [model] Got input parameters: {'Omega_m': 0.3292262943898907, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47793576959192724, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,742 [classy] Got parameters {'Omega_m': 0.3292262943898907, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:11,742 [classy] Computing new state
2023-07-02 10:34:11,742 [classy] Setting parameters: {'Omega_m': 0.3292262943898907, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:11,787 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.29216029083068}
2023-07-02 10:34:11,788 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:11,789 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0167008
2023-07-02 10:34:11,789 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47793576959192724, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,789 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:11,809 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.85172
2023-07-02 10:34:11,809 [model] Computed derived parameters: {}
2023-07-02 10:34:11,809 [model] Posterior to be computed for parameters {'Omega_m': 0.3201845618147824, 'b1': 0.5029801116990682}
2023-07-02 10:34:11,809 [prior] Evaluating prior at array([0.32018456, 0.50298011])
2023-07-02 10:34:11,810 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:11,810 [model] Got input parameters: {'Omega_m': 0.3201845618147824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5029801116990682, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,810 [classy] Got parameters {'Omega_m': 0.3201845618147824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:11,810 [classy] Re-using computed results
2023-07-02 10:34:11,810 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.34356305948222}
2023-07-02 10:34:11,810 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:11,810 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5029801116990682, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,810 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:11,829 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.39189
2023-07-02 10:34:11,829 [model] Computed derived parameters: {}
2023-07-02 10:34:11,829 [mcmc] New sample, #500:
Omega_m:0.3201846, b1:0.4919852
2023-07-02 10:34:11,829 [model] Posterior to be computed for parameters {'Omega_m': 0.35558158292288444, 'b1': 0.4479788227078772}
2023-07-02 10:34:11,829 [prior] Evaluating prior at array([0.35558158, 0.44797882])
2023-07-02 10:34:11,830 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:11,830 [model] Got input parameters: {'Omega_m': 0.35558158292288444, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4479788227078772, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,830 [classy] Got parameters {'Omega_m': 0.35558158292288444, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:11,830 [classy] Computing new state
2023-07-02 10:34:11,830 [classy] Setting parameters: {'Omega_m': 0.35558158292288444, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:11,874 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.37035377757368}
2023-07-02 10:34:11,875 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:11,876 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.102949
2023-07-02 10:34:11,876 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4479788227078772, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,876 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:11,896 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.03981
2023-07-02 10:34:11,896 [model] Computed derived parameters: {}
2023-07-02 10:34:11,896 [model] Posterior to be computed for parameters {'Omega_m': 0.3201845618147824, 'b1': 0.4974214964933156}
2023-07-02 10:34:11,896 [prior] Evaluating prior at array([0.32018456, 0.4974215 ])
2023-07-02 10:34:11,896 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:11,896 [model] Got input parameters: {'Omega_m': 0.3201845618147824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4974214964933156, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,896 [classy] Got parameters {'Omega_m': 0.3201845618147824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:11,896 [classy] Re-using computed results
2023-07-02 10:34:11,897 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.34356305948222}
2023-07-02 10:34:11,897 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:11,897 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4974214964933156, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,897 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:11,916 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.67489
2023-07-02 10:34:11,916 [model] Computed derived parameters: {}
2023-07-02 10:34:11,916 [mcmc] New sample, #501:
Omega_m:0.3201846, b1:0.5029801
2023-07-02 10:34:11,916 [model] Posterior to be computed for parameters {'Omega_m': 0.3043702957252894, 'b1': 0.5219943275435732}
2023-07-02 10:34:11,917 [prior] Evaluating prior at array([0.3043703 , 0.52199433])
2023-07-02 10:34:11,917 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:11,917 [model] Got input parameters: {'Omega_m': 0.3043702957252894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5219943275435732, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,917 [classy] Got parameters {'Omega_m': 0.3043702957252894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:11,917 [classy] Computing new state
2023-07-02 10:34:11,917 [classy] Setting parameters: {'Omega_m': 0.3043702957252894, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:11,963 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.24782602547376}
2023-07-02 10:34:11,963 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:11,965 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00432232
2023-07-02 10:34:11,965 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5219943275435732, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,965 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:11,985 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.22297
2023-07-02 10:34:11,985 [model] Computed derived parameters: {}
2023-07-02 10:34:11,985 [model] Posterior to be computed for parameters {'Omega_m': 0.3201845618147824, 'b1': 0.5232027580406549}
2023-07-02 10:34:11,985 [prior] Evaluating prior at array([0.32018456, 0.52320276])
2023-07-02 10:34:11,985 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:11,985 [model] Got input parameters: {'Omega_m': 0.3201845618147824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5232027580406549, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,985 [classy] Got parameters {'Omega_m': 0.3201845618147824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:11,985 [classy] Re-using computed results
2023-07-02 10:34:11,985 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.34356305948222}
2023-07-02 10:34:11,985 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:11,985 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5232027580406549, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:11,985 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:12,005 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.123277
2023-07-02 10:34:12,005 [model] Computed derived parameters: {}
2023-07-02 10:34:12,005 [model] Posterior to be computed for parameters {'Omega_m': 0.30914366468903215, 'b1': 0.5145772783790518}
2023-07-02 10:34:12,005 [prior] Evaluating prior at array([0.30914366, 0.51457728])
2023-07-02 10:34:12,005 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:12,005 [model] Got input parameters: {'Omega_m': 0.30914366468903215, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5145772783790518, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:12,005 [classy] Got parameters {'Omega_m': 0.30914366468903215, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:12,005 [classy] Computing new state
2023-07-02 10:34:12,005 [classy] Setting parameters: {'Omega_m': 0.30914366468903215, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:12,051 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.6639848881993}
2023-07-02 10:34:12,051 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:12,054 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000892373
2023-07-02 10:34:12,054 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5145772783790518, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:12,054 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:12,073 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.68101
2023-07-02 10:34:12,074 [model] Computed derived parameters: {}
2023-07-02 10:34:12,074 [mcmc] New sample, #502:
Omega_m:0.3201846, b1:0.4974215
2023-07-02 10:34:12,074 [model] Posterior to be computed for parameters {'Omega_m': 0.30914366468903215, 'b1': 0.47217468032976423}
2023-07-02 10:34:12,074 [prior] Evaluating prior at array([0.30914366, 0.47217468])
2023-07-02 10:34:12,074 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:12,074 [model] Got input parameters: {'Omega_m': 0.30914366468903215, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47217468032976423, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:12,074 [classy] Got parameters {'Omega_m': 0.30914366468903215, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:12,074 [classy] Re-using computed results
2023-07-02 10:34:12,074 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.6639848881993}
2023-07-02 10:34:12,074 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:12,074 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47217468032976423, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:12,074 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:12,094 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.16686
2023-07-02 10:34:12,094 [model] Computed derived parameters: {}
2023-07-02 10:34:12,094 [model] Posterior to be computed for parameters {'Omega_m': 0.30806010437272374, 'b1': 0.5162609571811367}
2023-07-02 10:34:12,094 [prior] Evaluating prior at array([0.3080601 , 0.51626096])
2023-07-02 10:34:12,094 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:12,094 [model] Got input parameters: {'Omega_m': 0.30806010437272374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5162609571811367, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:12,094 [classy] Got parameters {'Omega_m': 0.30806010437272374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:12,094 [classy] Computing new state
2023-07-02 10:34:12,094 [classy] Setting parameters: {'Omega_m': 0.30806010437272374, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:12,141 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.79581679673825}
2023-07-02 10:34:12,141 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:12,143 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0014159
2023-07-02 10:34:12,143 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5162609571811367, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:12,143 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:12,164 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.60262
2023-07-02 10:34:12,164 [model] Computed derived parameters: {}
2023-07-02 10:34:12,164 [model] Posterior to be computed for parameters {'Omega_m': 0.30914366468903215, 'b1': 0.4930934681429082}
2023-07-02 10:34:12,164 [prior] Evaluating prior at array([0.30914366, 0.49309347])
2023-07-02 10:34:12,164 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:12,164 [model] Got input parameters: {'Omega_m': 0.30914366468903215, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4930934681429082, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:12,164 [classy] Got parameters {'Omega_m': 0.30914366468903215, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:12,164 [classy] Re-using computed results
2023-07-02 10:34:12,165 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.6639848881993}
2023-07-02 10:34:12,165 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:12,165 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4930934681429082, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:12,165 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:12,184 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.87314
2023-07-02 10:34:12,184 [model] Computed derived parameters: {}
2023-07-02 10:34:12,184 [mcmc] New sample, #503:
Omega_m:0.3091437, b1:0.5145773
2023-07-02 10:34:12,185 [model] Posterior to be computed for parameters {'Omega_m': 0.3224465495168355, 'b1': 0.4724229204548411}
2023-07-02 10:34:12,185 [prior] Evaluating prior at array([0.32244655, 0.47242292])
2023-07-02 10:34:12,185 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:12,185 [model] Got input parameters: {'Omega_m': 0.3224465495168355, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4724229204548411, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:12,185 [classy] Got parameters {'Omega_m': 0.3224465495168355, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:12,185 [classy] Computing new state
2023-07-02 10:34:12,185 [classy] Setting parameters: {'Omega_m': 0.3224465495168355, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:12,229 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.07806539681823}
2023-07-02 10:34:12,229 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:12,230 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00614055
2023-07-02 10:34:12,230 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4724229204548411, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:12,230 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:12,250 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.08399
2023-07-02 10:34:12,251 [model] Computed derived parameters: {}
2023-07-02 10:34:12,251 [mcmc] New sample, #504:
Omega_m:0.3091437, b1:0.4930935
2023-07-02 10:34:12,251 [model] Posterior to be computed for parameters {'Omega_m': 0.3224465495168355, 'b1': 0.472988497226236}
2023-07-02 10:34:12,251 [prior] Evaluating prior at array([0.32244655, 0.4729885 ])
2023-07-02 10:34:12,251 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:12,251 [model] Got input parameters: {'Omega_m': 0.3224465495168355, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.472988497226236, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:12,251 [classy] Got parameters {'Omega_m': 0.3224465495168355, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:12,251 [classy] Re-using computed results
2023-07-02 10:34:12,251 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.07806539681823}
2023-07-02 10:34:12,251 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:12,251 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.472988497226236, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:12,251 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:12,271 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.12646
2023-07-02 10:34:12,271 [model] Computed derived parameters: {}
2023-07-02 10:34:12,271 [mcmc] New sample, #505:
Omega_m:0.3224465, b1:0.4724229
2023-07-02 10:34:12,271 [model] Posterior to be computed for parameters {'Omega_m': 0.33916422142999336, 'b1': 0.4470119185376681}
2023-07-02 10:34:12,271 [prior] Evaluating prior at array([0.33916422, 0.44701192])
2023-07-02 10:34:12,271 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:12,271 [model] Got input parameters: {'Omega_m': 0.33916422142999336, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4470119185376681, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:12,272 [classy] Got parameters {'Omega_m': 0.33916422142999336, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:12,272 [classy] Computing new state
2023-07-02 10:34:12,272 [classy] Setting parameters: {'Omega_m': 0.33916422142999336, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:12,316 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.16622334514827}
2023-07-02 10:34:12,316 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:12,318 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0411153
2023-07-02 10:34:12,318 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4470119185376681, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:12,318 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:12,337 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.242553
2023-07-02 10:34:12,337 [model] Computed derived parameters: {}
2023-07-02 10:34:12,338 [model] Posterior to be computed for parameters {'Omega_m': 0.3224465495168355, 'b1': 0.42161342621185954}
2023-07-02 10:34:12,338 [prior] Evaluating prior at array([0.32244655, 0.42161343])
2023-07-02 10:34:12,338 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:12,338 [model] Got input parameters: {'Omega_m': 0.3224465495168355, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42161342621185954, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:12,338 [classy] Got parameters {'Omega_m': 0.3224465495168355, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:12,338 [classy] Re-using computed results
2023-07-02 10:34:12,338 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.07806539681823}
2023-07-02 10:34:12,338 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:12,338 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42161342621185954, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:12,338 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:12,359 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.16691
2023-07-02 10:34:12,359 [model] Computed derived parameters: {}
2023-07-02 10:34:12,359 [model] Posterior to be computed for parameters {'Omega_m': 0.3268219573413302, 'b1': 0.4661898157927221}
2023-07-02 10:34:12,360 [prior] Evaluating prior at array([0.32682196, 0.46618982])
2023-07-02 10:34:12,360 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:12,360 [model] Got input parameters: {'Omega_m': 0.3268219573413302, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4661898157927221, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:12,360 [classy] Got parameters {'Omega_m': 0.3268219573413302, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:12,360 [classy] Computing new state
2023-07-02 10:34:12,360 [classy] Setting parameters: {'Omega_m': 0.3268219573413302, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:12,404 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.56919739640236}
2023-07-02 10:34:12,404 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:12,406 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0123724
2023-07-02 10:34:12,406 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4661898157927221, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:12,406 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:12,426 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.76775
2023-07-02 10:34:12,426 [model] Computed derived parameters: {}
2023-07-02 10:34:12,426 [model] Posterior to be computed for parameters {'Omega_m': 0.3224465495168355, 'b1': 0.4080867823067048}
2023-07-02 10:34:12,426 [prior] Evaluating prior at array([0.32244655, 0.40808678])
2023-07-02 10:34:12,426 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:12,426 [model] Got input parameters: {'Omega_m': 0.3224465495168355, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4080867823067048, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:12,426 [classy] Got parameters {'Omega_m': 0.3224465495168355, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:12,426 [classy] Re-using computed results
2023-07-02 10:34:12,426 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.07806539681823}
2023-07-02 10:34:12,426 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:12,426 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4080867823067048, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:12,426 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:12,447 [fs_likelihood.fslikelihood] Computed log-likelihood = -12.8965
2023-07-02 10:34:12,447 [model] Computed derived parameters: {}
2023-07-02 10:34:12,447 [model] Posterior to be computed for parameters {'Omega_m': 0.30806837203887805, 'b1': 0.49532987709028226}
2023-07-02 10:34:12,447 [prior] Evaluating prior at array([0.30806837, 0.49532988])
2023-07-02 10:34:12,447 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:12,447 [model] Got input parameters: {'Omega_m': 0.30806837203887805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49532987709028226, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:12,447 [classy] Got parameters {'Omega_m': 0.30806837203887805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:12,447 [classy] Computing new state
2023-07-02 10:34:12,447 [classy] Setting parameters: {'Omega_m': 0.30806837203887805, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:12,491 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.79481114901554}
2023-07-02 10:34:12,491 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:12,493 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00141136
2023-07-02 10:34:12,493 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49532987709028226, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:12,493 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:12,513 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.81726
2023-07-02 10:34:12,513 [model] Computed derived parameters: {}
2023-07-02 10:34:12,513 [mcmc] New sample, #506:
Omega_m:0.3224465, b1:0.4729885
2023-07-02 10:34:12,513 [model] Posterior to be computed for parameters {'Omega_m': 0.30806837203887805, 'b1': 0.5202226877504821}
2023-07-02 10:34:12,513 [prior] Evaluating prior at array([0.30806837, 0.52022269])
2023-07-02 10:34:12,513 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:12,513 [model] Got input parameters: {'Omega_m': 0.30806837203887805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5202226877504821, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:12,513 [classy] Got parameters {'Omega_m': 0.30806837203887805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:12,514 [classy] Re-using computed results
2023-07-02 10:34:12,514 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.79481114901554}
2023-07-02 10:34:12,514 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:12,514 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5202226877504821, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:12,514 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:12,533 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.48953
2023-07-02 10:34:12,533 [model] Computed derived parameters: {}
2023-07-02 10:34:12,533 [mcmc] New sample, #507:
Omega_m:0.3080684, b1:0.4953299
2023-07-02 10:34:12,533 [model] Posterior to be computed for parameters {'Omega_m': 0.28684664934873944, 'b1': 0.553197838371393}
2023-07-02 10:34:12,533 [prior] Evaluating prior at array([0.28684665, 0.55319784])
2023-07-02 10:34:12,533 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:12,533 [model] Got input parameters: {'Omega_m': 0.28684664934873944, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.553197838371393, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:12,533 [classy] Got parameters {'Omega_m': 0.28684664934873944, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:12,533 [classy] Computing new state
2023-07-02 10:34:12,533 [classy] Setting parameters: {'Omega_m': 0.28684664934873944, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:12,579 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.46234393171096}
2023-07-02 10:34:12,579 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:12,581 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0432303
2023-07-02 10:34:12,581 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.553197838371393, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:12,581 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:12,601 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.1693
2023-07-02 10:34:12,601 [model] Computed derived parameters: {}
2023-07-02 10:34:12,601 [model] Posterior to be computed for parameters {'Omega_m': 0.30806837203887805, 'b1': 0.38426491990651035}
2023-07-02 10:34:12,601 [prior] Evaluating prior at array([0.30806837, 0.38426492])
2023-07-02 10:34:12,602 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:12,602 [model] Got input parameters: {'Omega_m': 0.30806837203887805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.38426491990651035, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:12,602 [classy] Got parameters {'Omega_m': 0.30806837203887805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:12,602 [classy] Re-using computed results
2023-07-02 10:34:12,602 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.79481114901554}
2023-07-02 10:34:12,602 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:12,602 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.38426491990651035, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:12,602 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:12,621 [fs_likelihood.fslikelihood] Computed log-likelihood = -36.2506
2023-07-02 10:34:12,621 [model] Computed derived parameters: {}
2023-07-02 10:34:12,621 [model] Posterior to be computed for parameters {'Omega_m': 0.2884344834863504, 'b1': 0.5507305989953419}
2023-07-02 10:34:12,621 [prior] Evaluating prior at array([0.28843448, 0.5507306 ])
2023-07-02 10:34:12,621 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:12,621 [model] Got input parameters: {'Omega_m': 0.2884344834863504, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5507305989953419, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:12,621 [classy] Got parameters {'Omega_m': 0.2884344834863504, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:12,622 [classy] Computing new state
2023-07-02 10:34:12,622 [classy] Setting parameters: {'Omega_m': 0.2884344834863504, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:12,666 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.25691592411786}
2023-07-02 10:34:12,666 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:12,668 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0379093
2023-07-02 10:34:12,668 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5507305989953419, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:12,668 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:12,688 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.58953
2023-07-02 10:34:12,688 [model] Computed derived parameters: {}
2023-07-02 10:34:12,688 [model] Posterior to be computed for parameters {'Omega_m': 0.30806837203887805, 'b1': 0.5457473617190787}
2023-07-02 10:34:12,688 [prior] Evaluating prior at array([0.30806837, 0.54574736])
2023-07-02 10:34:12,688 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:12,688 [model] Got input parameters: {'Omega_m': 0.30806837203887805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5457473617190787, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:12,688 [classy] Got parameters {'Omega_m': 0.30806837203887805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:12,688 [classy] Re-using computed results
2023-07-02 10:34:12,688 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.79481114901554}
2023-07-02 10:34:12,688 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:12,688 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5457473617190787, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:12,688 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:12,708 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.345743
2023-07-02 10:34:12,708 [model] Computed derived parameters: {}
2023-07-02 10:34:12,708 [model] Posterior to be computed for parameters {'Omega_m': 0.2959569323215222, 'b1': 0.5390419209836764}
2023-07-02 10:34:12,709 [prior] Evaluating prior at array([0.29595693, 0.53904192])
2023-07-02 10:34:12,709 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:12,709 [model] Got input parameters: {'Omega_m': 0.2959569323215222, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5390419209836764, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:12,709 [classy] Got parameters {'Omega_m': 0.2959569323215222, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:12,709 [classy] Computing new state
2023-07-02 10:34:12,709 [classy] Setting parameters: {'Omega_m': 0.2959569323215222, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:12,753 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.29677926777404}
2023-07-02 10:34:12,753 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:12,755 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0176667
2023-07-02 10:34:12,755 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5390419209836764, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:12,755 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:12,776 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.626362
2023-07-02 10:34:12,776 [model] Computed derived parameters: {}
2023-07-02 10:34:12,776 [mcmc] New sample, #508:
Omega_m:0.3080684, b1:0.5202227
2023-07-02 10:34:12,776 [model] Posterior to be computed for parameters {'Omega_m': 0.2959569323215222, 'b1': 0.5436420521006314}
2023-07-02 10:34:12,777 [prior] Evaluating prior at array([0.29595693, 0.54364205])
2023-07-02 10:34:12,777 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:12,777 [model] Got input parameters: {'Omega_m': 0.2959569323215222, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5436420521006314, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:12,777 [classy] Got parameters {'Omega_m': 0.2959569323215222, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:12,777 [classy] Re-using computed results
2023-07-02 10:34:12,777 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.29677926777404}
2023-07-02 10:34:12,777 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:12,777 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5436420521006314, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:12,777 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:12,797 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.468652
2023-07-02 10:34:12,797 [model] Computed derived parameters: {}
2023-07-02 10:34:12,797 [mcmc] New sample, #509:
Omega_m:0.2959569, b1:0.5390419
2023-07-02 10:34:12,797 [model] Posterior to be computed for parameters {'Omega_m': 0.29829523346935716, 'b1': 0.5400087074531332}
2023-07-02 10:34:12,797 [prior] Evaluating prior at array([0.29829523, 0.54000871])
2023-07-02 10:34:12,797 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:12,797 [model] Got input parameters: {'Omega_m': 0.29829523346935716, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5400087074531332, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:12,797 [classy] Got parameters {'Omega_m': 0.29829523346935716, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:12,797 [classy] Computing new state
2023-07-02 10:34:12,797 [classy] Setting parameters: {'Omega_m': 0.29829523346935716, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:12,844 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.00264105327338}
2023-07-02 10:34:12,844 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:12,847 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0129972
2023-07-02 10:34:12,847 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5400087074531332, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:12,847 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:12,870 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.970597
2023-07-02 10:34:12,870 [model] Computed derived parameters: {}
2023-07-02 10:34:12,870 [mcmc] New sample, #510:
Omega_m:0.2959569, b1:0.5436421
2023-07-02 10:34:12,871 [model] Posterior to be computed for parameters {'Omega_m': 0.29829523346935716, 'b1': 0.5359778031254079}
2023-07-02 10:34:12,871 [prior] Evaluating prior at array([0.29829523, 0.5359778 ])
2023-07-02 10:34:12,871 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:12,871 [model] Got input parameters: {'Omega_m': 0.29829523346935716, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5359778031254079, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:12,871 [classy] Got parameters {'Omega_m': 0.29829523346935716, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:12,871 [classy] Re-using computed results
2023-07-02 10:34:12,871 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.00264105327338}
2023-07-02 10:34:12,871 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:12,871 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5359778031254079, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:12,871 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:12,890 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.12861
2023-07-02 10:34:12,890 [model] Computed derived parameters: {}
2023-07-02 10:34:12,890 [mcmc] New sample, #511:
Omega_m:0.2982952, b1:0.5400087
2023-07-02 10:34:12,891 [model] Posterior to be computed for parameters {'Omega_m': 0.31903597196410544, 'b1': 0.5037500247381678}
2023-07-02 10:34:12,891 [prior] Evaluating prior at array([0.31903597, 0.50375002])
2023-07-02 10:34:12,891 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:12,891 [model] Got input parameters: {'Omega_m': 0.31903597196410544, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5037500247381678, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:12,891 [classy] Got parameters {'Omega_m': 0.31903597196410544, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:12,891 [classy] Computing new state
2023-07-02 10:34:12,891 [classy] Setting parameters: {'Omega_m': 0.31903597196410544, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:12,935 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.47901496467136}
2023-07-02 10:34:12,935 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:12,936 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0027923
2023-07-02 10:34:12,936 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5037500247381678, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:12,936 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:12,957 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.53017
2023-07-02 10:34:12,957 [model] Computed derived parameters: {}
2023-07-02 10:34:12,957 [mcmc] New sample, #512:
Omega_m:0.2982952, b1:0.5359778
2023-07-02 10:34:12,957 [model] Posterior to be computed for parameters {'Omega_m': 0.31903597196410544, 'b1': 0.5305375474146355}
2023-07-02 10:34:12,957 [prior] Evaluating prior at array([0.31903597, 0.53053755])
2023-07-02 10:34:12,957 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:12,957 [model] Got input parameters: {'Omega_m': 0.31903597196410544, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5305375474146355, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:12,957 [classy] Got parameters {'Omega_m': 0.31903597196410544, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:12,957 [classy] Re-using computed results
2023-07-02 10:34:12,958 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.47901496467136}
2023-07-02 10:34:12,958 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:12,958 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5305375474146355, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:12,958 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:12,978 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.10939
2023-07-02 10:34:12,978 [model] Computed derived parameters: {}
2023-07-02 10:34:12,978 [model] Posterior to be computed for parameters {'Omega_m': 0.32907784545320684, 'b1': 0.4881465652238691}
2023-07-02 10:34:12,978 [prior] Evaluating prior at array([0.32907785, 0.48814657])
2023-07-02 10:34:12,978 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:12,978 [model] Got input parameters: {'Omega_m': 0.32907784545320684, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4881465652238691, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:12,978 [classy] Got parameters {'Omega_m': 0.32907784545320684, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:12,978 [classy] Computing new state
2023-07-02 10:34:12,978 [classy] Setting parameters: {'Omega_m': 0.32907784545320684, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:13,023 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.30921156342626}
2023-07-02 10:34:13,023 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:13,024 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0164153
2023-07-02 10:34:13,025 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4881465652238691, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,025 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:13,045 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.41295
2023-07-02 10:34:13,045 [model] Computed derived parameters: {}
2023-07-02 10:34:13,045 [model] Posterior to be computed for parameters {'Omega_m': 0.31903597196410544, 'b1': 0.5063582201700612}
2023-07-02 10:34:13,045 [prior] Evaluating prior at array([0.31903597, 0.50635822])
2023-07-02 10:34:13,045 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:13,045 [model] Got input parameters: {'Omega_m': 0.31903597196410544, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5063582201700612, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,045 [classy] Got parameters {'Omega_m': 0.31903597196410544, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:13,045 [classy] Re-using computed results
2023-07-02 10:34:13,045 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.47901496467136}
2023-07-02 10:34:13,045 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:13,045 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5063582201700612, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,045 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:13,065 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.35721
2023-07-02 10:34:13,065 [model] Computed derived parameters: {}
2023-07-02 10:34:13,065 [mcmc] New sample, #513:
Omega_m:0.319036, b1:0.50375
2023-07-02 10:34:13,065 [model] Posterior to be computed for parameters {'Omega_m': 0.2967908058250944, 'b1': 0.540923637630819}
2023-07-02 10:34:13,065 [prior] Evaluating prior at array([0.29679081, 0.54092364])
2023-07-02 10:34:13,065 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:13,065 [model] Got input parameters: {'Omega_m': 0.2967908058250944, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.540923637630819, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,066 [classy] Got parameters {'Omega_m': 0.2967908058250944, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:13,066 [classy] Computing new state
2023-07-02 10:34:13,066 [classy] Setting parameters: {'Omega_m': 0.2967908058250944, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:13,111 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.19165463580433}
2023-07-02 10:34:13,111 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:13,113 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0159151
2023-07-02 10:34:13,113 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.540923637630819, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,113 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:13,135 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.719399
2023-07-02 10:34:13,135 [model] Computed derived parameters: {}
2023-07-02 10:34:13,135 [model] Posterior to be computed for parameters {'Omega_m': 0.31903597196410544, 'b1': 0.5274775741735493}
2023-07-02 10:34:13,136 [prior] Evaluating prior at array([0.31903597, 0.52747757])
2023-07-02 10:34:13,136 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:13,136 [model] Got input parameters: {'Omega_m': 0.31903597196410544, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5274775741735493, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,136 [classy] Got parameters {'Omega_m': 0.31903597196410544, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:13,136 [classy] Re-using computed results
2023-07-02 10:34:13,136 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.47901496467136}
2023-07-02 10:34:13,136 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:13,136 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5274775741735493, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,136 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:13,156 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.480471
2023-07-02 10:34:13,156 [model] Computed derived parameters: {}
2023-07-02 10:34:13,156 [model] Posterior to be computed for parameters {'Omega_m': 0.3045926526944758, 'b1': 0.5288008199220247}
2023-07-02 10:34:13,156 [prior] Evaluating prior at array([0.30459265, 0.52880082])
2023-07-02 10:34:13,157 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:13,157 [model] Got input parameters: {'Omega_m': 0.3045926526944758, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5288008199220247, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,157 [classy] Got parameters {'Omega_m': 0.3045926526944758, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:13,157 [classy] Computing new state
2023-07-02 10:34:13,157 [classy] Setting parameters: {'Omega_m': 0.3045926526944758, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:13,201 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.22044885211443}
2023-07-02 10:34:13,201 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:13,203 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0040974
2023-07-02 10:34:13,203 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5288008199220247, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,203 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:13,222 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.02047
2023-07-02 10:34:13,222 [model] Computed derived parameters: {}
2023-07-02 10:34:13,222 [mcmc] New sample, #514:
Omega_m:0.319036, b1:0.5063582
2023-07-02 10:34:13,223 [model] Posterior to be computed for parameters {'Omega_m': 0.3045926526944758, 'b1': 0.5750502179088995}
2023-07-02 10:34:13,223 [prior] Evaluating prior at array([0.30459265, 0.57505022])
2023-07-02 10:34:13,223 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:13,223 [model] Got input parameters: {'Omega_m': 0.3045926526944758, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5750502179088995, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,223 [classy] Got parameters {'Omega_m': 0.3045926526944758, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:13,223 [classy] Re-using computed results
2023-07-02 10:34:13,223 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.22044885211443}
2023-07-02 10:34:13,223 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:13,223 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5750502179088995, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,223 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:13,243 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.51356
2023-07-02 10:34:13,243 [model] Computed derived parameters: {}
2023-07-02 10:34:13,243 [model] Posterior to be computed for parameters {'Omega_m': 0.3329935482126437, 'b1': 0.4846703871030373}
2023-07-02 10:34:13,243 [prior] Evaluating prior at array([0.33299355, 0.48467039])
2023-07-02 10:34:13,243 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:13,243 [model] Got input parameters: {'Omega_m': 0.3329935482126437, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4846703871030373, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,243 [classy] Got parameters {'Omega_m': 0.3329935482126437, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:13,243 [classy] Computing new state
2023-07-02 10:34:13,243 [classy] Setting parameters: {'Omega_m': 0.3329935482126437, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:13,287 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.86177602254241}
2023-07-02 10:34:13,287 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:13,288 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0247368
2023-07-02 10:34:13,289 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4846703871030373, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,289 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:13,308 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.475105
2023-07-02 10:34:13,308 [model] Computed derived parameters: {}
2023-07-02 10:34:13,308 [mcmc] New sample, #515:
Omega_m:0.3045927, b1:0.5288008
2023-07-02 10:34:13,308 [model] Posterior to be computed for parameters {'Omega_m': 0.3329935482126437, 'b1': 0.536250374737656}
2023-07-02 10:34:13,308 [prior] Evaluating prior at array([0.33299355, 0.53625037])
2023-07-02 10:34:13,309 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:13,309 [model] Got input parameters: {'Omega_m': 0.3329935482126437, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.536250374737656, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,309 [classy] Got parameters {'Omega_m': 0.3329935482126437, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:13,309 [classy] Re-using computed results
2023-07-02 10:34:13,309 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.86177602254241}
2023-07-02 10:34:13,309 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:13,309 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.536250374737656, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,309 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:13,328 [fs_likelihood.fslikelihood] Computed log-likelihood = -12.5
2023-07-02 10:34:13,328 [model] Computed derived parameters: {}
2023-07-02 10:34:13,328 [model] Posterior to be computed for parameters {'Omega_m': 0.32248407342681396, 'b1': 0.501000423974664}
2023-07-02 10:34:13,328 [prior] Evaluating prior at array([0.32248407, 0.50100042])
2023-07-02 10:34:13,328 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:13,328 [model] Got input parameters: {'Omega_m': 0.32248407342681396, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.501000423974664, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,328 [classy] Got parameters {'Omega_m': 0.32248407342681396, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:13,329 [classy] Computing new state
2023-07-02 10:34:13,329 [classy] Setting parameters: {'Omega_m': 0.32248407342681396, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:13,372 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.07367588992582}
2023-07-02 10:34:13,373 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:13,374 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0061848
2023-07-02 10:34:13,374 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.501000423974664, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,374 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:13,394 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.07894
2023-07-02 10:34:13,394 [model] Computed derived parameters: {}
2023-07-02 10:34:13,394 [mcmc] New sample, #516:
Omega_m:0.3329935, b1:0.4846704
2023-07-02 10:34:13,394 [model] Posterior to be computed for parameters {'Omega_m': 0.32248407342681396, 'b1': 0.48824752371618907}
2023-07-02 10:34:13,394 [prior] Evaluating prior at array([0.32248407, 0.48824752])
2023-07-02 10:34:13,394 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:13,394 [model] Got input parameters: {'Omega_m': 0.32248407342681396, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48824752371618907, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,394 [classy] Got parameters {'Omega_m': 0.32248407342681396, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:13,394 [classy] Re-using computed results
2023-07-02 10:34:13,394 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.07367588992582}
2023-07-02 10:34:13,394 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:13,394 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48824752371618907, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,394 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:13,414 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.63086
2023-07-02 10:34:13,414 [model] Computed derived parameters: {}
2023-07-02 10:34:13,414 [mcmc] New sample, #517:
Omega_m:0.3224841, b1:0.5010004
2023-07-02 10:34:13,414 [model] Posterior to be computed for parameters {'Omega_m': 0.32397525072247496, 'b1': 0.48593047355749697}
2023-07-02 10:34:13,414 [prior] Evaluating prior at array([0.32397525, 0.48593047])
2023-07-02 10:34:13,415 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:13,415 [model] Got input parameters: {'Omega_m': 0.32397525072247496, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48593047355749697, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,415 [classy] Got parameters {'Omega_m': 0.32397525072247496, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:13,415 [classy] Computing new state
2023-07-02 10:34:13,415 [classy] Setting parameters: {'Omega_m': 0.32397525072247496, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:13,458 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.89957713272946}
2023-07-02 10:34:13,458 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:13,460 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00807345
2023-07-02 10:34:13,460 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48593047355749697, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,460 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:13,479 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.49928
2023-07-02 10:34:13,480 [model] Computed derived parameters: {}
2023-07-02 10:34:13,480 [mcmc] New sample, #518:
Omega_m:0.3224841, b1:0.4882475
2023-07-02 10:34:13,480 [model] Posterior to be computed for parameters {'Omega_m': 0.32397525072247496, 'b1': 0.4865474541046453}
2023-07-02 10:34:13,480 [prior] Evaluating prior at array([0.32397525, 0.48654745])
2023-07-02 10:34:13,480 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:13,480 [model] Got input parameters: {'Omega_m': 0.32397525072247496, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4865474541046453, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,480 [classy] Got parameters {'Omega_m': 0.32397525072247496, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:13,480 [classy] Re-using computed results
2023-07-02 10:34:13,480 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.89957713272946}
2023-07-02 10:34:13,480 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:13,480 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4865474541046453, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,480 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:13,499 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.49196
2023-07-02 10:34:13,499 [model] Computed derived parameters: {}
2023-07-02 10:34:13,499 [mcmc] New sample, #519:
Omega_m:0.3239753, b1:0.4859305
2023-07-02 10:34:13,499 [model] Posterior to be computed for parameters {'Omega_m': 0.3104557904403714, 'b1': 0.5075545252847312}
2023-07-02 10:34:13,499 [prior] Evaluating prior at array([0.31045579, 0.50755453])
2023-07-02 10:34:13,500 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:13,500 [model] Got input parameters: {'Omega_m': 0.3104557904403714, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5075545252847312, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,500 [classy] Got parameters {'Omega_m': 0.3104557904403714, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:13,500 [classy] Computing new state
2023-07-02 10:34:13,500 [classy] Setting parameters: {'Omega_m': 0.3104557904403714, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:13,543 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.50488715667927}
2023-07-02 10:34:13,543 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:13,545 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000455923
2023-07-02 10:34:13,545 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5075545252847312, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,545 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:13,566 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.79516
2023-07-02 10:34:13,566 [model] Computed derived parameters: {}
2023-07-02 10:34:13,566 [mcmc] New sample, #520:
Omega_m:0.3239753, b1:0.4865475
2023-07-02 10:34:13,566 [model] Posterior to be computed for parameters {'Omega_m': 0.3104557904403714, 'b1': 0.47103066484752953}
2023-07-02 10:34:13,566 [prior] Evaluating prior at array([0.31045579, 0.47103066])
2023-07-02 10:34:13,566 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:13,566 [model] Got input parameters: {'Omega_m': 0.3104557904403714, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47103066484752953, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,566 [classy] Got parameters {'Omega_m': 0.3104557904403714, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:13,566 [classy] Re-using computed results
2023-07-02 10:34:13,566 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.50488715667927}
2023-07-02 10:34:13,566 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:13,566 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47103066484752953, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,566 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:13,585 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.849818
2023-07-02 10:34:13,586 [model] Computed derived parameters: {}
2023-07-02 10:34:13,586 [model] Posterior to be computed for parameters {'Omega_m': 0.26781637744500997, 'b1': 0.5738093287443314}
2023-07-02 10:34:13,586 [prior] Evaluating prior at array([0.26781638, 0.57380933])
2023-07-02 10:34:13,586 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:13,586 [model] Got input parameters: {'Omega_m': 0.26781637744500997, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5738093287443314, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,586 [classy] Got parameters {'Omega_m': 0.26781637744500997, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:13,586 [classy] Computing new state
2023-07-02 10:34:13,586 [classy] Setting parameters: {'Omega_m': 0.26781637744500997, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:13,630 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.00370750356993}
2023-07-02 10:34:13,630 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:13,632 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.137629
2023-07-02 10:34:13,632 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5738093287443314, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,632 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:13,651 [fs_likelihood.fslikelihood] Computed log-likelihood = -12.8092
2023-07-02 10:34:13,651 [model] Computed derived parameters: {}
2023-07-02 10:34:13,651 [model] Posterior to be computed for parameters {'Omega_m': 0.3104557904403714, 'b1': 0.5009915285883733}
2023-07-02 10:34:13,651 [prior] Evaluating prior at array([0.31045579, 0.50099153])
2023-07-02 10:34:13,652 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:13,652 [model] Got input parameters: {'Omega_m': 0.3104557904403714, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5009915285883733, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,652 [classy] Got parameters {'Omega_m': 0.3104557904403714, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:13,652 [classy] Re-using computed results
2023-07-02 10:34:13,652 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.50488715667927}
2023-07-02 10:34:13,652 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:13,652 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5009915285883733, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,652 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:13,672 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.64389
2023-07-02 10:34:13,672 [model] Computed derived parameters: {}
2023-07-02 10:34:13,672 [mcmc] New sample, #521:
Omega_m:0.3104558, b1:0.5075545
2023-07-02 10:34:13,672 [model] Posterior to be computed for parameters {'Omega_m': 0.35345616051831985, 'b1': 0.43417585576205}
2023-07-02 10:34:13,672 [prior] Evaluating prior at array([0.35345616, 0.43417586])
2023-07-02 10:34:13,672 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:13,672 [model] Got input parameters: {'Omega_m': 0.35345616051831985, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.43417585576205, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,672 [classy] Got parameters {'Omega_m': 0.35345616051831985, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:13,672 [classy] Computing new state
2023-07-02 10:34:13,672 [classy] Setting parameters: {'Omega_m': 0.35345616051831985, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:13,716 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.59851703486868}
2023-07-02 10:34:13,716 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:13,717 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0935194
2023-07-02 10:34:13,718 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.43417585576205, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,718 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:13,737 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.1004
2023-07-02 10:34:13,737 [model] Computed derived parameters: {}
2023-07-02 10:34:13,737 [model] Posterior to be computed for parameters {'Omega_m': 0.3104557904403714, 'b1': 0.5093538630087164}
2023-07-02 10:34:13,737 [prior] Evaluating prior at array([0.31045579, 0.50935386])
2023-07-02 10:34:13,737 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:13,737 [model] Got input parameters: {'Omega_m': 0.3104557904403714, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5093538630087164, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,737 [classy] Got parameters {'Omega_m': 0.3104557904403714, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:13,737 [classy] Re-using computed results
2023-07-02 10:34:13,737 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.50488715667927}
2023-07-02 10:34:13,737 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:13,737 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5093538630087164, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,737 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:13,756 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.79656
2023-07-02 10:34:13,756 [model] Computed derived parameters: {}
2023-07-02 10:34:13,756 [mcmc] New sample, #522:
Omega_m:0.3104558, b1:0.5009915
2023-07-02 10:34:13,757 [model] Posterior to be computed for parameters {'Omega_m': 0.2955766192553714, 'b1': 0.5324737066756817}
2023-07-02 10:34:13,757 [prior] Evaluating prior at array([0.29557662, 0.53247371])
2023-07-02 10:34:13,757 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:13,757 [model] Got input parameters: {'Omega_m': 0.2955766192553714, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5324737066756817, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,757 [classy] Got parameters {'Omega_m': 0.2955766192553714, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:13,757 [classy] Computing new state
2023-07-02 10:34:13,757 [classy] Setting parameters: {'Omega_m': 0.2955766192553714, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:13,801 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.34481007152823}
2023-07-02 10:34:13,801 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:13,802 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0184976
2023-07-02 10:34:13,802 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5324737066756817, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,803 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:13,822 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.551695
2023-07-02 10:34:13,822 [model] Computed derived parameters: {}
2023-07-02 10:34:13,822 [mcmc] New sample, #523:
Omega_m:0.3104558, b1:0.5093539
2023-07-02 10:34:13,822 [model] Posterior to be computed for parameters {'Omega_m': 0.2955766192553714, 'b1': 0.5366569261785293}
2023-07-02 10:34:13,823 [prior] Evaluating prior at array([0.29557662, 0.53665693])
2023-07-02 10:34:13,823 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:13,823 [model] Got input parameters: {'Omega_m': 0.2955766192553714, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5366569261785293, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,823 [classy] Got parameters {'Omega_m': 0.2955766192553714, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:13,823 [classy] Re-using computed results
2023-07-02 10:34:13,823 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.34481007152823}
2023-07-02 10:34:13,823 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:13,823 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5366569261785293, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,823 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:13,842 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.574729
2023-07-02 10:34:13,842 [model] Computed derived parameters: {}
2023-07-02 10:34:13,842 [mcmc] New sample, #524:
Omega_m:0.2955766, b1:0.5324737
2023-07-02 10:34:13,842 [model] Posterior to be computed for parameters {'Omega_m': 0.2969264084429165, 'b1': 0.5345595704447057}
2023-07-02 10:34:13,842 [prior] Evaluating prior at array([0.29692641, 0.53455957])
2023-07-02 10:34:13,842 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:13,842 [model] Got input parameters: {'Omega_m': 0.2969264084429165, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5345595704447057, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,842 [classy] Got parameters {'Omega_m': 0.2969264084429165, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:13,843 [classy] Computing new state
2023-07-02 10:34:13,843 [classy] Setting parameters: {'Omega_m': 0.2969264084429165, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:13,886 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.174583717974}
2023-07-02 10:34:13,886 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:13,888 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0156393
2023-07-02 10:34:13,888 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5345595704447057, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,888 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:13,907 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.896116
2023-07-02 10:34:13,907 [model] Computed derived parameters: {}
2023-07-02 10:34:13,908 [mcmc] New sample, #525:
Omega_m:0.2955766, b1:0.5366569
2023-07-02 10:34:13,908 [model] Posterior to be computed for parameters {'Omega_m': 0.2969264084429165, 'b1': 0.548243766317192}
2023-07-02 10:34:13,908 [prior] Evaluating prior at array([0.29692641, 0.54824377])
2023-07-02 10:34:13,908 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:13,908 [model] Got input parameters: {'Omega_m': 0.2969264084429165, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.548243766317192, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,908 [classy] Got parameters {'Omega_m': 0.2969264084429165, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:13,908 [classy] Re-using computed results
2023-07-02 10:34:13,908 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.174583717974}
2023-07-02 10:34:13,908 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:13,908 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.548243766317192, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,908 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:13,928 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.290385
2023-07-02 10:34:13,928 [model] Computed derived parameters: {}
2023-07-02 10:34:13,928 [model] Posterior to be computed for parameters {'Omega_m': 0.2809456529794828, 'b1': 0.5593910992577528}
2023-07-02 10:34:13,928 [prior] Evaluating prior at array([0.28094565, 0.5593911 ])
2023-07-02 10:34:13,928 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:13,928 [model] Got input parameters: {'Omega_m': 0.2809456529794828, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5593910992577528, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,928 [classy] Got parameters {'Omega_m': 0.2809456529794828, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:13,928 [classy] Computing new state
2023-07-02 10:34:13,928 [classy] Setting parameters: {'Omega_m': 0.2809456529794828, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:13,972 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.2345674521532}
2023-07-02 10:34:13,972 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:13,974 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0663397
2023-07-02 10:34:13,974 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5593910992577528, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,974 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:13,993 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.70358
2023-07-02 10:34:13,993 [model] Computed derived parameters: {}
2023-07-02 10:34:13,994 [model] Posterior to be computed for parameters {'Omega_m': 0.2969264084429165, 'b1': 0.5149500474456896}
2023-07-02 10:34:13,994 [prior] Evaluating prior at array([0.29692641, 0.51495005])
2023-07-02 10:34:13,994 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:13,994 [model] Got input parameters: {'Omega_m': 0.2969264084429165, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5149500474456896, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,994 [classy] Got parameters {'Omega_m': 0.2969264084429165, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:13,994 [classy] Re-using computed results
2023-07-02 10:34:13,994 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.174583717974}
2023-07-02 10:34:13,994 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:13,994 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5149500474456896, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:13,994 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:14,013 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.0392728
2023-07-02 10:34:14,013 [model] Computed derived parameters: {}
2023-07-02 10:34:14,014 [model] Posterior to be computed for parameters {'Omega_m': 0.3208895945494831, 'b1': 0.49732462572515457}
2023-07-02 10:34:14,014 [prior] Evaluating prior at array([0.32088959, 0.49732463])
2023-07-02 10:34:14,014 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:14,014 [model] Got input parameters: {'Omega_m': 0.3208895945494831, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49732462572515457, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:14,014 [classy] Got parameters {'Omega_m': 0.3208895945494831, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:14,014 [classy] Computing new state
2023-07-02 10:34:14,014 [classy] Setting parameters: {'Omega_m': 0.3208895945494831, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:14,057 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.26062982880703}
2023-07-02 10:34:14,058 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:14,059 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00444565
2023-07-02 10:34:14,059 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49732462572515457, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:14,059 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:14,079 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.58803
2023-07-02 10:34:14,079 [model] Computed derived parameters: {}
2023-07-02 10:34:14,079 [mcmc] New sample, #526:
Omega_m:0.2969264, b1:0.5345596
2023-07-02 10:34:14,079 [model] Posterior to be computed for parameters {'Omega_m': 0.3208895945494831, 'b1': 0.48072130998151774}
2023-07-02 10:34:14,079 [prior] Evaluating prior at array([0.32088959, 0.48072131])
2023-07-02 10:34:14,080 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:14,080 [model] Got input parameters: {'Omega_m': 0.3208895945494831, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48072130998151774, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:14,080 [classy] Got parameters {'Omega_m': 0.3208895945494831, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:14,080 [classy] Re-using computed results
2023-07-02 10:34:14,080 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.26062982880703}
2023-07-02 10:34:14,080 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:14,080 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48072130998151774, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:14,080 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:14,099 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.53391
2023-07-02 10:34:14,099 [model] Computed derived parameters: {}
2023-07-02 10:34:14,099 [mcmc] New sample, #527:
Omega_m:0.3208896, b1:0.4973246
2023-07-02 10:34:14,099 [model] Posterior to be computed for parameters {'Omega_m': 0.32998748087741514, 'b1': 0.46658465499003154}
2023-07-02 10:34:14,099 [prior] Evaluating prior at array([0.32998748, 0.46658465])
2023-07-02 10:34:14,099 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:14,099 [model] Got input parameters: {'Omega_m': 0.32998748087741514, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46658465499003154, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:14,099 [classy] Got parameters {'Omega_m': 0.32998748087741514, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:14,099 [classy] Computing new state
2023-07-02 10:34:14,099 [classy] Setting parameters: {'Omega_m': 0.32998748087741514, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:14,145 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.20483975668554}
2023-07-02 10:34:14,145 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:14,147 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.018202
2023-07-02 10:34:14,147 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46658465499003154, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:14,147 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:14,167 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.65273
2023-07-02 10:34:14,167 [model] Computed derived parameters: {}
2023-07-02 10:34:14,167 [model] Posterior to be computed for parameters {'Omega_m': 0.3208895945494831, 'b1': 0.4914201906985417}
2023-07-02 10:34:14,167 [prior] Evaluating prior at array([0.32088959, 0.49142019])
2023-07-02 10:34:14,167 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:14,167 [model] Got input parameters: {'Omega_m': 0.3208895945494831, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4914201906985417, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:14,167 [classy] Got parameters {'Omega_m': 0.3208895945494831, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:14,167 [classy] Re-using computed results
2023-07-02 10:34:14,167 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.26062982880703}
2023-07-02 10:34:14,167 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:14,167 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4914201906985417, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:14,167 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:14,187 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.74012
2023-07-02 10:34:14,187 [model] Computed derived parameters: {}
2023-07-02 10:34:14,187 [mcmc] New sample, #528:
Omega_m:0.3208896, b1:0.4807213
2023-07-02 10:34:14,187 [model] Posterior to be computed for parameters {'Omega_m': 0.3394240710259384, 'b1': 0.4626205893459687}
2023-07-02 10:34:14,187 [prior] Evaluating prior at array([0.33942407, 0.46262059])
2023-07-02 10:34:14,187 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:14,187 [model] Got input parameters: {'Omega_m': 0.3394240710259384, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4626205893459687, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:14,187 [classy] Got parameters {'Omega_m': 0.3394240710259384, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:14,187 [classy] Computing new state
2023-07-02 10:34:14,187 [classy] Setting parameters: {'Omega_m': 0.3394240710259384, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:14,231 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.1371836551355}
2023-07-02 10:34:14,231 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:14,233 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0418906
2023-07-02 10:34:14,233 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4626205893459687, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:14,233 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:14,252 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.169645
2023-07-02 10:34:14,252 [model] Computed derived parameters: {}
2023-07-02 10:34:14,252 [model] Posterior to be computed for parameters {'Omega_m': 0.3208895945494831, 'b1': 0.5125021485812256}
2023-07-02 10:34:14,252 [prior] Evaluating prior at array([0.32088959, 0.51250215])
2023-07-02 10:34:14,253 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:14,253 [model] Got input parameters: {'Omega_m': 0.3208895945494831, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5125021485812256, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:14,253 [classy] Got parameters {'Omega_m': 0.3208895945494831, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:14,253 [classy] Re-using computed results
2023-07-02 10:34:14,253 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.26062982880703}
2023-07-02 10:34:14,253 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:14,253 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5125021485812256, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:14,253 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:14,272 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.30125
2023-07-02 10:34:14,272 [model] Computed derived parameters: {}
2023-07-02 10:34:14,273 [mcmc] New sample, #529:
Omega_m:0.3208896, b1:0.4914202
2023-07-02 10:34:14,273 [model] Posterior to be computed for parameters {'Omega_m': 0.3742789649137844, 'b1': 0.42954363691730113}
2023-07-02 10:34:14,273 [prior] Evaluating prior at array([0.37427896, 0.42954364])
2023-07-02 10:34:14,273 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:14,273 [model] Got input parameters: {'Omega_m': 0.3742789649137844, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42954363691730113, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:14,273 [classy] Got parameters {'Omega_m': 0.3742789649137844, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:14,273 [classy] Computing new state
2023-07-02 10:34:14,273 [classy] Setting parameters: {'Omega_m': 0.3742789649137844, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:14,317 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.41593136378663}
2023-07-02 10:34:14,317 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:14,318 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.202697
2023-07-02 10:34:14,319 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42954363691730113, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:14,319 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:14,338 [fs_likelihood.fslikelihood] Computed log-likelihood = -16.0553
2023-07-02 10:34:14,338 [model] Computed derived parameters: {}
2023-07-02 10:34:14,338 [model] Posterior to be computed for parameters {'Omega_m': 0.3208895945494831, 'b1': 0.5276839073412256}
2023-07-02 10:34:14,338 [prior] Evaluating prior at array([0.32088959, 0.52768391])
2023-07-02 10:34:14,338 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:14,338 [model] Got input parameters: {'Omega_m': 0.3208895945494831, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5276839073412256, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:14,339 [classy] Got parameters {'Omega_m': 0.3208895945494831, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:14,339 [classy] Re-using computed results
2023-07-02 10:34:14,339 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.26062982880703}
2023-07-02 10:34:14,339 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:14,339 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5276839073412256, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:14,339 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:14,358 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.32306
2023-07-02 10:34:14,358 [model] Computed derived parameters: {}
2023-07-02 10:34:14,358 [model] Posterior to be computed for parameters {'Omega_m': 0.3180416210714104, 'b1': 0.5169274422190248}
2023-07-02 10:34:14,358 [prior] Evaluating prior at array([0.31804162, 0.51692744])
2023-07-02 10:34:14,358 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:14,358 [model] Got input parameters: {'Omega_m': 0.3180416210714104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5169274422190248, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:14,358 [classy] Got parameters {'Omega_m': 0.3180416210714104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:14,358 [classy] Computing new state
2023-07-02 10:34:14,358 [classy] Setting parameters: {'Omega_m': 0.3180416210714104, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:14,402 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.5966314590419}
2023-07-02 10:34:14,402 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:14,404 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00207043
2023-07-02 10:34:14,404 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5169274422190248, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:14,404 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:14,424 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.53143
2023-07-02 10:34:14,424 [model] Computed derived parameters: {}
2023-07-02 10:34:14,424 [mcmc] New sample, #530:
Omega_m:0.3208896, b1:0.5125021
2023-07-02 10:34:14,424 [model] Posterior to be computed for parameters {'Omega_m': 0.3180416210714104, 'b1': 0.5300526785045339}
2023-07-02 10:34:14,424 [prior] Evaluating prior at array([0.31804162, 0.53005268])
2023-07-02 10:34:14,424 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:14,424 [model] Got input parameters: {'Omega_m': 0.3180416210714104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5300526785045339, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:14,424 [classy] Got parameters {'Omega_m': 0.3180416210714104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:14,424 [classy] Re-using computed results
2023-07-02 10:34:14,424 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.5966314590419}
2023-07-02 10:34:14,424 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:14,424 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5300526785045339, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:14,424 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:14,443 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.593656
2023-07-02 10:34:14,443 [model] Computed derived parameters: {}
2023-07-02 10:34:14,443 [model] Posterior to be computed for parameters {'Omega_m': 0.25254614923597263, 'b1': 0.6186968923383961}
2023-07-02 10:34:14,444 [prior] Evaluating prior at array([0.25254615, 0.61869689])
2023-07-02 10:34:14,444 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:14,444 [model] Got input parameters: {'Omega_m': 0.25254614923597263, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6186968923383961, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:14,444 [classy] Got parameters {'Omega_m': 0.25254614923597263, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:14,444 [classy] Computing new state
2023-07-02 10:34:14,444 [classy] Setting parameters: {'Omega_m': 0.25254614923597263, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:14,487 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 155.1558554817771}
2023-07-02 10:34:14,487 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:14,489 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.258344
2023-07-02 10:34:14,489 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6186968923383961, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:14,489 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:14,508 [fs_likelihood.fslikelihood] Computed log-likelihood = -25.8119
2023-07-02 10:34:14,508 [model] Computed derived parameters: {}
2023-07-02 10:34:14,508 [model] Posterior to be computed for parameters {'Omega_m': 0.3180416210714104, 'b1': 0.5186987346080698}
2023-07-02 10:34:14,508 [prior] Evaluating prior at array([0.31804162, 0.51869873])
2023-07-02 10:34:14,509 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:14,509 [model] Got input parameters: {'Omega_m': 0.3180416210714104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5186987346080698, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:14,509 [classy] Got parameters {'Omega_m': 0.3180416210714104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:14,509 [classy] Re-using computed results
2023-07-02 10:34:14,509 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.5966314590419}
2023-07-02 10:34:14,509 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:14,509 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5186987346080698, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:14,509 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:14,528 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.30354
2023-07-02 10:34:14,528 [model] Computed derived parameters: {}
2023-07-02 10:34:14,529 [model] Posterior to be computed for parameters {'Omega_m': 0.3309140129975722, 'b1': 0.49692581139883557}
2023-07-02 10:34:14,529 [prior] Evaluating prior at array([0.33091401, 0.49692581])
2023-07-02 10:34:14,529 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:14,529 [model] Got input parameters: {'Omega_m': 0.3309140129975722, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49692581139883557, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:14,529 [classy] Got parameters {'Omega_m': 0.3309140129975722, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:14,529 [classy] Computing new state
2023-07-02 10:34:14,529 [classy] Setting parameters: {'Omega_m': 0.3309140129975722, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:14,573 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.09880081260047}
2023-07-02 10:34:14,573 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:14,575 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0201133
2023-07-02 10:34:14,575 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49692581139883557, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:14,575 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:14,594 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.187871
2023-07-02 10:34:14,594 [model] Computed derived parameters: {}
2023-07-02 10:34:14,594 [model] Posterior to be computed for parameters {'Omega_m': 0.3180416210714104, 'b1': 0.48229945233365085}
2023-07-02 10:34:14,594 [prior] Evaluating prior at array([0.31804162, 0.48229945])
2023-07-02 10:34:14,594 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:14,594 [model] Got input parameters: {'Omega_m': 0.3180416210714104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48229945233365085, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:14,594 [classy] Got parameters {'Omega_m': 0.3180416210714104, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:14,594 [classy] Re-using computed results
2023-07-02 10:34:14,595 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.5966314590419}
2023-07-02 10:34:14,595 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:14,595 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48229945233365085, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:14,595 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:14,613 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.46262
2023-07-02 10:34:14,614 [model] Computed derived parameters: {}
2023-07-02 10:34:14,614 [mcmc] New sample, #531:
Omega_m:0.3180416, b1:0.5169274
2023-07-02 10:34:14,614 [model] Posterior to be computed for parameters {'Omega_m': 0.32420741731181835, 'b1': 0.4727187946889358}
2023-07-02 10:34:14,614 [prior] Evaluating prior at array([0.32420742, 0.47271879])
2023-07-02 10:34:14,614 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:14,614 [model] Got input parameters: {'Omega_m': 0.32420741731181835, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4727187946889358, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:14,614 [classy] Got parameters {'Omega_m': 0.32420741731181835, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:14,614 [classy] Computing new state
2023-07-02 10:34:14,614 [classy] Setting parameters: {'Omega_m': 0.32420741731181835, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:14,658 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.8725357216212}
2023-07-02 10:34:14,658 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:14,660 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0083901
2023-07-02 10:34:14,660 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4727187946889358, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:14,660 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:14,680 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.1659
2023-07-02 10:34:14,680 [model] Computed derived parameters: {}
2023-07-02 10:34:14,680 [mcmc] New sample, #532:
Omega_m:0.3180416, b1:0.4822995
2023-07-02 10:34:14,680 [model] Posterior to be computed for parameters {'Omega_m': 0.32420741731181835, 'b1': 0.49706249878377906}
2023-07-02 10:34:14,680 [prior] Evaluating prior at array([0.32420742, 0.4970625 ])
2023-07-02 10:34:14,680 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:14,680 [model] Got input parameters: {'Omega_m': 0.32420741731181835, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49706249878377906, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:14,680 [classy] Got parameters {'Omega_m': 0.32420741731181835, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:14,680 [classy] Re-using computed results
2023-07-02 10:34:14,680 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.8725357216212}
2023-07-02 10:34:14,680 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:14,680 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49706249878377906, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:14,680 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:14,700 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.99052
2023-07-02 10:34:14,700 [model] Computed derived parameters: {}
2023-07-02 10:34:14,700 [mcmc] New sample, #533:
Omega_m:0.3242074, b1:0.4727188
2023-07-02 10:34:14,700 [model] Posterior to be computed for parameters {'Omega_m': 0.4057375928175148, 'b1': 0.37037769299753937}
2023-07-02 10:34:14,700 [prior] Evaluating prior at array([0.40573759, 0.37037769])
2023-07-02 10:34:14,700 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:14,700 [model] Got input parameters: {'Omega_m': 0.4057375928175148, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.37037769299753937, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:14,700 [classy] Got parameters {'Omega_m': 0.4057375928175148, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:14,700 [classy] Computing new state
2023-07-02 10:34:14,700 [classy] Setting parameters: {'Omega_m': 0.4057375928175148, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:14,744 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 137.32538784219003}
2023-07-02 10:34:14,744 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:14,746 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.430951
2023-07-02 10:34:14,746 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.37037769299753937, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:14,746 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:14,765 [fs_likelihood.fslikelihood] Computed log-likelihood = -31.2374
2023-07-02 10:34:14,765 [model] Computed derived parameters: {}
2023-07-02 10:34:14,765 [model] Posterior to be computed for parameters {'Omega_m': 0.32420741731181835, 'b1': 0.5041277243174977}
2023-07-02 10:34:14,765 [prior] Evaluating prior at array([0.32420742, 0.50412772])
2023-07-02 10:34:14,765 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:14,765 [model] Got input parameters: {'Omega_m': 0.32420741731181835, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5041277243174977, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:14,766 [classy] Got parameters {'Omega_m': 0.32420741731181835, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:14,766 [classy] Re-using computed results
2023-07-02 10:34:14,766 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.8725357216212}
2023-07-02 10:34:14,766 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:14,766 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5041277243174977, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:14,766 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:14,786 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.32215
2023-07-02 10:34:14,786 [model] Computed derived parameters: {}
2023-07-02 10:34:14,786 [model] Posterior to be computed for parameters {'Omega_m': 0.3486394467695948, 'b1': 0.459099046753606}
2023-07-02 10:34:14,786 [prior] Evaluating prior at array([0.34863945, 0.45909905])
2023-07-02 10:34:14,786 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:14,786 [model] Got input parameters: {'Omega_m': 0.3486394467695948, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.459099046753606, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:14,786 [classy] Got parameters {'Omega_m': 0.3486394467695948, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:14,786 [classy] Computing new state
2023-07-02 10:34:14,786 [classy] Setting parameters: {'Omega_m': 0.3486394467695948, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:14,830 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.12027525009282}
2023-07-02 10:34:14,830 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:14,832 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0736839
2023-07-02 10:34:14,832 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.459099046753606, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:14,832 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:14,851 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.61308
2023-07-02 10:34:14,851 [model] Computed derived parameters: {}
2023-07-02 10:34:14,852 [model] Posterior to be computed for parameters {'Omega_m': 0.32420741731181835, 'b1': 0.510588638679861}
2023-07-02 10:34:14,852 [prior] Evaluating prior at array([0.32420742, 0.51058864])
2023-07-02 10:34:14,852 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:14,852 [model] Got input parameters: {'Omega_m': 0.32420741731181835, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510588638679861, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:14,852 [classy] Got parameters {'Omega_m': 0.32420741731181835, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:14,852 [classy] Re-using computed results
2023-07-02 10:34:14,852 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.8725357216212}
2023-07-02 10:34:14,852 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:14,852 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510588638679861, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:14,852 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:14,871 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.458527
2023-07-02 10:34:14,871 [model] Computed derived parameters: {}
2023-07-02 10:34:14,871 [model] Posterior to be computed for parameters {'Omega_m': 0.30523756247332773, 'b1': 0.5265386082254843}
2023-07-02 10:34:14,871 [prior] Evaluating prior at array([0.30523756, 0.52653861])
2023-07-02 10:34:14,871 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:14,871 [model] Got input parameters: {'Omega_m': 0.30523756247332773, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5265386082254843, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:14,871 [classy] Got parameters {'Omega_m': 0.30523756247332773, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:14,871 [classy] Computing new state
2023-07-02 10:34:14,872 [classy] Setting parameters: {'Omega_m': 0.30523756247332773, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:14,915 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.14115013602412}
2023-07-02 10:34:14,915 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:14,917 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00348146
2023-07-02 10:34:14,917 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5265386082254843, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:14,917 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:14,937 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.153
2023-07-02 10:34:14,937 [model] Computed derived parameters: {}
2023-07-02 10:34:14,937 [mcmc] New sample, #534:
Omega_m:0.3242074, b1:0.4970625
2023-07-02 10:34:14,937 [model] Posterior to be computed for parameters {'Omega_m': 0.30523756247332773, 'b1': 0.5398967333955982}
2023-07-02 10:34:14,937 [prior] Evaluating prior at array([0.30523756, 0.53989673])
2023-07-02 10:34:14,937 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:14,937 [model] Got input parameters: {'Omega_m': 0.30523756247332773, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5398967333955982, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:14,937 [classy] Got parameters {'Omega_m': 0.30523756247332773, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:14,937 [classy] Re-using computed results
2023-07-02 10:34:14,937 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.14115013602412}
2023-07-02 10:34:14,937 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:14,938 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5398967333955982, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:14,938 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:14,957 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.04669
2023-07-02 10:34:14,957 [model] Computed derived parameters: {}
2023-07-02 10:34:14,957 [mcmc] New sample, #535:
Omega_m:0.3052376, b1:0.5265386
2023-07-02 10:34:14,957 [model] Posterior to be computed for parameters {'Omega_m': 0.3153610714768006, 'b1': 0.5241664253958245}
2023-07-02 10:34:14,957 [prior] Evaluating prior at array([0.31536107, 0.52416643])
2023-07-02 10:34:14,957 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:14,957 [model] Got input parameters: {'Omega_m': 0.3153610714768006, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5241664253958245, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:14,957 [classy] Got parameters {'Omega_m': 0.3153610714768006, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:14,957 [classy] Computing new state
2023-07-02 10:34:14,957 [classy] Setting parameters: {'Omega_m': 0.3153610714768006, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:15,001 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.91533241195924}
2023-07-02 10:34:15,001 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:15,003 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000706452
2023-07-02 10:34:15,003 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5241664253958245, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,003 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:15,023 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.27115
2023-07-02 10:34:15,023 [model] Computed derived parameters: {}
2023-07-02 10:34:15,023 [mcmc] New sample, #536:
Omega_m:0.3052376, b1:0.5398967
2023-07-02 10:34:15,023 [model] Posterior to be computed for parameters {'Omega_m': 0.3153610714768006, 'b1': 0.5082600859606241}
2023-07-02 10:34:15,023 [prior] Evaluating prior at array([0.31536107, 0.50826009])
2023-07-02 10:34:15,023 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:15,023 [model] Got input parameters: {'Omega_m': 0.3153610714768006, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5082600859606241, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,023 [classy] Got parameters {'Omega_m': 0.3153610714768006, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:15,023 [classy] Re-using computed results
2023-07-02 10:34:15,023 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.91533241195924}
2023-07-02 10:34:15,023 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:15,023 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5082600859606241, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,023 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:15,043 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.7269
2023-07-02 10:34:15,043 [model] Computed derived parameters: {}
2023-07-02 10:34:15,043 [mcmc] New sample, #537:
Omega_m:0.3153611, b1:0.5241664
2023-07-02 10:34:15,043 [model] Posterior to be computed for parameters {'Omega_m': 0.30986375112911274, 'b1': 0.5168020393695545}
2023-07-02 10:34:15,043 [prior] Evaluating prior at array([0.30986375, 0.51680204])
2023-07-02 10:34:15,043 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:15,044 [model] Got input parameters: {'Omega_m': 0.30986375112911274, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5168020393695545, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,044 [classy] Got parameters {'Omega_m': 0.30986375112911274, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:15,044 [classy] Computing new state
2023-07-02 10:34:15,044 [classy] Setting parameters: {'Omega_m': 0.30986375112911274, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:15,087 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.5765990208315}
2023-07-02 10:34:15,087 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:15,089 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000626182
2023-07-02 10:34:15,089 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5168020393695545, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,089 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:15,109 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.62627
2023-07-02 10:34:15,109 [model] Computed derived parameters: {}
2023-07-02 10:34:15,109 [mcmc] New sample, #538:
Omega_m:0.3153611, b1:0.5082601
2023-07-02 10:34:15,109 [model] Posterior to be computed for parameters {'Omega_m': 0.30986375112911274, 'b1': 0.4796261148221118}
2023-07-02 10:34:15,109 [prior] Evaluating prior at array([0.30986375, 0.47962611])
2023-07-02 10:34:15,109 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:15,109 [model] Got input parameters: {'Omega_m': 0.30986375112911274, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4796261148221118, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,109 [classy] Got parameters {'Omega_m': 0.30986375112911274, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:15,109 [classy] Re-using computed results
2023-07-02 10:34:15,109 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.5765990208315}
2023-07-02 10:34:15,109 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:15,109 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4796261148221118, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,109 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:15,131 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.413385
2023-07-02 10:34:15,131 [model] Computed derived parameters: {}
2023-07-02 10:34:15,132 [model] Posterior to be computed for parameters {'Omega_m': 0.33003535821164065, 'b1': 0.4854585998418444}
2023-07-02 10:34:15,132 [prior] Evaluating prior at array([0.33003536, 0.4854586 ])
2023-07-02 10:34:15,132 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:15,132 [model] Got input parameters: {'Omega_m': 0.33003535821164065, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4854585998418444, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,132 [classy] Got parameters {'Omega_m': 0.33003535821164065, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:15,132 [classy] Computing new state
2023-07-02 10:34:15,132 [classy] Setting parameters: {'Omega_m': 0.33003535821164065, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:15,177 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.19935233230783}
2023-07-02 10:34:15,177 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:15,179 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0182985
2023-07-02 10:34:15,179 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4854585998418444, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,179 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:15,198 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.3398
2023-07-02 10:34:15,198 [model] Computed derived parameters: {}
2023-07-02 10:34:15,198 [model] Posterior to be computed for parameters {'Omega_m': 0.30986375112911274, 'b1': 0.46817791628454336}
2023-07-02 10:34:15,198 [prior] Evaluating prior at array([0.30986375, 0.46817792])
2023-07-02 10:34:15,199 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:15,199 [model] Got input parameters: {'Omega_m': 0.30986375112911274, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46817791628454336, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,199 [classy] Got parameters {'Omega_m': 0.30986375112911274, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:15,199 [classy] Re-using computed results
2023-07-02 10:34:15,199 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.5765990208315}
2023-07-02 10:34:15,199 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:15,199 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46817791628454336, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,199 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:15,218 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.66685
2023-07-02 10:34:15,218 [model] Computed derived parameters: {}
2023-07-02 10:34:15,218 [model] Posterior to be computed for parameters {'Omega_m': 0.30648004680805313, 'b1': 0.5220597727436418}
2023-07-02 10:34:15,218 [prior] Evaluating prior at array([0.30648005, 0.52205977])
2023-07-02 10:34:15,218 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:15,218 [model] Got input parameters: {'Omega_m': 0.30648004680805313, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5220597727436418, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,218 [classy] Got parameters {'Omega_m': 0.30648004680805313, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:15,218 [classy] Computing new state
2023-07-02 10:34:15,218 [classy] Setting parameters: {'Omega_m': 0.30648004680805313, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:15,262 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.98879132440524}
2023-07-02 10:34:15,262 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:15,264 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00244642
2023-07-02 10:34:15,264 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5220597727436418, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,264 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:15,284 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.37936
2023-07-02 10:34:15,284 [model] Computed derived parameters: {}
2023-07-02 10:34:15,284 [mcmc] New sample, #539:
Omega_m:0.3098638, b1:0.516802
2023-07-02 10:34:15,284 [model] Posterior to be computed for parameters {'Omega_m': 0.30648004680805313, 'b1': 0.4562033062552549}
2023-07-02 10:34:15,284 [prior] Evaluating prior at array([0.30648005, 0.45620331])
2023-07-02 10:34:15,284 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:15,284 [model] Got input parameters: {'Omega_m': 0.30648004680805313, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4562033062552549, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,284 [classy] Got parameters {'Omega_m': 0.30648004680805313, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:15,284 [classy] Re-using computed results
2023-07-02 10:34:15,285 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.98879132440524}
2023-07-02 10:34:15,285 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:15,285 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4562033062552549, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,285 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:15,304 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.46358
2023-07-02 10:34:15,304 [model] Computed derived parameters: {}
2023-07-02 10:34:15,304 [model] Posterior to be computed for parameters {'Omega_m': 0.36030100945801946, 'b1': 0.4384306359455362}
2023-07-02 10:34:15,304 [prior] Evaluating prior at array([0.36030101, 0.43843064])
2023-07-02 10:34:15,304 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:15,304 [model] Got input parameters: {'Omega_m': 0.36030100945801946, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4384306359455362, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,304 [classy] Got parameters {'Omega_m': 0.36030100945801946, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:15,304 [classy] Computing new state
2023-07-02 10:34:15,304 [classy] Setting parameters: {'Omega_m': 0.36030100945801946, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:15,348 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.86818117488713}
2023-07-02 10:34:15,348 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:15,350 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.125327
2023-07-02 10:34:15,350 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4384306359455362, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,350 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:15,369 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.63056
2023-07-02 10:34:15,370 [model] Computed derived parameters: {}
2023-07-02 10:34:15,370 [model] Posterior to be computed for parameters {'Omega_m': 0.30648004680805313, 'b1': 0.5227867378041536}
2023-07-02 10:34:15,370 [prior] Evaluating prior at array([0.30648005, 0.52278674])
2023-07-02 10:34:15,370 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:15,370 [model] Got input parameters: {'Omega_m': 0.30648004680805313, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5227867378041536, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,370 [classy] Got parameters {'Omega_m': 0.30648004680805313, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:15,370 [classy] Re-using computed results
2023-07-02 10:34:15,370 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.98879132440524}
2023-07-02 10:34:15,370 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:15,370 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5227867378041536, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,370 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:15,390 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.35344
2023-07-02 10:34:15,391 [model] Computed derived parameters: {}
2023-07-02 10:34:15,391 [mcmc] New sample, #540:
Omega_m:0.30648, b1:0.5220598
2023-07-02 10:34:15,391 [model] Posterior to be computed for parameters {'Omega_m': 0.2885560610632319, 'b1': 0.5506377345536866}
2023-07-02 10:34:15,391 [prior] Evaluating prior at array([0.28855606, 0.55063773])
2023-07-02 10:34:15,391 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:15,391 [model] Got input parameters: {'Omega_m': 0.2885560610632319, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5506377345536866, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,391 [classy] Got parameters {'Omega_m': 0.2885560610632319, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:15,391 [classy] Computing new state
2023-07-02 10:34:15,391 [classy] Setting parameters: {'Omega_m': 0.2885560610632319, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:15,435 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.24122881330186}
2023-07-02 10:34:15,435 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:15,436 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0375173
2023-07-02 10:34:15,437 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5506377345536866, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,437 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:15,456 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.54793
2023-07-02 10:34:15,456 [model] Computed derived parameters: {}
2023-07-02 10:34:15,456 [model] Posterior to be computed for parameters {'Omega_m': 0.30648004680805313, 'b1': 0.5640151924742844}
2023-07-02 10:34:15,456 [prior] Evaluating prior at array([0.30648005, 0.56401519])
2023-07-02 10:34:15,456 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:15,456 [model] Got input parameters: {'Omega_m': 0.30648004680805313, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5640151924742844, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,456 [classy] Got parameters {'Omega_m': 0.30648004680805313, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:15,456 [classy] Re-using computed results
2023-07-02 10:34:15,456 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.98879132440524}
2023-07-02 10:34:15,456 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:15,457 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5640151924742844, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,457 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:15,476 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.0294
2023-07-02 10:34:15,476 [model] Computed derived parameters: {}
2023-07-02 10:34:15,476 [model] Posterior to be computed for parameters {'Omega_m': 0.30276841155490936, 'b1': 0.5285540232083292}
2023-07-02 10:34:15,476 [prior] Evaluating prior at array([0.30276841, 0.52855402])
2023-07-02 10:34:15,476 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:15,476 [model] Got input parameters: {'Omega_m': 0.30276841155490936, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5285540232083292, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,476 [classy] Got parameters {'Omega_m': 0.30276841155490936, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:15,476 [classy] Computing new state
2023-07-02 10:34:15,476 [classy] Setting parameters: {'Omega_m': 0.30276841155490936, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:15,520 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.4455568792512}
2023-07-02 10:34:15,520 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:15,521 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0061335
2023-07-02 10:34:15,522 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5285540232083292, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,522 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:15,541 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.91616
2023-07-02 10:34:15,542 [model] Computed derived parameters: {}
2023-07-02 10:34:15,542 [mcmc] New sample, #541:
Omega_m:0.30648, b1:0.5227867
2023-07-02 10:34:15,542 [model] Posterior to be computed for parameters {'Omega_m': 0.30276841155490936, 'b1': 0.5294590749939853}
2023-07-02 10:34:15,542 [prior] Evaluating prior at array([0.30276841, 0.52945907])
2023-07-02 10:34:15,542 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:15,542 [model] Got input parameters: {'Omega_m': 0.30276841155490936, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5294590749939853, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,542 [classy] Got parameters {'Omega_m': 0.30276841155490936, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:15,542 [classy] Re-using computed results
2023-07-02 10:34:15,542 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.4455568792512}
2023-07-02 10:34:15,542 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:15,542 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5294590749939853, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,542 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:15,561 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.88479
2023-07-02 10:34:15,561 [model] Computed derived parameters: {}
2023-07-02 10:34:15,561 [mcmc] New sample, #542:
Omega_m:0.3027684, b1:0.528554
2023-07-02 10:34:15,561 [model] Posterior to be computed for parameters {'Omega_m': 0.3287326538909308, 'b1': 0.48911481009667834}
2023-07-02 10:34:15,562 [prior] Evaluating prior at array([0.32873265, 0.48911481])
2023-07-02 10:34:15,562 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:15,562 [model] Got input parameters: {'Omega_m': 0.3287326538909308, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48911481009667834, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,562 [classy] Got parameters {'Omega_m': 0.3287326538909308, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:15,562 [classy] Computing new state
2023-07-02 10:34:15,562 [classy] Setting parameters: {'Omega_m': 0.3287326538909308, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:15,606 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.3488921595526}
2023-07-02 10:34:15,606 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:15,608 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0157605
2023-07-02 10:34:15,608 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48911481009667834, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,608 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:15,627 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.43605
2023-07-02 10:34:15,627 [model] Computed derived parameters: {}
2023-07-02 10:34:15,627 [mcmc] New sample, #543:
Omega_m:0.3027684, b1:0.5294591
2023-07-02 10:34:15,627 [model] Posterior to be computed for parameters {'Omega_m': 0.3287326538909308, 'b1': 0.5023084131207975}
2023-07-02 10:34:15,627 [prior] Evaluating prior at array([0.32873265, 0.50230841])
2023-07-02 10:34:15,628 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:15,628 [model] Got input parameters: {'Omega_m': 0.3287326538909308, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5023084131207975, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,628 [classy] Got parameters {'Omega_m': 0.3287326538909308, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:15,628 [classy] Re-using computed results
2023-07-02 10:34:15,628 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.3488921595526}
2023-07-02 10:34:15,628 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:15,628 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5023084131207975, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,628 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:15,648 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.0706315
2023-07-02 10:34:15,648 [model] Computed derived parameters: {}
2023-07-02 10:34:15,648 [model] Posterior to be computed for parameters {'Omega_m': 0.3444973132799683, 'b1': 0.46461905989622776}
2023-07-02 10:34:15,648 [prior] Evaluating prior at array([0.34449731, 0.46461906])
2023-07-02 10:34:15,648 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:15,648 [model] Got input parameters: {'Omega_m': 0.3444973132799683, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46461905989622776, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,648 [classy] Got parameters {'Omega_m': 0.3444973132799683, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:15,648 [classy] Computing new state
2023-07-02 10:34:15,648 [classy] Setting parameters: {'Omega_m': 0.3444973132799683, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:15,692 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.57425491359498}
2023-07-02 10:34:15,692 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:15,694 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0583732
2023-07-02 10:34:15,694 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46461905989622776, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,694 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:15,713 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.21276
2023-07-02 10:34:15,713 [model] Computed derived parameters: {}
2023-07-02 10:34:15,714 [model] Posterior to be computed for parameters {'Omega_m': 0.3287326538909308, 'b1': 0.5180436646946928}
2023-07-02 10:34:15,714 [prior] Evaluating prior at array([0.32873265, 0.51804366])
2023-07-02 10:34:15,714 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:15,714 [model] Got input parameters: {'Omega_m': 0.3287326538909308, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5180436646946928, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,714 [classy] Got parameters {'Omega_m': 0.3287326538909308, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:15,714 [classy] Re-using computed results
2023-07-02 10:34:15,714 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.3488921595526}
2023-07-02 10:34:15,714 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:15,714 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5180436646946928, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,714 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:15,733 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.21671
2023-07-02 10:34:15,733 [model] Computed derived parameters: {}
2023-07-02 10:34:15,733 [model] Posterior to be computed for parameters {'Omega_m': 0.2944983735743141, 'b1': 0.5423093865371431}
2023-07-02 10:34:15,733 [prior] Evaluating prior at array([0.29449837, 0.54230939])
2023-07-02 10:34:15,733 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:15,733 [model] Got input parameters: {'Omega_m': 0.2944983735743141, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5423093865371431, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,734 [classy] Got parameters {'Omega_m': 0.2944983735743141, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:15,734 [classy] Computing new state
2023-07-02 10:34:15,734 [classy] Setting parameters: {'Omega_m': 0.2944983735743141, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:15,777 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.4812802738758}
2023-07-02 10:34:15,777 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:15,779 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0209632
2023-07-02 10:34:15,779 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5423093865371431, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,779 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:15,799 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.240779
2023-07-02 10:34:15,799 [model] Computed derived parameters: {}
2023-07-02 10:34:15,799 [mcmc] New sample, #544:
Omega_m:0.3287327, b1:0.4891148
2023-07-02 10:34:15,799 [model] Posterior to be computed for parameters {'Omega_m': 0.2944983735743141, 'b1': 0.5389394175172902}
2023-07-02 10:34:15,799 [prior] Evaluating prior at array([0.29449837, 0.53893942])
2023-07-02 10:34:15,799 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:15,799 [model] Got input parameters: {'Omega_m': 0.2944983735743141, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5389394175172902, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,799 [classy] Got parameters {'Omega_m': 0.2944983735743141, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:15,799 [classy] Re-using computed results
2023-07-02 10:34:15,799 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.4812802738758}
2023-07-02 10:34:15,799 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:15,799 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5389394175172902, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,799 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:15,819 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.295449
2023-07-02 10:34:15,819 [model] Computed derived parameters: {}
2023-07-02 10:34:15,819 [mcmc] New sample, #545:
Omega_m:0.2944984, b1:0.5423094
2023-07-02 10:34:15,819 [model] Posterior to be computed for parameters {'Omega_m': 0.333173893073786, 'b1': 0.4788438682794477}
2023-07-02 10:34:15,819 [prior] Evaluating prior at array([0.33317389, 0.47884387])
2023-07-02 10:34:15,819 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:15,819 [model] Got input parameters: {'Omega_m': 0.333173893073786, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4788438682794477, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,819 [classy] Got parameters {'Omega_m': 0.333173893073786, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:15,819 [classy] Computing new state
2023-07-02 10:34:15,819 [classy] Setting parameters: {'Omega_m': 0.333173893073786, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:15,863 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.84128413564446}
2023-07-02 10:34:15,863 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:15,864 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0251593
2023-07-02 10:34:15,865 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4788438682794477, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,865 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:15,884 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.87954
2023-07-02 10:34:15,884 [model] Computed derived parameters: {}
2023-07-02 10:34:15,884 [mcmc] New sample, #546:
Omega_m:0.2944984, b1:0.5389394
2023-07-02 10:34:15,884 [model] Posterior to be computed for parameters {'Omega_m': 0.333173893073786, 'b1': 0.43304443969117223}
2023-07-02 10:34:15,884 [prior] Evaluating prior at array([0.33317389, 0.43304444])
2023-07-02 10:34:15,884 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:15,884 [model] Got input parameters: {'Omega_m': 0.333173893073786, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.43304443969117223, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,884 [classy] Got parameters {'Omega_m': 0.333173893073786, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:15,884 [classy] Re-using computed results
2023-07-02 10:34:15,884 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.84128413564446}
2023-07-02 10:34:15,884 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:15,884 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.43304443969117223, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,884 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:15,904 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.88247
2023-07-02 10:34:15,904 [model] Computed derived parameters: {}
2023-07-02 10:34:15,904 [model] Posterior to be computed for parameters {'Omega_m': 0.3396662398576064, 'b1': 0.4687558035070648}
2023-07-02 10:34:15,904 [prior] Evaluating prior at array([0.33966624, 0.4687558 ])
2023-07-02 10:34:15,904 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:15,904 [model] Got input parameters: {'Omega_m': 0.3396662398576064, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4687558035070648, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,904 [classy] Got parameters {'Omega_m': 0.3396662398576064, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:15,904 [classy] Computing new state
2023-07-02 10:34:15,905 [classy] Setting parameters: {'Omega_m': 0.3396662398576064, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:15,948 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.11013980766754}
2023-07-02 10:34:15,948 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:15,950 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0426192
2023-07-02 10:34:15,950 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4687558035070648, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,950 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:15,970 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.586026
2023-07-02 10:34:15,970 [model] Computed derived parameters: {}
2023-07-02 10:34:15,980 [mcmc] Progress @ 2023-07-02 10:34:15 : 1411 steps taken, and 546 accepted.
2023-07-02 10:34:15,980 [model] Posterior to be computed for parameters {'Omega_m': 0.333173893073786, 'b1': 0.46139290275356704}
2023-07-02 10:34:15,980 [prior] Evaluating prior at array([0.33317389, 0.4613929 ])
2023-07-02 10:34:15,981 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:15,981 [model] Got input parameters: {'Omega_m': 0.333173893073786, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46139290275356704, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,981 [classy] Got parameters {'Omega_m': 0.333173893073786, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:15,981 [classy] Re-using computed results
2023-07-02 10:34:15,981 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.84128413564446}
2023-07-02 10:34:15,981 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:15,981 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46139290275356704, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:15,981 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:16,001 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.14332
2023-07-02 10:34:16,001 [model] Computed derived parameters: {}
2023-07-02 10:34:16,001 [mcmc] New sample, #547:
Omega_m:0.3331739, b1:0.4788439
2023-07-02 10:34:16,001 [model] Posterior to be computed for parameters {'Omega_m': 0.335504454211472, 'b1': 0.45777158483943986}
2023-07-02 10:34:16,001 [prior] Evaluating prior at array([0.33550445, 0.45777158])
2023-07-02 10:34:16,002 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:16,002 [model] Got input parameters: {'Omega_m': 0.335504454211472, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45777158483943986, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:16,002 [classy] Got parameters {'Omega_m': 0.335504454211472, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:16,002 [classy] Computing new state
2023-07-02 10:34:16,002 [classy] Setting parameters: {'Omega_m': 0.335504454211472, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:16,046 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.57735576085673}
2023-07-02 10:34:16,046 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:16,048 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0309266
2023-07-02 10:34:16,048 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45777158483943986, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:16,048 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:16,067 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.717662
2023-07-02 10:34:16,067 [model] Computed derived parameters: {}
2023-07-02 10:34:16,067 [model] Posterior to be computed for parameters {'Omega_m': 0.333173893073786, 'b1': 0.44570874619334866}
2023-07-02 10:34:16,067 [prior] Evaluating prior at array([0.33317389, 0.44570875])
2023-07-02 10:34:16,067 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:16,067 [model] Got input parameters: {'Omega_m': 0.333173893073786, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44570874619334866, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:16,067 [classy] Got parameters {'Omega_m': 0.333173893073786, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:16,068 [classy] Re-using computed results
2023-07-02 10:34:16,068 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.84128413564446}
2023-07-02 10:34:16,068 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:16,068 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44570874619334866, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:16,068 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:16,087 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.020215
2023-07-02 10:34:16,087 [model] Computed derived parameters: {}
2023-07-02 10:34:16,087 [model] Posterior to be computed for parameters {'Omega_m': 0.32257144637319035, 'b1': 0.4778674030572008}
2023-07-02 10:34:16,087 [prior] Evaluating prior at array([0.32257145, 0.4778674 ])
2023-07-02 10:34:16,087 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:16,088 [model] Got input parameters: {'Omega_m': 0.32257144637319035, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4778674030572008, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:16,088 [classy] Got parameters {'Omega_m': 0.32257144637319035, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:16,088 [classy] Computing new state
2023-07-02 10:34:16,088 [classy] Setting parameters: {'Omega_m': 0.32257144637319035, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:16,133 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.06345424376704}
2023-07-02 10:34:16,133 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:16,135 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00628852
2023-07-02 10:34:16,135 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4778674030572008, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:16,135 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:16,156 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.42429
2023-07-02 10:34:16,156 [model] Computed derived parameters: {}
2023-07-02 10:34:16,156 [mcmc] New sample, #548:
Omega_m:0.3331739, b1:0.4613929
2023-07-02 10:34:16,156 [model] Posterior to be computed for parameters {'Omega_m': 0.32257144637319035, 'b1': 0.49862824477713624}
2023-07-02 10:34:16,156 [prior] Evaluating prior at array([0.32257145, 0.49862824])
2023-07-02 10:34:16,156 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:16,156 [model] Got input parameters: {'Omega_m': 0.32257144637319035, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49862824477713624, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:16,156 [classy] Got parameters {'Omega_m': 0.32257144637319035, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:16,156 [classy] Re-using computed results
2023-07-02 10:34:16,156 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.06345424376704}
2023-07-02 10:34:16,156 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:16,156 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49862824477713624, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:16,156 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:16,176 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.23296
2023-07-02 10:34:16,176 [model] Computed derived parameters: {}
2023-07-02 10:34:16,176 [mcmc] New sample, #549:
Omega_m:0.3225714, b1:0.4778674
2023-07-02 10:34:16,176 [model] Posterior to be computed for parameters {'Omega_m': 0.32836670863896106, 'b1': 0.4896233374521399}
2023-07-02 10:34:16,176 [prior] Evaluating prior at array([0.32836671, 0.48962334])
2023-07-02 10:34:16,176 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:16,176 [model] Got input parameters: {'Omega_m': 0.32836670863896106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4896233374521399, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:16,176 [classy] Got parameters {'Omega_m': 0.32836670863896106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:16,177 [classy] Computing new state
2023-07-02 10:34:16,177 [classy] Setting parameters: {'Omega_m': 0.32836670863896106, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:16,220 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.39099589080354}
2023-07-02 10:34:16,220 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:16,222 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0150807
2023-07-02 10:34:16,222 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4896233374521399, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:16,222 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:16,242 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.49835
2023-07-02 10:34:16,242 [model] Computed derived parameters: {}
2023-07-02 10:34:16,242 [mcmc] New sample, #550:
Omega_m:0.3225714, b1:0.4986282
2023-07-02 10:34:16,242 [model] Posterior to be computed for parameters {'Omega_m': 0.32836670863896106, 'b1': 0.4691245253120672}
2023-07-02 10:34:16,242 [prior] Evaluating prior at array([0.32836671, 0.46912453])
2023-07-02 10:34:16,242 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:16,243 [model] Got input parameters: {'Omega_m': 0.32836670863896106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4691245253120672, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:16,243 [classy] Got parameters {'Omega_m': 0.32836670863896106, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:16,243 [classy] Re-using computed results
2023-07-02 10:34:16,243 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.39099589080354}
2023-07-02 10:34:16,243 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:16,243 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4691245253120672, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:16,243 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:16,262 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.87155
2023-07-02 10:34:16,262 [model] Computed derived parameters: {}
2023-07-02 10:34:16,262 [mcmc] New sample, #551:
Omega_m:0.3283667, b1:0.4896233
2023-07-02 10:34:16,262 [model] Posterior to be computed for parameters {'Omega_m': 0.32678173130872135, 'b1': 0.4715873256680284}
2023-07-02 10:34:16,262 [prior] Evaluating prior at array([0.32678173, 0.47158733])
2023-07-02 10:34:16,263 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:16,263 [model] Got input parameters: {'Omega_m': 0.32678173130872135, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4715873256680284, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:16,263 [classy] Got parameters {'Omega_m': 0.32678173130872135, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:16,263 [classy] Computing new state
2023-07-02 10:34:16,263 [classy] Setting parameters: {'Omega_m': 0.32678173130872135, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:16,306 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.57384767432077}
2023-07-02 10:34:16,306 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:16,308 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0123054
2023-07-02 10:34:16,308 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4715873256680284, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:16,308 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:16,327 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.05985
2023-07-02 10:34:16,328 [model] Computed derived parameters: {}
2023-07-02 10:34:16,328 [mcmc] New sample, #552:
Omega_m:0.3283667, b1:0.4691245
2023-07-02 10:34:16,328 [model] Posterior to be computed for parameters {'Omega_m': 0.32678173130872135, 'b1': 0.44329725119594615}
2023-07-02 10:34:16,328 [prior] Evaluating prior at array([0.32678173, 0.44329725])
2023-07-02 10:34:16,328 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:16,328 [model] Got input parameters: {'Omega_m': 0.32678173130872135, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44329725119594615, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:16,328 [classy] Got parameters {'Omega_m': 0.32678173130872135, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:16,328 [classy] Re-using computed results
2023-07-02 10:34:16,328 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.57384767432077}
2023-07-02 10:34:16,328 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:16,328 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44329725119594615, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:16,328 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:16,348 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.13831
2023-07-02 10:34:16,348 [model] Computed derived parameters: {}
2023-07-02 10:34:16,348 [model] Posterior to be computed for parameters {'Omega_m': 0.34104823326330724, 'b1': 0.449419471641522}
2023-07-02 10:34:16,348 [prior] Evaluating prior at array([0.34104823, 0.44941947])
2023-07-02 10:34:16,348 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:16,348 [model] Got input parameters: {'Omega_m': 0.34104823326330724, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.449419471641522, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:16,348 [classy] Got parameters {'Omega_m': 0.34104823326330724, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:16,348 [classy] Computing new state
2023-07-02 10:34:16,348 [classy] Setting parameters: {'Omega_m': 0.34104823326330724, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:16,392 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.9561400373312}
2023-07-02 10:34:16,392 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:16,394 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0468897
2023-07-02 10:34:16,394 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.449419471641522, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:16,394 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:16,414 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.48121
2023-07-02 10:34:16,414 [model] Computed derived parameters: {}
2023-07-02 10:34:16,414 [model] Posterior to be computed for parameters {'Omega_m': 0.32678173130872135, 'b1': 0.422309050519154}
2023-07-02 10:34:16,414 [prior] Evaluating prior at array([0.32678173, 0.42230905])
2023-07-02 10:34:16,414 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:16,414 [model] Got input parameters: {'Omega_m': 0.32678173130872135, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.422309050519154, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:16,414 [classy] Got parameters {'Omega_m': 0.32678173130872135, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:16,414 [classy] Re-using computed results
2023-07-02 10:34:16,414 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.57384767432077}
2023-07-02 10:34:16,414 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:16,414 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.422309050519154, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:16,414 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:16,434 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.05292
2023-07-02 10:34:16,434 [model] Computed derived parameters: {}
2023-07-02 10:34:16,434 [model] Posterior to be computed for parameters {'Omega_m': 0.3273426791516871, 'b1': 0.47071570276152114}
2023-07-02 10:34:16,434 [prior] Evaluating prior at array([0.32734268, 0.4707157 ])
2023-07-02 10:34:16,434 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:16,434 [model] Got input parameters: {'Omega_m': 0.3273426791516871, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47071570276152114, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:16,434 [classy] Got parameters {'Omega_m': 0.3273426791516871, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:16,434 [classy] Computing new state
2023-07-02 10:34:16,434 [classy] Setting parameters: {'Omega_m': 0.3273426791516871, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:16,478 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.50904260710018}
2023-07-02 10:34:16,478 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:16,480 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0132561
2023-07-02 10:34:16,480 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47071570276152114, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:16,480 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:16,500 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.99606
2023-07-02 10:34:16,500 [model] Computed derived parameters: {}
2023-07-02 10:34:16,500 [mcmc] New sample, #553:
Omega_m:0.3267817, b1:0.4715873
2023-07-02 10:34:16,500 [model] Posterior to be computed for parameters {'Omega_m': 0.3273426791516871, 'b1': 0.4400329831026975}
2023-07-02 10:34:16,500 [prior] Evaluating prior at array([0.32734268, 0.44003298])
2023-07-02 10:34:16,500 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:16,500 [model] Got input parameters: {'Omega_m': 0.3273426791516871, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4400329831026975, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:16,500 [classy] Got parameters {'Omega_m': 0.3273426791516871, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:16,500 [classy] Re-using computed results
2023-07-02 10:34:16,500 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.50904260710018}
2023-07-02 10:34:16,500 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:16,500 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4400329831026975, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:16,500 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:16,520 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.63577
2023-07-02 10:34:16,520 [model] Computed derived parameters: {}
2023-07-02 10:34:16,520 [model] Posterior to be computed for parameters {'Omega_m': 0.3412016119405975, 'b1': 0.4491811457968425}
2023-07-02 10:34:16,520 [prior] Evaluating prior at array([0.34120161, 0.44918115])
2023-07-02 10:34:16,520 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:16,520 [model] Got input parameters: {'Omega_m': 0.3412016119405975, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4491811457968425, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:16,520 [classy] Got parameters {'Omega_m': 0.3412016119405975, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:16,520 [classy] Computing new state
2023-07-02 10:34:16,520 [classy] Setting parameters: {'Omega_m': 0.3412016119405975, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:16,564 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.93908241059165}
2023-07-02 10:34:16,564 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:16,566 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0473754
2023-07-02 10:34:16,566 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4491811457968425, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:16,566 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:16,586 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.51829
2023-07-02 10:34:16,586 [model] Computed derived parameters: {}
2023-07-02 10:34:16,586 [model] Posterior to be computed for parameters {'Omega_m': 0.3273426791516871, 'b1': 0.4840401309562115}
2023-07-02 10:34:16,586 [prior] Evaluating prior at array([0.32734268, 0.48404013])
2023-07-02 10:34:16,586 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:16,586 [model] Got input parameters: {'Omega_m': 0.3273426791516871, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4840401309562115, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:16,586 [classy] Got parameters {'Omega_m': 0.3273426791516871, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:16,586 [classy] Re-using computed results
2023-07-02 10:34:16,586 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.50904260710018}
2023-07-02 10:34:16,586 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:16,586 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4840401309562115, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:16,586 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:16,606 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.03684
2023-07-02 10:34:16,606 [model] Computed derived parameters: {}
2023-07-02 10:34:16,606 [mcmc] New sample, #554:
Omega_m:0.3273427, b1:0.4707157
2023-07-02 10:34:16,606 [model] Posterior to be computed for parameters {'Omega_m': 0.3523354420496836, 'b1': 0.4452053891669828}
2023-07-02 10:34:16,606 [prior] Evaluating prior at array([0.35233544, 0.44520539])
2023-07-02 10:34:16,606 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:16,606 [model] Got input parameters: {'Omega_m': 0.3523354420496836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4452053891669828, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:16,607 [classy] Got parameters {'Omega_m': 0.3523354420496836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:16,607 [classy] Computing new state
2023-07-02 10:34:16,607 [classy] Setting parameters: {'Omega_m': 0.3523354420496836, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:16,650 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.71933054335227}
2023-07-02 10:34:16,650 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:16,652 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0887129
2023-07-02 10:34:16,652 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4452053891669828, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:16,652 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:16,671 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.12387
2023-07-02 10:34:16,672 [model] Computed derived parameters: {}
2023-07-02 10:34:16,672 [model] Posterior to be computed for parameters {'Omega_m': 0.3273426791516871, 'b1': 0.4498700782205796}
2023-07-02 10:34:16,672 [prior] Evaluating prior at array([0.32734268, 0.44987008])
2023-07-02 10:34:16,672 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:16,672 [model] Got input parameters: {'Omega_m': 0.3273426791516871, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4498700782205796, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:16,672 [classy] Got parameters {'Omega_m': 0.3273426791516871, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:16,672 [classy] Re-using computed results
2023-07-02 10:34:16,672 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.50904260710018}
2023-07-02 10:34:16,672 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:16,672 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4498700782205796, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:16,672 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:16,692 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.0470865
2023-07-02 10:34:16,692 [model] Computed derived parameters: {}
2023-07-02 10:34:16,692 [model] Posterior to be computed for parameters {'Omega_m': 0.3106254396811001, 'b1': 0.5100160376984385}
2023-07-02 10:34:16,692 [prior] Evaluating prior at array([0.31062544, 0.51001604])
2023-07-02 10:34:16,692 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:16,692 [model] Got input parameters: {'Omega_m': 0.3106254396811001, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5100160376984385, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:16,692 [classy] Got parameters {'Omega_m': 0.3106254396811001, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:16,692 [classy] Computing new state
2023-07-02 10:34:16,692 [classy] Setting parameters: {'Omega_m': 0.3106254396811001, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:16,736 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.4843584563492}
2023-07-02 10:34:16,736 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:16,738 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000415187
2023-07-02 10:34:16,738 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5100160376984385, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:16,738 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:16,758 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.79923
2023-07-02 10:34:16,758 [model] Computed derived parameters: {}
2023-07-02 10:34:16,758 [mcmc] New sample, #555:
Omega_m:0.3273427, b1:0.4840401
2023-07-02 10:34:16,758 [model] Posterior to be computed for parameters {'Omega_m': 0.3106254396811001, 'b1': 0.5497728022164425}
2023-07-02 10:34:16,758 [prior] Evaluating prior at array([0.31062544, 0.5497728 ])
2023-07-02 10:34:16,758 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:16,758 [model] Got input parameters: {'Omega_m': 0.3106254396811001, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5497728022164425, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:16,758 [classy] Got parameters {'Omega_m': 0.3106254396811001, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:16,758 [classy] Re-using computed results
2023-07-02 10:34:16,758 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.4843584563492}
2023-07-02 10:34:16,758 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:16,758 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5497728022164425, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:16,758 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:16,777 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.0067
2023-07-02 10:34:16,778 [model] Computed derived parameters: {}
2023-07-02 10:34:16,778 [model] Posterior to be computed for parameters {'Omega_m': 0.28956282242490256, 'b1': 0.5427439640140743}
2023-07-02 10:34:16,778 [prior] Evaluating prior at array([0.28956282, 0.54274396])
2023-07-02 10:34:16,778 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:16,778 [model] Got input parameters: {'Omega_m': 0.28956282242490256, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5427439640140743, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:16,778 [classy] Got parameters {'Omega_m': 0.28956282242490256, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:16,778 [classy] Computing new state
2023-07-02 10:34:16,778 [classy] Setting parameters: {'Omega_m': 0.28956282242490256, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:16,822 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.11152995899099}
2023-07-02 10:34:16,822 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:16,824 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0343539
2023-07-02 10:34:16,824 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5427439640140743, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:16,824 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:16,843 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.2228
2023-07-02 10:34:16,843 [model] Computed derived parameters: {}
2023-07-02 10:34:16,843 [model] Posterior to be computed for parameters {'Omega_m': 0.3106254396811001, 'b1': 0.4848255436293355}
2023-07-02 10:34:16,843 [prior] Evaluating prior at array([0.31062544, 0.48482554])
2023-07-02 10:34:16,843 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:16,844 [model] Got input parameters: {'Omega_m': 0.3106254396811001, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4848255436293355, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:16,844 [classy] Got parameters {'Omega_m': 0.3106254396811001, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:16,844 [classy] Re-using computed results
2023-07-02 10:34:16,844 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.4843584563492}
2023-07-02 10:34:16,844 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:16,844 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4848255436293355, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:16,844 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:16,864 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.36336
2023-07-02 10:34:16,864 [model] Computed derived parameters: {}
2023-07-02 10:34:16,864 [mcmc] New sample, #556:
Omega_m:0.3106254, b1:0.510016
2023-07-02 10:34:16,864 [model] Posterior to be computed for parameters {'Omega_m': 0.2888608337685909, 'b1': 0.5186442476360211}
2023-07-02 10:34:16,864 [prior] Evaluating prior at array([0.28886083, 0.51864425])
2023-07-02 10:34:16,864 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:16,864 [model] Got input parameters: {'Omega_m': 0.2888608337685909, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5186442476360211, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:16,864 [classy] Got parameters {'Omega_m': 0.2888608337685909, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:16,864 [classy] Computing new state
2023-07-02 10:34:16,864 [classy] Setting parameters: {'Omega_m': 0.2888608337685909, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:16,908 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.201922881403}
2023-07-02 10:34:16,908 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:16,910 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0365439
2023-07-02 10:34:16,910 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5186442476360211, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:16,910 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:16,929 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.58873
2023-07-02 10:34:16,929 [model] Computed derived parameters: {}
2023-07-02 10:34:16,929 [model] Posterior to be computed for parameters {'Omega_m': 0.3106254396811001, 'b1': 0.42169762913828684}
2023-07-02 10:34:16,929 [prior] Evaluating prior at array([0.31062544, 0.42169763])
2023-07-02 10:34:16,930 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:16,930 [model] Got input parameters: {'Omega_m': 0.3106254396811001, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42169762913828684, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:16,930 [classy] Got parameters {'Omega_m': 0.3106254396811001, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:16,930 [classy] Re-using computed results
2023-07-02 10:34:16,930 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.4843584563492}
2023-07-02 10:34:16,930 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:16,930 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42169762913828684, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:16,930 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:16,949 [fs_likelihood.fslikelihood] Computed log-likelihood = -15.6306
2023-07-02 10:34:16,949 [model] Computed derived parameters: {}
2023-07-02 10:34:16,949 [model] Posterior to be computed for parameters {'Omega_m': 0.3165448489039054, 'b1': 0.4756277318607595}
2023-07-02 10:34:16,949 [prior] Evaluating prior at array([0.31654485, 0.47562773])
2023-07-02 10:34:16,949 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:16,949 [model] Got input parameters: {'Omega_m': 0.3165448489039054, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4756277318607595, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:16,949 [classy] Got parameters {'Omega_m': 0.3165448489039054, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:16,949 [classy] Computing new state
2023-07-02 10:34:16,949 [classy] Setting parameters: {'Omega_m': 0.3165448489039054, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:16,994 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.77429325573698}
2023-07-02 10:34:16,994 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:16,996 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00120348
2023-07-02 10:34:16,996 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4756277318607595, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:16,996 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:17,016 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.64801
2023-07-02 10:34:17,016 [model] Computed derived parameters: {}
2023-07-02 10:34:17,016 [mcmc] New sample, #557:
Omega_m:0.3106254, b1:0.4848255
2023-07-02 10:34:17,016 [model] Posterior to be computed for parameters {'Omega_m': 0.3165448489039054, 'b1': 0.4651667974868253}
2023-07-02 10:34:17,016 [prior] Evaluating prior at array([0.31654485, 0.4651668 ])
2023-07-02 10:34:17,017 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:17,017 [model] Got input parameters: {'Omega_m': 0.3165448489039054, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4651667974868253, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:17,017 [classy] Got parameters {'Omega_m': 0.3165448489039054, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:17,017 [classy] Re-using computed results
2023-07-02 10:34:17,017 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.77429325573698}
2023-07-02 10:34:17,017 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:17,017 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4651667974868253, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:17,017 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:17,038 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.177217
2023-07-02 10:34:17,038 [model] Computed derived parameters: {}
2023-07-02 10:34:17,038 [model] Posterior to be computed for parameters {'Omega_m': 0.30511801097629115, 'b1': 0.4933832038026727}
2023-07-02 10:34:17,038 [prior] Evaluating prior at array([0.30511801, 0.4933832 ])
2023-07-02 10:34:17,038 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:17,038 [model] Got input parameters: {'Omega_m': 0.30511801097629115, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4933832038026727, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:17,038 [classy] Got parameters {'Omega_m': 0.30511801097629115, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:17,038 [classy] Computing new state
2023-07-02 10:34:17,039 [classy] Setting parameters: {'Omega_m': 0.30511801097629115, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:17,083 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.1558405140349}
2023-07-02 10:34:17,083 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:17,084 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00359159
2023-07-02 10:34:17,084 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4933832038026727, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:17,084 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:17,104 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.715657
2023-07-02 10:34:17,104 [model] Computed derived parameters: {}
2023-07-02 10:34:17,104 [mcmc] New sample, #558:
Omega_m:0.3165448, b1:0.4756277
2023-07-02 10:34:17,104 [model] Posterior to be computed for parameters {'Omega_m': 0.30511801097629115, 'b1': 0.4631054968930223}
2023-07-02 10:34:17,104 [prior] Evaluating prior at array([0.30511801, 0.4631055 ])
2023-07-02 10:34:17,104 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:17,104 [model] Got input parameters: {'Omega_m': 0.30511801097629115, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4631054968930223, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:17,104 [classy] Got parameters {'Omega_m': 0.30511801097629115, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:17,104 [classy] Re-using computed results
2023-07-02 10:34:17,104 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.1558405140349}
2023-07-02 10:34:17,104 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:17,104 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4631054968930223, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:17,104 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:17,125 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.36033
2023-07-02 10:34:17,125 [model] Computed derived parameters: {}
2023-07-02 10:34:17,125 [model] Posterior to be computed for parameters {'Omega_m': 0.3089625092287251, 'b1': 0.48740947062432205}
2023-07-02 10:34:17,125 [prior] Evaluating prior at array([0.30896251, 0.48740947])
2023-07-02 10:34:17,126 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:17,126 [model] Got input parameters: {'Omega_m': 0.3089625092287251, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48740947062432205, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:17,126 [classy] Got parameters {'Omega_m': 0.3089625092287251, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:17,126 [classy] Computing new state
2023-07-02 10:34:17,126 [classy] Setting parameters: {'Omega_m': 0.3089625092287251, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:17,171 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.68599715977578}
2023-07-02 10:34:17,171 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:17,173 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000969591
2023-07-02 10:34:17,173 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48740947062432205, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:17,173 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:17,194 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.20784
2023-07-02 10:34:17,194 [model] Computed derived parameters: {}
2023-07-02 10:34:17,194 [mcmc] New sample, #559:
Omega_m:0.305118, b1:0.4933832
2023-07-02 10:34:17,194 [model] Posterior to be computed for parameters {'Omega_m': 0.3089625092287251, 'b1': 0.44693862254810013}
2023-07-02 10:34:17,194 [prior] Evaluating prior at array([0.30896251, 0.44693862])
2023-07-02 10:34:17,194 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:17,194 [model] Got input parameters: {'Omega_m': 0.3089625092287251, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44693862254810013, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:17,194 [classy] Got parameters {'Omega_m': 0.3089625092287251, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:17,194 [classy] Re-using computed results
2023-07-02 10:34:17,194 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.68599715977578}
2023-07-02 10:34:17,194 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:17,194 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44693862254810013, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:17,194 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:17,215 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.7044
2023-07-02 10:34:17,216 [model] Computed derived parameters: {}
2023-07-02 10:34:17,216 [model] Posterior to be computed for parameters {'Omega_m': 0.3290862865472117, 'b1': 0.4561403508724592}
2023-07-02 10:34:17,216 [prior] Evaluating prior at array([0.32908629, 0.45614035])
2023-07-02 10:34:17,216 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:17,216 [model] Got input parameters: {'Omega_m': 0.3290862865472117, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4561403508724592, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:17,216 [classy] Got parameters {'Omega_m': 0.3290862865472117, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:17,216 [classy] Computing new state
2023-07-02 10:34:17,216 [classy] Setting parameters: {'Omega_m': 0.3290862865472117, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:17,261 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.3082419495965}
2023-07-02 10:34:17,261 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:17,263 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0164314
2023-07-02 10:34:17,263 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4561403508724592, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:17,263 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:17,284 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.969876
2023-07-02 10:34:17,284 [model] Computed derived parameters: {}
2023-07-02 10:34:17,284 [model] Posterior to be computed for parameters {'Omega_m': 0.3089625092287251, 'b1': 0.46421764612128774}
2023-07-02 10:34:17,284 [prior] Evaluating prior at array([0.30896251, 0.46421765])
2023-07-02 10:34:17,284 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:17,284 [model] Got input parameters: {'Omega_m': 0.3089625092287251, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46421764612128774, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:17,284 [classy] Got parameters {'Omega_m': 0.3089625092287251, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:17,284 [classy] Re-using computed results
2023-07-02 10:34:17,285 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.68599715977578}
2023-07-02 10:34:17,285 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:17,285 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46421764612128774, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:17,285 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:17,304 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.96603
2023-07-02 10:34:17,304 [model] Computed derived parameters: {}
2023-07-02 10:34:17,304 [model] Posterior to be computed for parameters {'Omega_m': 0.2862665091378119, 'b1': 0.5226754116799859}
2023-07-02 10:34:17,304 [prior] Evaluating prior at array([0.28626651, 0.52267541])
2023-07-02 10:34:17,304 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:17,304 [model] Got input parameters: {'Omega_m': 0.2862665091378119, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5226754116799859, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:17,304 [classy] Got parameters {'Omega_m': 0.2862665091378119, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:17,304 [classy] Computing new state
2023-07-02 10:34:17,305 [classy] Setting parameters: {'Omega_m': 0.2862665091378119, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:17,349 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.53764835325944}
2023-07-02 10:34:17,349 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:17,351 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.045268
2023-07-02 10:34:17,351 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5226754116799859, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:17,351 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:17,371 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.6369
2023-07-02 10:34:17,371 [model] Computed derived parameters: {}
2023-07-02 10:34:17,371 [model] Posterior to be computed for parameters {'Omega_m': 0.3089625092287251, 'b1': 0.41340429321664374}
2023-07-02 10:34:17,371 [prior] Evaluating prior at array([0.30896251, 0.41340429])
2023-07-02 10:34:17,371 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:17,371 [model] Got input parameters: {'Omega_m': 0.3089625092287251, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.41340429321664374, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:17,371 [classy] Got parameters {'Omega_m': 0.3089625092287251, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:17,371 [classy] Re-using computed results
2023-07-02 10:34:17,371 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.68599715977578}
2023-07-02 10:34:17,371 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:17,371 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.41340429321664374, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:17,371 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:17,391 [fs_likelihood.fslikelihood] Computed log-likelihood = -20.5581
2023-07-02 10:34:17,391 [model] Computed derived parameters: {}
2023-07-02 10:34:17,391 [model] Posterior to be computed for parameters {'Omega_m': 0.3604808183438888, 'b1': 0.4073582878050974}
2023-07-02 10:34:17,391 [prior] Evaluating prior at array([0.36048082, 0.40735829])
2023-07-02 10:34:17,391 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:17,391 [model] Got input parameters: {'Omega_m': 0.3604808183438888, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4073582878050974, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:17,391 [classy] Got parameters {'Omega_m': 0.3604808183438888, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:17,391 [classy] Computing new state
2023-07-02 10:34:17,391 [classy] Setting parameters: {'Omega_m': 0.3604808183438888, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:17,435 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.84917048579166}
2023-07-02 10:34:17,435 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:17,437 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.126218
2023-07-02 10:34:17,437 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4073582878050974, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:17,437 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:17,456 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.91909
2023-07-02 10:34:17,456 [model] Computed derived parameters: {}
2023-07-02 10:34:17,456 [model] Posterior to be computed for parameters {'Omega_m': 0.3089625092287251, 'b1': 0.49743446946431746}
2023-07-02 10:34:17,456 [prior] Evaluating prior at array([0.30896251, 0.49743447])
2023-07-02 10:34:17,456 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:17,457 [model] Got input parameters: {'Omega_m': 0.3089625092287251, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49743446946431746, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:17,457 [classy] Got parameters {'Omega_m': 0.3089625092287251, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:17,457 [classy] Re-using computed results
2023-07-02 10:34:17,457 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.68599715977578}
2023-07-02 10:34:17,457 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:17,457 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49743446946431746, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:17,457 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:17,476 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.19375
2023-07-02 10:34:17,476 [model] Computed derived parameters: {}
2023-07-02 10:34:17,476 [mcmc] New sample, #560:
Omega_m:0.3089625, b1:0.4874095
2023-07-02 10:34:17,476 [mcmc] Learn + convergence test @ 560 samples accepted.
2023-07-02 10:34:17,476 [mcmc] Ready to check convergence and learn a new proposal covmat
2023-07-02 10:34:17,481 [mcmc] - Acceptance rate: 0.458
2023-07-02 10:34:17,482 [mcmc] - Condition number = 6.51786
2023-07-02 10:34:17,482 [mcmc] - Eigenvalues = array([0.0126918 , 0.08272334])
2023-07-02 10:34:17,482 [mcmc] - Convergence of means: R-1 = 0.082723 after 448 accepted steps
2023-07-02 10:34:17,482 [mcmc] - Updated covariance matrix of proposal pdf.
2023-07-02 10:34:17,482 [mcmc] array([[ 9.69406425e-05, -1.55540497e-04],
[-1.55540497e-04, 4.21144443e-04]])
2023-07-02 10:34:17,492 [mcmc] Dumped checkpoint and progress info, and current covmat.
2023-07-02 10:34:17,492 [model] Posterior to be computed for parameters {'Omega_m': 0.3328675817018873, 'b1': 0.4590789691789578}
2023-07-02 10:34:17,492 [prior] Evaluating prior at array([0.33286758, 0.45907897])
2023-07-02 10:34:17,493 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:17,493 [model] Got input parameters: {'Omega_m': 0.3328675817018873, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4590789691789578, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:17,493 [classy] Got parameters {'Omega_m': 0.3328675817018873, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:17,493 [classy] Computing new state
2023-07-02 10:34:17,493 [classy] Setting parameters: {'Omega_m': 0.3328675817018873, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:17,538 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.87609464967395}
2023-07-02 10:34:17,538 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:17,540 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0244437
2023-07-02 10:34:17,540 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4590789691789578, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:17,540 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:17,560 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.08242
2023-07-02 10:34:17,560 [model] Computed derived parameters: {}
2023-07-02 10:34:17,560 [model] Posterior to be computed for parameters {'Omega_m': 0.3089625092287251, 'b1': 0.4880039345539698}
2023-07-02 10:34:17,560 [prior] Evaluating prior at array([0.30896251, 0.48800393])
2023-07-02 10:34:17,560 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:17,560 [model] Got input parameters: {'Omega_m': 0.3089625092287251, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4880039345539698, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:17,560 [classy] Got parameters {'Omega_m': 0.3089625092287251, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:17,560 [classy] Re-using computed results
2023-07-02 10:34:17,560 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.68599715977578}
2023-07-02 10:34:17,561 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:17,561 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4880039345539698, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:17,561 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:17,580 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.28042
2023-07-02 10:34:17,580 [model] Computed derived parameters: {}
2023-07-02 10:34:17,581 [model] Posterior to be computed for parameters {'Omega_m': 0.2759428857891994, 'b1': 0.5504141949045585}
2023-07-02 10:34:17,581 [prior] Evaluating prior at array([0.27594289, 0.55041419])
2023-07-02 10:34:17,581 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:17,581 [model] Got input parameters: {'Omega_m': 0.2759428857891994, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5504141949045585, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:17,581 [classy] Got parameters {'Omega_m': 0.2759428857891994, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:17,581 [classy] Computing new state
2023-07-02 10:34:17,581 [classy] Setting parameters: {'Omega_m': 0.2759428857891994, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:17,625 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.90019267056047}
2023-07-02 10:34:17,625 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:17,627 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.090176
2023-07-02 10:34:17,627 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5504141949045585, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:17,627 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:17,646 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.36109
2023-07-02 10:34:17,647 [model] Computed derived parameters: {}
2023-07-02 10:34:17,647 [model] Posterior to be computed for parameters {'Omega_m': 0.3089625092287251, 'b1': 0.5476331317798704}
2023-07-02 10:34:17,647 [prior] Evaluating prior at array([0.30896251, 0.54763313])
2023-07-02 10:34:17,647 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:17,647 [model] Got input parameters: {'Omega_m': 0.3089625092287251, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5476331317798704, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:17,647 [classy] Got parameters {'Omega_m': 0.3089625092287251, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:17,647 [classy] Re-using computed results
2023-07-02 10:34:17,647 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.68599715977578}
2023-07-02 10:34:17,647 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:17,647 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5476331317798704, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:17,647 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:17,667 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.963049
2023-07-02 10:34:17,667 [model] Computed derived parameters: {}
2023-07-02 10:34:17,668 [model] Posterior to be computed for parameters {'Omega_m': 0.310897316481309, 'b1': 0.4943300864840143}
2023-07-02 10:34:17,668 [prior] Evaluating prior at array([0.31089732, 0.49433009])
2023-07-02 10:34:17,668 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:17,668 [model] Got input parameters: {'Omega_m': 0.310897316481309, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4943300864840143, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:17,668 [classy] Got parameters {'Omega_m': 0.310897316481309, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:17,668 [classy] Computing new state
2023-07-02 10:34:17,668 [classy] Setting parameters: {'Omega_m': 0.310897316481309, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:17,711 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.45148278673094}
2023-07-02 10:34:17,712 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:17,714 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00035737
2023-07-02 10:34:17,714 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4943300864840143, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:17,714 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:17,734 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.34062
2023-07-02 10:34:17,734 [model] Computed derived parameters: {}
2023-07-02 10:34:17,734 [mcmc] New sample, #561:
Omega_m:0.3089625, b1:0.4974345
2023-07-02 10:34:17,734 [model] Posterior to be computed for parameters {'Omega_m': 0.310897316481309, 'b1': 0.5166955998628603}
2023-07-02 10:34:17,734 [prior] Evaluating prior at array([0.31089732, 0.5166956 ])
2023-07-02 10:34:17,734 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:17,734 [model] Got input parameters: {'Omega_m': 0.310897316481309, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5166955998628603, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:17,734 [classy] Got parameters {'Omega_m': 0.310897316481309, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:17,734 [classy] Re-using computed results
2023-07-02 10:34:17,734 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.45148278673094}
2023-07-02 10:34:17,734 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:17,734 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5166955998628603, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:17,734 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:17,754 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.60666
2023-07-02 10:34:17,754 [model] Computed derived parameters: {}
2023-07-02 10:34:17,754 [mcmc] New sample, #562:
Omega_m:0.3108973, b1:0.4943301
2023-07-02 10:34:17,754 [model] Posterior to be computed for parameters {'Omega_m': 0.31882915419358865, 'b1': 0.5039690287981492}
2023-07-02 10:34:17,754 [prior] Evaluating prior at array([0.31882915, 0.50396903])
2023-07-02 10:34:17,754 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:17,754 [model] Got input parameters: {'Omega_m': 0.31882915419358865, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5039690287981492, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:17,754 [classy] Got parameters {'Omega_m': 0.31882915419358865, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:17,754 [classy] Computing new state
2023-07-02 10:34:17,754 [classy] Setting parameters: {'Omega_m': 0.31882915419358865, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:17,798 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.50345214723896}
2023-07-02 10:34:17,798 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:17,800 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0026326
2023-07-02 10:34:17,800 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5039690287981492, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:17,800 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:17,820 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.54788
2023-07-02 10:34:17,820 [model] Computed derived parameters: {}
2023-07-02 10:34:17,820 [mcmc] New sample, #563:
Omega_m:0.3108973, b1:0.5166956
2023-07-02 10:34:17,820 [model] Posterior to be computed for parameters {'Omega_m': 0.31882915419358865, 'b1': 0.47006799039162317}
2023-07-02 10:34:17,820 [prior] Evaluating prior at array([0.31882915, 0.47006799])
2023-07-02 10:34:17,821 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:17,821 [model] Got input parameters: {'Omega_m': 0.31882915419358865, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47006799039162317, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:17,821 [classy] Got parameters {'Omega_m': 0.31882915419358865, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:17,821 [classy] Re-using computed results
2023-07-02 10:34:17,821 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.50345214723896}
2023-07-02 10:34:17,821 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:17,821 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47006799039162317, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:17,821 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:17,840 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.41508
2023-07-02 10:34:17,840 [model] Computed derived parameters: {}
2023-07-02 10:34:17,840 [mcmc] New sample, #564:
Omega_m:0.3188292, b1:0.503969
2023-07-02 10:34:17,840 [model] Posterior to be computed for parameters {'Omega_m': 0.3577674026022992, 'b1': 0.4075918778582508}
2023-07-02 10:34:17,840 [prior] Evaluating prior at array([0.3577674 , 0.40759188])
2023-07-02 10:34:17,840 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:17,840 [model] Got input parameters: {'Omega_m': 0.3577674026022992, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4075918778582508, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:17,840 [classy] Got parameters {'Omega_m': 0.3577674026022992, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:17,840 [classy] Computing new state
2023-07-02 10:34:17,840 [classy] Setting parameters: {'Omega_m': 0.3577674026022992, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:17,884 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.1370105134144}
2023-07-02 10:34:17,884 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:17,886 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.113069
2023-07-02 10:34:17,886 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4075918778582508, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:17,886 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:17,905 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.24626
2023-07-02 10:34:17,905 [model] Computed derived parameters: {}
2023-07-02 10:34:17,906 [model] Posterior to be computed for parameters {'Omega_m': 0.31882915419358865, 'b1': 0.5122573992281159}
2023-07-02 10:34:17,906 [prior] Evaluating prior at array([0.31882915, 0.5122574 ])
2023-07-02 10:34:17,906 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:17,906 [model] Got input parameters: {'Omega_m': 0.31882915419358865, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5122573992281159, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:17,906 [classy] Got parameters {'Omega_m': 0.31882915419358865, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:17,906 [classy] Re-using computed results
2023-07-02 10:34:17,906 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.50345214723896}
2023-07-02 10:34:17,906 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:17,906 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5122573992281159, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:17,906 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:17,925 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.8727
2023-07-02 10:34:17,926 [model] Computed derived parameters: {}
2023-07-02 10:34:17,926 [mcmc] New sample, #565:
Omega_m:0.3188292, b1:0.470068
2023-07-02 10:34:17,926 [model] Posterior to be computed for parameters {'Omega_m': 0.34118478434882804, 'b1': 0.4763879669241002}
2023-07-02 10:34:17,926 [prior] Evaluating prior at array([0.34118478, 0.47638797])
2023-07-02 10:34:17,926 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:17,926 [model] Got input parameters: {'Omega_m': 0.34118478434882804, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4763879669241002, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:17,926 [classy] Got parameters {'Omega_m': 0.34118478434882804, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:17,926 [classy] Computing new state
2023-07-02 10:34:17,926 [classy] Setting parameters: {'Omega_m': 0.34118478434882804, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:17,970 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.94095534834648}
2023-07-02 10:34:17,970 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:17,972 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0473219
2023-07-02 10:34:17,972 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4763879669241002, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:17,972 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:17,991 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.02694
2023-07-02 10:34:17,991 [model] Computed derived parameters: {}
2023-07-02 10:34:17,992 [model] Posterior to be computed for parameters {'Omega_m': 0.31882915419358865, 'b1': 0.47039459427515506}
2023-07-02 10:34:17,992 [prior] Evaluating prior at array([0.31882915, 0.47039459])
2023-07-02 10:34:17,992 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:17,992 [model] Got input parameters: {'Omega_m': 0.31882915419358865, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47039459427515506, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:17,992 [classy] Got parameters {'Omega_m': 0.31882915419358865, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:17,992 [classy] Re-using computed results
2023-07-02 10:34:17,992 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.50345214723896}
2023-07-02 10:34:17,992 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:17,992 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47039459427515506, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:17,992 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:18,011 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.45461
2023-07-02 10:34:18,011 [model] Computed derived parameters: {}
2023-07-02 10:34:18,011 [model] Posterior to be computed for parameters {'Omega_m': 0.3434834197371073, 'b1': 0.47269982456895515}
2023-07-02 10:34:18,011 [prior] Evaluating prior at array([0.34348342, 0.47269982])
2023-07-02 10:34:18,011 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:18,011 [model] Got input parameters: {'Omega_m': 0.3434834197371073, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47269982456895515, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:18,011 [classy] Got parameters {'Omega_m': 0.3434834197371073, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:18,011 [classy] Computing new state
2023-07-02 10:34:18,012 [classy] Setting parameters: {'Omega_m': 0.3434834197371073, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:18,055 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.68615106961454}
2023-07-02 10:34:18,055 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:18,057 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0548763
2023-07-02 10:34:18,057 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47269982456895515, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:18,057 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:18,077 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.68007
2023-07-02 10:34:18,077 [model] Computed derived parameters: {}
2023-07-02 10:34:18,078 [model] Posterior to be computed for parameters {'Omega_m': 0.31882915419358865, 'b1': 0.506043777338209}
2023-07-02 10:34:18,078 [prior] Evaluating prior at array([0.31882915, 0.50604378])
2023-07-02 10:34:18,078 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:18,078 [model] Got input parameters: {'Omega_m': 0.31882915419358865, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.506043777338209, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:18,078 [classy] Got parameters {'Omega_m': 0.31882915419358865, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:18,078 [classy] Re-using computed results
2023-07-02 10:34:18,078 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.50345214723896}
2023-07-02 10:34:18,078 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:18,078 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.506043777338209, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:18,078 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:18,097 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.41524
2023-07-02 10:34:18,097 [model] Computed derived parameters: {}
2023-07-02 10:34:18,098 [mcmc] New sample, #566:
Omega_m:0.3188292, b1:0.5122574
2023-07-02 10:34:18,098 [model] Posterior to be computed for parameters {'Omega_m': 0.33211914511992036, 'b1': 0.4847200916920089}
2023-07-02 10:34:18,098 [prior] Evaluating prior at array([0.33211915, 0.48472009])
2023-07-02 10:34:18,098 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:18,098 [model] Got input parameters: {'Omega_m': 0.33211914511992036, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4847200916920089, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:18,098 [classy] Got parameters {'Omega_m': 0.33211914511992036, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:18,098 [classy] Computing new state
2023-07-02 10:34:18,098 [classy] Setting parameters: {'Omega_m': 0.33211914511992036, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:18,144 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.96127824130795}
2023-07-02 10:34:18,144 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:18,145 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0227367
2023-07-02 10:34:18,146 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4847200916920089, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:18,146 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:18,165 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.767404
2023-07-02 10:34:18,165 [model] Computed derived parameters: {}
2023-07-02 10:34:18,165 [mcmc] New sample, #567:
Omega_m:0.3188292, b1:0.5060438
2023-07-02 10:34:18,166 [model] Posterior to be computed for parameters {'Omega_m': 0.33211914511992036, 'b1': 0.46325562182273516}
2023-07-02 10:34:18,166 [prior] Evaluating prior at array([0.33211915, 0.46325562])
2023-07-02 10:34:18,166 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:18,166 [model] Got input parameters: {'Omega_m': 0.33211914511992036, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46325562182273516, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:18,166 [classy] Got parameters {'Omega_m': 0.33211914511992036, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:18,166 [classy] Re-using computed results
2023-07-02 10:34:18,166 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.96127824130795}
2023-07-02 10:34:18,166 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:18,166 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46325562182273516, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:18,166 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:18,186 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.3271
2023-07-02 10:34:18,186 [model] Computed derived parameters: {}
2023-07-02 10:34:18,186 [mcmc] New sample, #568:
Omega_m:0.3321191, b1:0.4847201
2023-07-02 10:34:18,186 [model] Posterior to be computed for parameters {'Omega_m': 0.34488762013828034, 'b1': 0.44276870433858456}
2023-07-02 10:34:18,186 [prior] Evaluating prior at array([0.34488762, 0.4427687 ])
2023-07-02 10:34:18,186 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:18,186 [model] Got input parameters: {'Omega_m': 0.34488762013828034, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44276870433858456, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:18,186 [classy] Got parameters {'Omega_m': 0.34488762013828034, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:18,186 [classy] Computing new state
2023-07-02 10:34:18,186 [classy] Setting parameters: {'Omega_m': 0.34488762013828034, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:18,230 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.53126424036347}
2023-07-02 10:34:18,230 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:18,232 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0597456
2023-07-02 10:34:18,232 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44276870433858456, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:18,232 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:18,251 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.47869
2023-07-02 10:34:18,251 [model] Computed derived parameters: {}
2023-07-02 10:34:18,252 [model] Posterior to be computed for parameters {'Omega_m': 0.33211914511992036, 'b1': 0.46857828747262825}
2023-07-02 10:34:18,252 [prior] Evaluating prior at array([0.33211915, 0.46857829])
2023-07-02 10:34:18,252 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:18,252 [model] Got input parameters: {'Omega_m': 0.33211914511992036, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46857828747262825, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:18,252 [classy] Got parameters {'Omega_m': 0.33211914511992036, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:18,252 [classy] Re-using computed results
2023-07-02 10:34:18,252 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.96127824130795}
2023-07-02 10:34:18,252 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:18,252 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46857828747262825, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:18,252 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:18,271 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.42556
2023-07-02 10:34:18,271 [model] Computed derived parameters: {}
2023-07-02 10:34:18,272 [mcmc] New sample, #569:
Omega_m:0.3321191, b1:0.4632556
2023-07-02 10:34:18,272 [model] Posterior to be computed for parameters {'Omega_m': 0.28290987132865336, 'b1': 0.5475341792425563}
2023-07-02 10:34:18,272 [prior] Evaluating prior at array([0.28290987, 0.54753418])
2023-07-02 10:34:18,272 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:18,272 [model] Got input parameters: {'Omega_m': 0.28290987132865336, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5475341792425563, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:18,272 [classy] Got parameters {'Omega_m': 0.28290987132865336, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:18,272 [classy] Computing new state
2023-07-02 10:34:18,272 [classy] Setting parameters: {'Omega_m': 0.28290987132865336, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:18,316 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.9759878957657}
2023-07-02 10:34:18,316 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:18,317 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0580564
2023-07-02 10:34:18,317 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5475341792425563, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:18,317 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:18,337 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.09318
2023-07-02 10:34:18,337 [model] Computed derived parameters: {}
2023-07-02 10:34:18,337 [model] Posterior to be computed for parameters {'Omega_m': 0.33211914511992036, 'b1': 0.4105146666016665}
2023-07-02 10:34:18,337 [prior] Evaluating prior at array([0.33211915, 0.41051467])
2023-07-02 10:34:18,338 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:18,338 [model] Got input parameters: {'Omega_m': 0.33211914511992036, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4105146666016665, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:18,338 [classy] Got parameters {'Omega_m': 0.33211914511992036, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:18,338 [classy] Re-using computed results
2023-07-02 10:34:18,338 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.96127824130795}
2023-07-02 10:34:18,338 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:18,338 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4105146666016665, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:18,338 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:18,357 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.48653
2023-07-02 10:34:18,357 [model] Computed derived parameters: {}
2023-07-02 10:34:18,357 [model] Posterior to be computed for parameters {'Omega_m': 0.3691494160591612, 'b1': 0.4091635097441123}
2023-07-02 10:34:18,357 [prior] Evaluating prior at array([0.36914942, 0.40916351])
2023-07-02 10:34:18,357 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:18,357 [model] Got input parameters: {'Omega_m': 0.3691494160591612, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4091635097441123, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:18,357 [classy] Got parameters {'Omega_m': 0.3691494160591612, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:18,357 [classy] Computing new state
2023-07-02 10:34:18,357 [classy] Setting parameters: {'Omega_m': 0.3691494160591612, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:18,402 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.94293474479315}
2023-07-02 10:34:18,402 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:18,404 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.172435
2023-07-02 10:34:18,404 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4091635097441123, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:18,404 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:18,424 [fs_likelihood.fslikelihood] Computed log-likelihood = -10.1906
2023-07-02 10:34:18,424 [model] Computed derived parameters: {}
2023-07-02 10:34:18,424 [model] Posterior to be computed for parameters {'Omega_m': 0.33211914511992036, 'b1': 0.483681501245867}
2023-07-02 10:34:18,424 [prior] Evaluating prior at array([0.33211915, 0.4836815 ])
2023-07-02 10:34:18,424 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:18,424 [model] Got input parameters: {'Omega_m': 0.33211914511992036, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.483681501245867, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:18,424 [classy] Got parameters {'Omega_m': 0.33211914511992036, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:18,424 [classy] Re-using computed results
2023-07-02 10:34:18,424 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.96127824130795}
2023-07-02 10:34:18,424 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:18,424 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.483681501245867, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:18,424 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:18,444 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.853962
2023-07-02 10:34:18,444 [model] Computed derived parameters: {}
2023-07-02 10:34:18,444 [model] Posterior to be computed for parameters {'Omega_m': 0.3345171149089384, 'b1': 0.4647307638547759}
2023-07-02 10:34:18,444 [prior] Evaluating prior at array([0.33451711, 0.46473076])
2023-07-02 10:34:18,444 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:18,444 [model] Got input parameters: {'Omega_m': 0.3345171149089384, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4647307638547759, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:18,444 [classy] Got parameters {'Omega_m': 0.3345171149089384, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:18,444 [classy] Computing new state
2023-07-02 10:34:18,444 [classy] Setting parameters: {'Omega_m': 0.3345171149089384, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:18,488 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.68896567031166}
2023-07-02 10:34:18,488 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:18,490 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0284141
2023-07-02 10:34:18,490 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4647307638547759, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:18,490 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:18,509 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.99169
2023-07-02 10:34:18,509 [model] Computed derived parameters: {}
2023-07-02 10:34:18,509 [mcmc] New sample, #570:
Omega_m:0.3321191, b1:0.4685783
2023-07-02 10:34:18,510 [model] Posterior to be computed for parameters {'Omega_m': 0.3345171149089384, 'b1': 0.4575059592904157}
2023-07-02 10:34:18,510 [prior] Evaluating prior at array([0.33451711, 0.45750596])
2023-07-02 10:34:18,510 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:18,510 [model] Got input parameters: {'Omega_m': 0.3345171149089384, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4575059592904157, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:18,510 [classy] Got parameters {'Omega_m': 0.3345171149089384, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:18,510 [classy] Re-using computed results
2023-07-02 10:34:18,510 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.68896567031166}
2023-07-02 10:34:18,510 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:18,510 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4575059592904157, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:18,510 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:18,530 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.839723
2023-07-02 10:34:18,530 [model] Computed derived parameters: {}
2023-07-02 10:34:18,530 [model] Posterior to be computed for parameters {'Omega_m': 0.3251680275444227, 'b1': 0.4797313008111108}
2023-07-02 10:34:18,530 [prior] Evaluating prior at array([0.32516803, 0.4797313 ])
2023-07-02 10:34:18,530 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:18,530 [model] Got input parameters: {'Omega_m': 0.3251680275444227, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4797313008111108, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:18,530 [classy] Got parameters {'Omega_m': 0.3251680275444227, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:18,530 [classy] Computing new state
2023-07-02 10:34:18,530 [classy] Setting parameters: {'Omega_m': 0.3251680275444227, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:18,574 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.76083460052172}
2023-07-02 10:34:18,574 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:18,576 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00976458
2023-07-02 10:34:18,576 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4797313008111108, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:18,576 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:18,596 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.37746
2023-07-02 10:34:18,596 [model] Computed derived parameters: {}
2023-07-02 10:34:18,596 [mcmc] New sample, #571:
Omega_m:0.3345171, b1:0.4647308
2023-07-02 10:34:18,596 [model] Posterior to be computed for parameters {'Omega_m': 0.3251680275444227, 'b1': 0.47941505850622906}
2023-07-02 10:34:18,596 [prior] Evaluating prior at array([0.32516803, 0.47941506])
2023-07-02 10:34:18,596 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:18,596 [model] Got input parameters: {'Omega_m': 0.3251680275444227, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47941505850622906, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:18,596 [classy] Got parameters {'Omega_m': 0.3251680275444227, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:18,596 [classy] Re-using computed results
2023-07-02 10:34:18,596 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.76083460052172}
2023-07-02 10:34:18,596 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:18,596 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47941505850622906, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:18,596 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:18,616 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.37347
2023-07-02 10:34:18,616 [model] Computed derived parameters: {}
2023-07-02 10:34:18,616 [mcmc] New sample, #572:
Omega_m:0.325168, b1:0.4797313
2023-07-02 10:34:18,616 [model] Posterior to be computed for parameters {'Omega_m': 0.30042496489678194, 'b1': 0.519115107418765}
2023-07-02 10:34:18,616 [prior] Evaluating prior at array([0.30042496, 0.51911511])
2023-07-02 10:34:18,616 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:18,616 [model] Got input parameters: {'Omega_m': 0.30042496489678194, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.519115107418765, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:18,616 [classy] Got parameters {'Omega_m': 0.30042496489678194, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:18,616 [classy] Computing new state
2023-07-02 10:34:18,616 [classy] Setting parameters: {'Omega_m': 0.30042496489678194, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:18,661 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.73648349023696}
2023-07-02 10:34:18,661 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:18,662 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00939399
2023-07-02 10:34:18,663 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.519115107418765, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:18,663 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:18,682 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.46589
2023-07-02 10:34:18,682 [model] Computed derived parameters: {}
2023-07-02 10:34:18,683 [model] Posterior to be computed for parameters {'Omega_m': 0.3251680275444227, 'b1': 0.46384885979996043}
2023-07-02 10:34:18,683 [prior] Evaluating prior at array([0.32516803, 0.46384886])
2023-07-02 10:34:18,683 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:18,683 [model] Got input parameters: {'Omega_m': 0.3251680275444227, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46384885979996043, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:18,683 [classy] Got parameters {'Omega_m': 0.3251680275444227, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:18,683 [classy] Re-using computed results
2023-07-02 10:34:18,683 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.76083460052172}
2023-07-02 10:34:18,683 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:18,683 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46384885979996043, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:18,683 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:18,702 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.51943
2023-07-02 10:34:18,702 [model] Computed derived parameters: {}
2023-07-02 10:34:18,702 [model] Posterior to be computed for parameters {'Omega_m': 0.3225648137071411, 'b1': 0.48359189458111673}
2023-07-02 10:34:18,702 [prior] Evaluating prior at array([0.32256481, 0.48359189])
2023-07-02 10:34:18,703 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:18,703 [model] Got input parameters: {'Omega_m': 0.3225648137071411, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48359189458111673, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:18,703 [classy] Got parameters {'Omega_m': 0.3225648137071411, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:18,703 [classy] Computing new state
2023-07-02 10:34:18,703 [classy] Setting parameters: {'Omega_m': 0.3225648137071411, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:18,746 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.06422836147004}
2023-07-02 10:34:18,746 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:18,748 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00628066
2023-07-02 10:34:18,748 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48359189458111673, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:18,748 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:18,767 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.60562
2023-07-02 10:34:18,768 [model] Computed derived parameters: {}
2023-07-02 10:34:18,768 [mcmc] New sample, #573:
Omega_m:0.325168, b1:0.4794151
2023-07-02 10:34:18,768 [model] Posterior to be computed for parameters {'Omega_m': 0.3225648137071411, 'b1': 0.46448513800977925}
2023-07-02 10:34:18,768 [prior] Evaluating prior at array([0.32256481, 0.46448514])
2023-07-02 10:34:18,768 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:18,768 [model] Got input parameters: {'Omega_m': 0.3225648137071411, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46448513800977925, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:18,768 [classy] Got parameters {'Omega_m': 0.3225648137071411, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:18,768 [classy] Re-using computed results
2023-07-02 10:34:18,768 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.06422836147004}
2023-07-02 10:34:18,768 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:18,768 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46448513800977925, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:18,768 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:18,788 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.32957
2023-07-02 10:34:18,788 [model] Computed derived parameters: {}
2023-07-02 10:34:18,788 [model] Posterior to be computed for parameters {'Omega_m': 0.3423149098023159, 'b1': 0.45190302113114844}
2023-07-02 10:34:18,788 [prior] Evaluating prior at array([0.34231491, 0.45190302])
2023-07-02 10:34:18,788 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:18,788 [model] Got input parameters: {'Omega_m': 0.3423149098023159, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45190302113114844, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:18,788 [classy] Got parameters {'Omega_m': 0.3423149098023159, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:18,788 [classy] Computing new state
2023-07-02 10:34:18,788 [classy] Setting parameters: {'Omega_m': 0.3423149098023159, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:18,832 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.81548503423645}
2023-07-02 10:34:18,832 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:18,834 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.050971
2023-07-02 10:34:18,834 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45190302113114844, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:18,834 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:18,854 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.762956
2023-07-02 10:34:18,854 [model] Computed derived parameters: {}
2023-07-02 10:34:18,854 [model] Posterior to be computed for parameters {'Omega_m': 0.3225648137071411, 'b1': 0.4721307328033743}
2023-07-02 10:34:18,854 [prior] Evaluating prior at array([0.32256481, 0.47213073])
2023-07-02 10:34:18,854 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:18,854 [model] Got input parameters: {'Omega_m': 0.3225648137071411, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4721307328033743, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:18,854 [classy] Got parameters {'Omega_m': 0.3225648137071411, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:18,854 [classy] Re-using computed results
2023-07-02 10:34:18,854 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.06422836147004}
2023-07-02 10:34:18,854 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:18,854 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4721307328033743, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:18,854 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:18,873 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.06868
2023-07-02 10:34:18,873 [model] Computed derived parameters: {}
2023-07-02 10:34:18,874 [model] Posterior to be computed for parameters {'Omega_m': 0.33285293017405154, 'b1': 0.4670846928344826}
2023-07-02 10:34:18,874 [prior] Evaluating prior at array([0.33285293, 0.46708469])
2023-07-02 10:34:18,874 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:18,874 [model] Got input parameters: {'Omega_m': 0.33285293017405154, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4670846928344826, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:18,874 [classy] Got parameters {'Omega_m': 0.33285293017405154, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:18,874 [classy] Computing new state
2023-07-02 10:34:18,874 [classy] Setting parameters: {'Omega_m': 0.33285293017405154, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:18,918 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.87776024357615}
2023-07-02 10:34:18,918 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:18,919 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0244097
2023-07-02 10:34:18,920 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4670846928344826, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:18,920 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:18,939 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.29705
2023-07-02 10:34:18,940 [model] Computed derived parameters: {}
2023-07-02 10:34:18,940 [model] Posterior to be computed for parameters {'Omega_m': 0.3225648137071411, 'b1': 0.5220972866468442}
2023-07-02 10:34:18,940 [prior] Evaluating prior at array([0.32256481, 0.52209729])
2023-07-02 10:34:18,940 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:18,940 [model] Got input parameters: {'Omega_m': 0.3225648137071411, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5220972866468442, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:18,940 [classy] Got parameters {'Omega_m': 0.3225648137071411, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:18,940 [classy] Re-using computed results
2023-07-02 10:34:18,940 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.06422836147004}
2023-07-02 10:34:18,940 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:18,940 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5220972866468442, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:18,940 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:18,959 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.910166
2023-07-02 10:34:18,959 [model] Computed derived parameters: {}
2023-07-02 10:34:18,959 [model] Posterior to be computed for parameters {'Omega_m': 0.3222685813322882, 'b1': 0.48406719709069745}
2023-07-02 10:34:18,959 [prior] Evaluating prior at array([0.32226858, 0.4840672 ])
2023-07-02 10:34:18,959 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:18,960 [model] Got input parameters: {'Omega_m': 0.3222685813322882, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48406719709069745, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:18,960 [classy] Got parameters {'Omega_m': 0.3222685813322882, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:18,960 [classy] Computing new state
2023-07-02 10:34:18,960 [classy] Setting parameters: {'Omega_m': 0.3222685813322882, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:19,004 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.09889739921127}
2023-07-02 10:34:19,004 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:19,006 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00593268
2023-07-02 10:34:19,006 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48406719709069745, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,006 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:19,026 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.62759
2023-07-02 10:34:19,026 [model] Computed derived parameters: {}
2023-07-02 10:34:19,026 [mcmc] New sample, #574:
Omega_m:0.3225648, b1:0.4835919
2023-07-02 10:34:19,026 [model] Posterior to be computed for parameters {'Omega_m': 0.3222685813322882, 'b1': 0.5017720279759543}
2023-07-02 10:34:19,026 [prior] Evaluating prior at array([0.32226858, 0.50177203])
2023-07-02 10:34:19,026 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:19,026 [model] Got input parameters: {'Omega_m': 0.3222685813322882, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5017720279759543, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,026 [classy] Got parameters {'Omega_m': 0.3222685813322882, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:19,026 [classy] Re-using computed results
2023-07-02 10:34:19,026 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.09889739921127}
2023-07-02 10:34:19,026 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:19,026 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5017720279759543, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,026 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:19,046 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.06521
2023-07-02 10:34:19,046 [model] Computed derived parameters: {}
2023-07-02 10:34:19,046 [model] Posterior to be computed for parameters {'Omega_m': 0.3327163516282342, 'b1': 0.46730383203428855}
2023-07-02 10:34:19,046 [prior] Evaluating prior at array([0.33271635, 0.46730383])
2023-07-02 10:34:19,046 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:19,046 [model] Got input parameters: {'Omega_m': 0.3327163516282342, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46730383203428855, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,046 [classy] Got parameters {'Omega_m': 0.3327163516282342, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:19,046 [classy] Computing new state
2023-07-02 10:34:19,046 [classy] Setting parameters: {'Omega_m': 0.3327163516282342, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:19,090 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.89329414169708}
2023-07-02 10:34:19,090 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:19,092 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0240939
2023-07-02 10:34:19,092 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46730383203428855, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,093 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:19,112 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.32105
2023-07-02 10:34:19,112 [model] Computed derived parameters: {}
2023-07-02 10:34:19,112 [model] Posterior to be computed for parameters {'Omega_m': 0.3222685813322882, 'b1': 0.39976009914808924}
2023-07-02 10:34:19,112 [prior] Evaluating prior at array([0.32226858, 0.3997601 ])
2023-07-02 10:34:19,112 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:19,112 [model] Got input parameters: {'Omega_m': 0.3222685813322882, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.39976009914808924, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,112 [classy] Got parameters {'Omega_m': 0.3222685813322882, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:19,112 [classy] Re-using computed results
2023-07-02 10:34:19,112 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.09889739921127}
2023-07-02 10:34:19,112 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:19,112 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.39976009914808924, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,112 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:19,134 [fs_likelihood.fslikelihood] Computed log-likelihood = -16.3102
2023-07-02 10:34:19,134 [model] Computed derived parameters: {}
2023-07-02 10:34:19,134 [model] Posterior to be computed for parameters {'Omega_m': 0.3314000913515809, 'b1': 0.4694157612691179}
2023-07-02 10:34:19,134 [prior] Evaluating prior at array([0.33140009, 0.46941576])
2023-07-02 10:34:19,134 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:19,134 [model] Got input parameters: {'Omega_m': 0.3314000913515809, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4694157612691179, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,134 [classy] Got parameters {'Omega_m': 0.3314000913515809, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:19,134 [classy] Computing new state
2023-07-02 10:34:19,134 [classy] Setting parameters: {'Omega_m': 0.3314000913515809, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:19,178 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.0432780066275}
2023-07-02 10:34:19,178 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:19,180 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0211528
2023-07-02 10:34:19,180 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4694157612691179, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,180 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:19,200 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.54361
2023-07-02 10:34:19,200 [model] Computed derived parameters: {}
2023-07-02 10:34:19,200 [model] Posterior to be computed for parameters {'Omega_m': 0.3222685813322882, 'b1': 0.4605219610957813}
2023-07-02 10:34:19,200 [prior] Evaluating prior at array([0.32226858, 0.46052196])
2023-07-02 10:34:19,200 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:19,201 [model] Got input parameters: {'Omega_m': 0.3222685813322882, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4605219610957813, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,201 [classy] Got parameters {'Omega_m': 0.3222685813322882, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:19,201 [classy] Re-using computed results
2023-07-02 10:34:19,201 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.09889739921127}
2023-07-02 10:34:19,201 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:19,201 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4605219610957813, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,201 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:19,220 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.778907
2023-07-02 10:34:19,220 [model] Computed derived parameters: {}
2023-07-02 10:34:19,220 [model] Posterior to be computed for parameters {'Omega_m': 0.309568902714246, 'b1': 0.5044437312930161}
2023-07-02 10:34:19,220 [prior] Evaluating prior at array([0.3095689 , 0.50444373])
2023-07-02 10:34:19,220 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:19,220 [model] Got input parameters: {'Omega_m': 0.309568902714246, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5044437312930161, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,220 [classy] Got parameters {'Omega_m': 0.309568902714246, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:19,220 [classy] Computing new state
2023-07-02 10:34:19,220 [classy] Setting parameters: {'Omega_m': 0.309568902714246, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:19,264 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.61235747132253}
2023-07-02 10:34:19,264 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:19,266 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000727312
2023-07-02 10:34:19,266 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5044437312930161, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,266 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:19,286 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.65604
2023-07-02 10:34:19,286 [model] Computed derived parameters: {}
2023-07-02 10:34:19,286 [mcmc] New sample, #575:
Omega_m:0.3222686, b1:0.4840672
2023-07-02 10:34:19,286 [model] Posterior to be computed for parameters {'Omega_m': 0.309568902714246, 'b1': 0.5041431400491372}
2023-07-02 10:34:19,286 [prior] Evaluating prior at array([0.3095689 , 0.50414314])
2023-07-02 10:34:19,286 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:19,286 [model] Got input parameters: {'Omega_m': 0.309568902714246, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5041431400491372, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,286 [classy] Got parameters {'Omega_m': 0.309568902714246, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:19,286 [classy] Re-using computed results
2023-07-02 10:34:19,286 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.61235747132253}
2023-07-02 10:34:19,286 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:19,286 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5041431400491372, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,286 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:19,306 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.64659
2023-07-02 10:34:19,306 [model] Computed derived parameters: {}
2023-07-02 10:34:19,306 [mcmc] New sample, #576:
Omega_m:0.3095689, b1:0.5044437
2023-07-02 10:34:19,306 [model] Posterior to be computed for parameters {'Omega_m': 0.31630045365259457, 'b1': 0.49334241964861925}
2023-07-02 10:34:19,306 [prior] Evaluating prior at array([0.31630045, 0.49334242])
2023-07-02 10:34:19,306 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:19,306 [model] Got input parameters: {'Omega_m': 0.31630045365259457, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49334241964861925, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,306 [classy] Got parameters {'Omega_m': 0.31630045365259457, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:19,306 [classy] Computing new state
2023-07-02 10:34:19,306 [classy] Setting parameters: {'Omega_m': 0.31630045365259457, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:19,350 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.80337053060526}
2023-07-02 10:34:19,350 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:19,352 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00108719
2023-07-02 10:34:19,352 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49334241964861925, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,352 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:19,371 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.86189
2023-07-02 10:34:19,371 [model] Computed derived parameters: {}
2023-07-02 10:34:19,371 [mcmc] New sample, #577:
Omega_m:0.3095689, b1:0.5041431
2023-07-02 10:34:19,372 [model] Posterior to be computed for parameters {'Omega_m': 0.31630045365259457, 'b1': 0.496674452613616}
2023-07-02 10:34:19,372 [prior] Evaluating prior at array([0.31630045, 0.49667445])
2023-07-02 10:34:19,372 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:19,372 [model] Got input parameters: {'Omega_m': 0.31630045365259457, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.496674452613616, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,372 [classy] Got parameters {'Omega_m': 0.31630045365259457, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:19,372 [classy] Re-using computed results
2023-07-02 10:34:19,372 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.80337053060526}
2023-07-02 10:34:19,372 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:19,372 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.496674452613616, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,372 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:19,392 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.91521
2023-07-02 10:34:19,392 [model] Computed derived parameters: {}
2023-07-02 10:34:19,392 [mcmc] New sample, #578:
Omega_m:0.3163005, b1:0.4933424
2023-07-02 10:34:19,392 [model] Posterior to be computed for parameters {'Omega_m': 0.33061656367639586, 'b1': 0.4737043669667468}
2023-07-02 10:34:19,392 [prior] Evaluating prior at array([0.33061656, 0.47370437])
2023-07-02 10:34:19,392 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:19,392 [model] Got input parameters: {'Omega_m': 0.33061656367639586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4737043669667468, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,392 [classy] Got parameters {'Omega_m': 0.33061656367639586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:19,392 [classy] Computing new state
2023-07-02 10:34:19,392 [classy] Setting parameters: {'Omega_m': 0.33061656367639586, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:19,436 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.13281407870255}
2023-07-02 10:34:19,436 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:19,438 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0194896
2023-07-02 10:34:19,438 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4737043669667468, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,438 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:19,458 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.66588
2023-07-02 10:34:19,458 [model] Computed derived parameters: {}
2023-07-02 10:34:19,458 [model] Posterior to be computed for parameters {'Omega_m': 0.31630045365259457, 'b1': 0.48135175419687165}
2023-07-02 10:34:19,458 [prior] Evaluating prior at array([0.31630045, 0.48135175])
2023-07-02 10:34:19,458 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:19,458 [model] Got input parameters: {'Omega_m': 0.31630045365259457, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48135175419687165, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,458 [classy] Got parameters {'Omega_m': 0.31630045365259457, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:19,458 [classy] Re-using computed results
2023-07-02 10:34:19,458 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.80337053060526}
2023-07-02 10:34:19,458 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:19,458 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48135175419687165, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,458 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:19,477 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.18525
2023-07-02 10:34:19,477 [model] Computed derived parameters: {}
2023-07-02 10:34:19,478 [mcmc] New sample, #579:
Omega_m:0.3163005, b1:0.4966745
2023-07-02 10:34:19,478 [model] Posterior to be computed for parameters {'Omega_m': 0.32207127041761824, 'b1': 0.4720925242018101}
2023-07-02 10:34:19,478 [prior] Evaluating prior at array([0.32207127, 0.47209252])
2023-07-02 10:34:19,478 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:19,478 [model] Got input parameters: {'Omega_m': 0.32207127041761824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4720925242018101, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,478 [classy] Got parameters {'Omega_m': 0.32207127041761824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:19,478 [classy] Computing new state
2023-07-02 10:34:19,478 [classy] Setting parameters: {'Omega_m': 0.32207127041761824, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:19,522 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.12199829578879}
2023-07-02 10:34:19,523 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:19,524 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00570662
2023-07-02 10:34:19,524 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4720925242018101, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,524 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:19,544 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.03267
2023-07-02 10:34:19,544 [model] Computed derived parameters: {}
2023-07-02 10:34:19,544 [mcmc] New sample, #580:
Omega_m:0.3163005, b1:0.4813518
2023-07-02 10:34:19,544 [model] Posterior to be computed for parameters {'Omega_m': 0.32207127041761824, 'b1': 0.44774432278508847}
2023-07-02 10:34:19,544 [prior] Evaluating prior at array([0.32207127, 0.44774432])
2023-07-02 10:34:19,544 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:19,545 [model] Got input parameters: {'Omega_m': 0.32207127041761824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44774432278508847, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,545 [classy] Got parameters {'Omega_m': 0.32207127041761824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:19,545 [classy] Re-using computed results
2023-07-02 10:34:19,545 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.12199829578879}
2023-07-02 10:34:19,545 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:19,545 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44774432278508847, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,545 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:19,564 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.45478
2023-07-02 10:34:19,564 [model] Computed derived parameters: {}
2023-07-02 10:34:19,564 [model] Posterior to be computed for parameters {'Omega_m': 0.3402449266571032, 'b1': 0.4429330360696503}
2023-07-02 10:34:19,564 [prior] Evaluating prior at array([0.34024493, 0.44293304])
2023-07-02 10:34:19,564 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:19,564 [model] Got input parameters: {'Omega_m': 0.3402449266571032, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4429330360696503, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,564 [classy] Got parameters {'Omega_m': 0.3402449266571032, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:19,564 [classy] Computing new state
2023-07-02 10:34:19,564 [classy] Setting parameters: {'Omega_m': 0.3402449266571032, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:19,609 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.0455863290492}
2023-07-02 10:34:19,609 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:19,611 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0443841
2023-07-02 10:34:19,611 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4429330360696503, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,611 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:19,630 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.620192
2023-07-02 10:34:19,630 [model] Computed derived parameters: {}
2023-07-02 10:34:19,630 [model] Posterior to be computed for parameters {'Omega_m': 0.32207127041761824, 'b1': 0.5123821009017084}
2023-07-02 10:34:19,630 [prior] Evaluating prior at array([0.32207127, 0.5123821 ])
2023-07-02 10:34:19,630 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:19,630 [model] Got input parameters: {'Omega_m': 0.32207127041761824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5123821009017084, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,630 [classy] Got parameters {'Omega_m': 0.32207127041761824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:19,630 [classy] Re-using computed results
2023-07-02 10:34:19,631 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.12199829578879}
2023-07-02 10:34:19,631 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:19,631 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5123821009017084, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,631 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:19,650 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.947895
2023-07-02 10:34:19,650 [model] Computed derived parameters: {}
2023-07-02 10:34:19,650 [mcmc] New sample, #581:
Omega_m:0.3220713, b1:0.4720925
2023-07-02 10:34:19,651 [model] Posterior to be computed for parameters {'Omega_m': 0.3208101312033207, 'b1': 0.514405588826632}
2023-07-02 10:34:19,651 [prior] Evaluating prior at array([0.32081013, 0.51440559])
2023-07-02 10:34:19,651 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:19,651 [model] Got input parameters: {'Omega_m': 0.3208101312033207, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.514405588826632, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,651 [classy] Got parameters {'Omega_m': 0.3208101312033207, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:19,651 [classy] Computing new state
2023-07-02 10:34:19,651 [classy] Setting parameters: {'Omega_m': 0.3208101312033207, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:19,695 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.26997085172243}
2023-07-02 10:34:19,695 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:19,697 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00436657
2023-07-02 10:34:19,697 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.514405588826632, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,697 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:19,716 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.07177
2023-07-02 10:34:19,716 [model] Computed derived parameters: {}
2023-07-02 10:34:19,716 [mcmc] New sample, #582:
Omega_m:0.3220713, b1:0.5123821
2023-07-02 10:34:19,716 [model] Posterior to be computed for parameters {'Omega_m': 0.3208101312033207, 'b1': 0.49572030167286996}
2023-07-02 10:34:19,716 [prior] Evaluating prior at array([0.32081013, 0.4957203 ])
2023-07-02 10:34:19,716 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:19,716 [model] Got input parameters: {'Omega_m': 0.3208101312033207, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49572030167286996, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,716 [classy] Got parameters {'Omega_m': 0.3208101312033207, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:19,716 [classy] Re-using computed results
2023-07-02 10:34:19,716 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.26997085172243}
2023-07-02 10:34:19,716 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:19,716 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49572030167286996, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,716 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:19,736 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.65796
2023-07-02 10:34:19,736 [model] Computed derived parameters: {}
2023-07-02 10:34:19,736 [mcmc] New sample, #583:
Omega_m:0.3208101, b1:0.5144056
2023-07-02 10:34:19,736 [model] Posterior to be computed for parameters {'Omega_m': 0.32269572483744435, 'b1': 0.49269488155532387}
2023-07-02 10:34:19,736 [prior] Evaluating prior at array([0.32269572, 0.49269488])
2023-07-02 10:34:19,736 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:19,736 [model] Got input parameters: {'Omega_m': 0.32269572483744435, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49269488155532387, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,736 [classy] Got parameters {'Omega_m': 0.32269572483744435, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:19,736 [classy] Computing new state
2023-07-02 10:34:19,736 [classy] Setting parameters: {'Omega_m': 0.32269572483744435, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:19,780 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.04892208524046}
2023-07-02 10:34:19,780 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:19,782 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00643749
2023-07-02 10:34:19,782 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49269488155532387, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,782 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:19,803 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.51118
2023-07-02 10:34:19,803 [model] Computed derived parameters: {}
2023-07-02 10:34:19,803 [model] Posterior to be computed for parameters {'Omega_m': 0.3208101312033207, 'b1': 0.48747975598648347}
2023-07-02 10:34:19,803 [prior] Evaluating prior at array([0.32081013, 0.48747976])
2023-07-02 10:34:19,803 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:19,803 [model] Got input parameters: {'Omega_m': 0.3208101312033207, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48747975598648347, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,803 [classy] Got parameters {'Omega_m': 0.3208101312033207, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:19,803 [classy] Re-using computed results
2023-07-02 10:34:19,803 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.26997085172243}
2023-07-02 10:34:19,803 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:19,803 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48747975598648347, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,803 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:19,822 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.73881
2023-07-02 10:34:19,822 [model] Computed derived parameters: {}
2023-07-02 10:34:19,823 [mcmc] New sample, #584:
Omega_m:0.3208101, b1:0.4957203
2023-07-02 10:34:19,823 [model] Posterior to be computed for parameters {'Omega_m': 0.3544554814046757, 'b1': 0.43349605689090864}
2023-07-02 10:34:19,823 [prior] Evaluating prior at array([0.35445548, 0.43349606])
2023-07-02 10:34:19,823 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:19,823 [model] Got input parameters: {'Omega_m': 0.3544554814046757, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.43349605689090864, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,823 [classy] Got parameters {'Omega_m': 0.3544554814046757, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:19,823 [classy] Computing new state
2023-07-02 10:34:19,823 [classy] Setting parameters: {'Omega_m': 0.3544554814046757, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:19,869 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.49108284724593}
2023-07-02 10:34:19,870 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:19,871 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.097902
2023-07-02 10:34:19,871 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.43349605689090864, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,871 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:19,890 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.46302
2023-07-02 10:34:19,890 [model] Computed derived parameters: {}
2023-07-02 10:34:19,891 [model] Posterior to be computed for parameters {'Omega_m': 0.3208101312033207, 'b1': 0.5548511060510317}
2023-07-02 10:34:19,891 [prior] Evaluating prior at array([0.32081013, 0.55485111])
2023-07-02 10:34:19,891 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:19,891 [model] Got input parameters: {'Omega_m': 0.3208101312033207, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5548511060510317, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,891 [classy] Got parameters {'Omega_m': 0.3208101312033207, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:19,891 [classy] Re-using computed results
2023-07-02 10:34:19,891 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.26997085172243}
2023-07-02 10:34:19,891 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:19,891 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5548511060510317, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,891 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:19,911 [fs_likelihood.fslikelihood] Computed log-likelihood = -9.48431
2023-07-02 10:34:19,911 [model] Computed derived parameters: {}
2023-07-02 10:34:19,911 [model] Posterior to be computed for parameters {'Omega_m': 0.34458551923748154, 'b1': 0.4493323333609053}
2023-07-02 10:34:19,911 [prior] Evaluating prior at array([0.34458552, 0.44933233])
2023-07-02 10:34:19,911 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:19,911 [model] Got input parameters: {'Omega_m': 0.34458551923748154, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4493323333609053, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,911 [classy] Got parameters {'Omega_m': 0.34458551923748154, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:19,911 [classy] Computing new state
2023-07-02 10:34:19,911 [classy] Setting parameters: {'Omega_m': 0.34458551923748154, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:19,958 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.56453323800775}
2023-07-02 10:34:19,958 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:19,960 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0586822
2023-07-02 10:34:19,960 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4493323333609053, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,960 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:19,979 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.37911
2023-07-02 10:34:19,979 [model] Computed derived parameters: {}
2023-07-02 10:34:19,979 [model] Posterior to be computed for parameters {'Omega_m': 0.3208101312033207, 'b1': 0.48525705618702586}
2023-07-02 10:34:19,979 [prior] Evaluating prior at array([0.32081013, 0.48525706])
2023-07-02 10:34:19,980 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:19,980 [model] Got input parameters: {'Omega_m': 0.3208101312033207, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48525705618702586, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,980 [classy] Got parameters {'Omega_m': 0.3208101312033207, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:19,980 [classy] Re-using computed results
2023-07-02 10:34:19,980 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.26997085172243}
2023-07-02 10:34:19,980 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:19,980 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48525705618702586, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:19,980 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:20,000 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.69764
2023-07-02 10:34:20,000 [model] Computed derived parameters: {}
2023-07-02 10:34:20,000 [mcmc] New sample, #585:
Omega_m:0.3208101, b1:0.4874798
2023-07-02 10:34:20,000 [model] Posterior to be computed for parameters {'Omega_m': 0.33698350134927635, 'b1': 0.4593070113191481}
2023-07-02 10:34:20,000 [prior] Evaluating prior at array([0.3369835 , 0.45930701])
2023-07-02 10:34:20,000 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:20,000 [model] Got input parameters: {'Omega_m': 0.33698350134927635, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4593070113191481, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:20,000 [classy] Got parameters {'Omega_m': 0.33698350134927635, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:20,000 [classy] Computing new state
2023-07-02 10:34:20,000 [classy] Setting parameters: {'Omega_m': 0.33698350134927635, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:20,047 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.41071656787383}
2023-07-02 10:34:20,047 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:20,048 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0348792
2023-07-02 10:34:20,048 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4593070113191481, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:20,049 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:20,068 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.488039
2023-07-02 10:34:20,068 [model] Computed derived parameters: {}
2023-07-02 10:34:20,068 [model] Posterior to be computed for parameters {'Omega_m': 0.3208101312033207, 'b1': 0.489559830250117}
2023-07-02 10:34:20,068 [prior] Evaluating prior at array([0.32081013, 0.48955983])
2023-07-02 10:34:20,068 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:20,068 [model] Got input parameters: {'Omega_m': 0.3208101312033207, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.489559830250117, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:20,068 [classy] Got parameters {'Omega_m': 0.3208101312033207, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:20,068 [classy] Re-using computed results
2023-07-02 10:34:20,068 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.26997085172243}
2023-07-02 10:34:20,068 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:20,068 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.489559830250117, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:20,068 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:20,088 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.75326
2023-07-02 10:34:20,088 [model] Computed derived parameters: {}
2023-07-02 10:34:20,088 [mcmc] New sample, #586:
Omega_m:0.3208101, b1:0.4852571
2023-07-02 10:34:20,088 [model] Posterior to be computed for parameters {'Omega_m': 0.33733528308750954, 'b1': 0.4630453543571363}
2023-07-02 10:34:20,088 [prior] Evaluating prior at array([0.33733528, 0.46304535])
2023-07-02 10:34:20,088 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:20,088 [model] Got input parameters: {'Omega_m': 0.33733528308750954, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4630453543571363, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:20,088 [classy] Got parameters {'Omega_m': 0.33733528308750954, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:20,088 [classy] Computing new state
2023-07-02 10:34:20,088 [classy] Setting parameters: {'Omega_m': 0.33733528308750954, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:20,137 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.37117775021488}
2023-07-02 10:34:20,137 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:20,139 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0358525
2023-07-02 10:34:20,139 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4630453543571363, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:20,139 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:20,159 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.38923
2023-07-02 10:34:20,159 [model] Computed derived parameters: {}
2023-07-02 10:34:20,159 [model] Posterior to be computed for parameters {'Omega_m': 0.3208101312033207, 'b1': 0.539621897224631}
2023-07-02 10:34:20,160 [prior] Evaluating prior at array([0.32081013, 0.5396219 ])
2023-07-02 10:34:20,160 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:20,160 [model] Got input parameters: {'Omega_m': 0.3208101312033207, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.539621897224631, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:20,160 [classy] Got parameters {'Omega_m': 0.3208101312033207, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:20,160 [classy] Re-using computed results
2023-07-02 10:34:20,160 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.26997085172243}
2023-07-02 10:34:20,160 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:20,160 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.539621897224631, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:20,160 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:20,180 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.31746
2023-07-02 10:34:20,180 [model] Computed derived parameters: {}
2023-07-02 10:34:20,180 [model] Posterior to be computed for parameters {'Omega_m': 0.3676346496046627, 'b1': 0.4144302596988956}
2023-07-02 10:34:20,180 [prior] Evaluating prior at array([0.36763465, 0.41443026])
2023-07-02 10:34:20,180 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:20,180 [model] Got input parameters: {'Omega_m': 0.3676346496046627, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4144302596988956, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:20,180 [classy] Got parameters {'Omega_m': 0.3676346496046627, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:20,180 [classy] Computing new state
2023-07-02 10:34:20,180 [classy] Setting parameters: {'Omega_m': 0.3676346496046627, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:20,227 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.09986397891416}
2023-07-02 10:34:20,227 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:20,229 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.163906
2023-07-02 10:34:20,229 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4144302596988956, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:20,229 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:20,248 [fs_likelihood.fslikelihood] Computed log-likelihood = -9.6609
2023-07-02 10:34:20,248 [model] Computed derived parameters: {}
2023-07-02 10:34:20,248 [model] Posterior to be computed for parameters {'Omega_m': 0.3208101312033207, 'b1': 0.5313958150440904}
2023-07-02 10:34:20,248 [prior] Evaluating prior at array([0.32081013, 0.53139582])
2023-07-02 10:34:20,249 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:20,249 [model] Got input parameters: {'Omega_m': 0.3208101312033207, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5313958150440904, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:20,249 [classy] Got parameters {'Omega_m': 0.3208101312033207, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:20,249 [classy] Re-using computed results
2023-07-02 10:34:20,249 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.26997085172243}
2023-07-02 10:34:20,249 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:20,249 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5313958150440904, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:20,249 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:20,268 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.13505
2023-07-02 10:34:20,268 [model] Computed derived parameters: {}
2023-07-02 10:34:20,268 [model] Posterior to be computed for parameters {'Omega_m': 0.3289026332147191, 'b1': 0.4765754745843504}
2023-07-02 10:34:20,269 [prior] Evaluating prior at array([0.32890263, 0.47657547])
2023-07-02 10:34:20,269 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:20,269 [model] Got input parameters: {'Omega_m': 0.3289026332147191, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4765754745843504, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:20,269 [classy] Got parameters {'Omega_m': 0.3289026332147191, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:20,269 [classy] Computing new state
2023-07-02 10:34:20,269 [classy] Setting parameters: {'Omega_m': 0.3289026332147191, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:20,315 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.32934705197334}
2023-07-02 10:34:20,315 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:20,317 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0160814
2023-07-02 10:34:20,317 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4765754745843504, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:20,317 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:20,336 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.92367
2023-07-02 10:34:20,336 [model] Computed derived parameters: {}
2023-07-02 10:34:20,337 [mcmc] New sample, #587:
Omega_m:0.3208101, b1:0.4895598
2023-07-02 10:34:20,337 [model] Posterior to be computed for parameters {'Omega_m': 0.3289026332147191, 'b1': 0.511913457355319}
2023-07-02 10:34:20,337 [prior] Evaluating prior at array([0.32890263, 0.51191346])
2023-07-02 10:34:20,337 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:20,337 [model] Got input parameters: {'Omega_m': 0.3289026332147191, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.511913457355319, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:20,337 [classy] Got parameters {'Omega_m': 0.3289026332147191, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:20,337 [classy] Re-using computed results
2023-07-02 10:34:20,337 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.32934705197334}
2023-07-02 10:34:20,337 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:20,337 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.511913457355319, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:20,337 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:20,357 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.90211
2023-07-02 10:34:20,357 [model] Computed derived parameters: {}
2023-07-02 10:34:20,357 [model] Posterior to be computed for parameters {'Omega_m': 0.37708108121482425, 'b1': 0.399273534668007}
2023-07-02 10:34:20,357 [prior] Evaluating prior at array([0.37708108, 0.39927353])
2023-07-02 10:34:20,357 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:20,357 [model] Got input parameters: {'Omega_m': 0.37708108121482425, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.399273534668007, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:20,357 [classy] Got parameters {'Omega_m': 0.37708108121482425, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:20,357 [classy] Computing new state
2023-07-02 10:34:20,357 [classy] Setting parameters: {'Omega_m': 0.37708108121482425, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:20,403 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.1309004510357}
2023-07-02 10:34:20,403 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:20,405 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.220106
2023-07-02 10:34:20,405 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.399273534668007, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:20,405 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:20,425 [fs_likelihood.fslikelihood] Computed log-likelihood = -13.917
2023-07-02 10:34:20,425 [model] Computed derived parameters: {}
2023-07-02 10:34:20,425 [model] Posterior to be computed for parameters {'Omega_m': 0.3289026332147191, 'b1': 0.4590033429366307}
2023-07-02 10:34:20,425 [prior] Evaluating prior at array([0.32890263, 0.45900334])
2023-07-02 10:34:20,425 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:20,425 [model] Got input parameters: {'Omega_m': 0.3289026332147191, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4590033429366307, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:20,425 [classy] Got parameters {'Omega_m': 0.3289026332147191, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:20,425 [classy] Re-using computed results
2023-07-02 10:34:20,425 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.32934705197334}
2023-07-02 10:34:20,425 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:20,425 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4590033429366307, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:20,425 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:20,444 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.23022
2023-07-02 10:34:20,445 [model] Computed derived parameters: {}
2023-07-02 10:34:20,445 [mcmc] New sample, #588:
Omega_m:0.3289026, b1:0.4765755
2023-07-02 10:34:20,445 [model] Posterior to be computed for parameters {'Omega_m': 0.32100907256639155, 'b1': 0.47166849875405537}
2023-07-02 10:34:20,445 [prior] Evaluating prior at array([0.32100907, 0.4716685 ])
2023-07-02 10:34:20,445 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:20,445 [model] Got input parameters: {'Omega_m': 0.32100907256639155, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47166849875405537, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:20,445 [classy] Got parameters {'Omega_m': 0.32100907256639155, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:20,445 [classy] Computing new state
2023-07-02 10:34:20,445 [classy] Setting parameters: {'Omega_m': 0.32100907256639155, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:20,491 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.24659446686888}
2023-07-02 10:34:20,491 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:20,493 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00456581
2023-07-02 10:34:20,493 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47166849875405537, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:20,493 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:20,513 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.8998
2023-07-02 10:34:20,513 [model] Computed derived parameters: {}
2023-07-02 10:34:20,513 [mcmc] New sample, #589:
Omega_m:0.3289026, b1:0.4590033
2023-07-02 10:34:20,513 [model] Posterior to be computed for parameters {'Omega_m': 0.32100907256639155, 'b1': 0.4516625191844553}
2023-07-02 10:34:20,513 [prior] Evaluating prior at array([0.32100907, 0.45166252])
2023-07-02 10:34:20,513 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:20,513 [model] Got input parameters: {'Omega_m': 0.32100907256639155, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4516625191844553, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:20,513 [classy] Got parameters {'Omega_m': 0.32100907256639155, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:20,513 [classy] Re-using computed results
2023-07-02 10:34:20,513 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.24659446686888}
2023-07-02 10:34:20,513 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:20,513 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4516625191844553, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:20,513 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:20,533 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.983418
2023-07-02 10:34:20,533 [model] Computed derived parameters: {}
2023-07-02 10:34:20,533 [model] Posterior to be computed for parameters {'Omega_m': 0.30920681555238894, 'b1': 0.49060512706909953}
2023-07-02 10:34:20,533 [prior] Evaluating prior at array([0.30920682, 0.49060513])
2023-07-02 10:34:20,533 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:20,533 [model] Got input parameters: {'Omega_m': 0.30920681555238894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49060512706909953, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:20,533 [classy] Got parameters {'Omega_m': 0.30920681555238894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:20,533 [classy] Computing new state
2023-07-02 10:34:20,533 [classy] Setting parameters: {'Omega_m': 0.30920681555238894, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:20,580 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.65631469921092}
2023-07-02 10:34:20,580 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:20,582 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000866428
2023-07-02 10:34:20,582 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49060512706909953, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:20,582 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:20,601 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.64164
2023-07-02 10:34:20,601 [model] Computed derived parameters: {}
2023-07-02 10:34:20,601 [mcmc] New sample, #590:
Omega_m:0.3210091, b1:0.4716685
2023-07-02 10:34:20,601 [model] Posterior to be computed for parameters {'Omega_m': 0.30920681555238894, 'b1': 0.37544542411639775}
2023-07-02 10:34:20,602 [prior] Evaluating prior at array([0.30920682, 0.37544542])
2023-07-02 10:34:20,602 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:20,602 [model] Got input parameters: {'Omega_m': 0.30920681555238894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.37544542411639775, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:20,602 [classy] Got parameters {'Omega_m': 0.30920681555238894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:20,602 [classy] Re-using computed results
2023-07-02 10:34:20,602 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.65631469921092}
2023-07-02 10:34:20,602 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:20,602 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.37544542411639775, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:20,602 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:20,622 [fs_likelihood.fslikelihood] Computed log-likelihood = -40.0954
2023-07-02 10:34:20,622 [model] Computed derived parameters: {}
2023-07-02 10:34:20,622 [model] Posterior to be computed for parameters {'Omega_m': 0.315205769466246, 'b1': 0.4809798528176567}
2023-07-02 10:34:20,622 [prior] Evaluating prior at array([0.31520577, 0.48097985])
2023-07-02 10:34:20,622 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:20,622 [model] Got input parameters: {'Omega_m': 0.315205769466246, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4809798528176567, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:20,622 [classy] Got parameters {'Omega_m': 0.315205769466246, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:20,622 [classy] Computing new state
2023-07-02 10:34:20,622 [classy] Setting parameters: {'Omega_m': 0.315205769466246, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:20,669 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.9338687893775}
2023-07-02 10:34:20,669 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:20,670 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000653707
2023-07-02 10:34:20,670 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4809798528176567, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:20,671 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:20,690 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.97225
2023-07-02 10:34:20,690 [model] Computed derived parameters: {}
2023-07-02 10:34:20,690 [mcmc] New sample, #591:
Omega_m:0.3092068, b1:0.4906051
2023-07-02 10:34:20,690 [model] Posterior to be computed for parameters {'Omega_m': 0.315205769466246, 'b1': 0.4935116725125957}
2023-07-02 10:34:20,690 [prior] Evaluating prior at array([0.31520577, 0.49351167])
2023-07-02 10:34:20,690 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:20,690 [model] Got input parameters: {'Omega_m': 0.315205769466246, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4935116725125957, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:20,690 [classy] Got parameters {'Omega_m': 0.315205769466246, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:20,690 [classy] Re-using computed results
2023-07-02 10:34:20,690 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.9338687893775}
2023-07-02 10:34:20,691 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:20,691 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4935116725125957, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:20,691 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:20,710 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.81483
2023-07-02 10:34:20,710 [model] Computed derived parameters: {}
2023-07-02 10:34:20,711 [mcmc] New sample, #592:
Omega_m:0.3152058, b1:0.4809799
2023-07-02 10:34:20,711 [model] Posterior to be computed for parameters {'Omega_m': 0.2997242142097797, 'b1': 0.5183517058454316}
2023-07-02 10:34:20,711 [prior] Evaluating prior at array([0.29972421, 0.51835171])
2023-07-02 10:34:20,711 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:20,711 [model] Got input parameters: {'Omega_m': 0.2997242142097797, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5183517058454316, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:20,711 [classy] Got parameters {'Omega_m': 0.2997242142097797, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:20,711 [classy] Computing new state
2023-07-02 10:34:20,711 [classy] Setting parameters: {'Omega_m': 0.2997242142097797, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:20,758 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.82387556999797}
2023-07-02 10:34:20,758 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:20,760 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0105118
2023-07-02 10:34:20,760 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5183517058454316, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:20,760 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:20,779 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.24208
2023-07-02 10:34:20,779 [model] Computed derived parameters: {}
2023-07-02 10:34:20,779 [mcmc] New sample, #593:
Omega_m:0.3152058, b1:0.4935117
2023-07-02 10:34:20,780 [model] Posterior to be computed for parameters {'Omega_m': 0.2997242142097797, 'b1': 0.5182346109804218}
2023-07-02 10:34:20,780 [prior] Evaluating prior at array([0.29972421, 0.51823461])
2023-07-02 10:34:20,780 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:20,780 [model] Got input parameters: {'Omega_m': 0.2997242142097797, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5182346109804218, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:20,780 [classy] Got parameters {'Omega_m': 0.2997242142097797, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:20,780 [classy] Re-using computed results
2023-07-02 10:34:20,780 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.82387556999797}
2023-07-02 10:34:20,780 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:20,780 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5182346109804218, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:20,780 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:20,799 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.23608
2023-07-02 10:34:20,799 [model] Computed derived parameters: {}
2023-07-02 10:34:20,799 [mcmc] New sample, #594:
Omega_m:0.2997242, b1:0.5183517
2023-07-02 10:34:20,799 [model] Posterior to be computed for parameters {'Omega_m': 0.3012898083111917, 'b1': 0.5157226275898305}
2023-07-02 10:34:20,799 [prior] Evaluating prior at array([0.30128981, 0.51572263])
2023-07-02 10:34:20,800 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:20,800 [model] Got input parameters: {'Omega_m': 0.3012898083111917, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5157226275898305, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:20,800 [classy] Got parameters {'Omega_m': 0.3012898083111917, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:20,800 [classy] Computing new state
2023-07-02 10:34:20,800 [classy] Setting parameters: {'Omega_m': 0.3012898083111917, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:20,846 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.62888503452058}
2023-07-02 10:34:20,846 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:20,848 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00810553
2023-07-02 10:34:20,848 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5157226275898305, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:20,848 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:20,868 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.53588
2023-07-02 10:34:20,868 [model] Computed derived parameters: {}
2023-07-02 10:34:20,868 [mcmc] New sample, #595:
Omega_m:0.2997242, b1:0.5182346
2023-07-02 10:34:20,868 [model] Posterior to be computed for parameters {'Omega_m': 0.3012898083111917, 'b1': 0.5539329096874281}
2023-07-02 10:34:20,868 [prior] Evaluating prior at array([0.30128981, 0.55393291])
2023-07-02 10:34:20,868 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:20,868 [model] Got input parameters: {'Omega_m': 0.3012898083111917, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5539329096874281, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:20,868 [classy] Got parameters {'Omega_m': 0.3012898083111917, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:20,868 [classy] Re-using computed results
2023-07-02 10:34:20,868 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.62888503452058}
2023-07-02 10:34:20,868 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:20,868 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5539329096874281, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:20,868 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:20,887 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.476751
2023-07-02 10:34:20,887 [model] Computed derived parameters: {}
2023-07-02 10:34:20,888 [model] Posterior to be computed for parameters {'Omega_m': 0.30051780299900904, 'b1': 0.5169613040257611}
2023-07-02 10:34:20,888 [prior] Evaluating prior at array([0.3005178, 0.5169613])
2023-07-02 10:34:20,888 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:20,888 [model] Got input parameters: {'Omega_m': 0.30051780299900904, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5169613040257611, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:20,888 [classy] Got parameters {'Omega_m': 0.30051780299900904, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:20,888 [classy] Computing new state
2023-07-02 10:34:20,888 [classy] Setting parameters: {'Omega_m': 0.30051780299900904, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:20,934 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.72491798214503}
2023-07-02 10:34:20,934 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:20,936 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00925082
2023-07-02 10:34:20,936 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5169613040257611, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:20,936 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:20,955 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.39223
2023-07-02 10:34:20,955 [model] Computed derived parameters: {}
2023-07-02 10:34:20,955 [mcmc] New sample, #596:
Omega_m:0.3012898, b1:0.5157226
2023-07-02 10:34:20,955 [model] Posterior to be computed for parameters {'Omega_m': 0.30051780299900904, 'b1': 0.6407225465572772}
2023-07-02 10:34:20,956 [prior] Evaluating prior at array([0.3005178 , 0.64072255])
2023-07-02 10:34:20,956 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:20,956 [model] Got input parameters: {'Omega_m': 0.30051780299900904, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6407225465572772, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:20,956 [classy] Got parameters {'Omega_m': 0.30051780299900904, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:20,956 [classy] Re-using computed results
2023-07-02 10:34:20,956 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.72491798214503}
2023-07-02 10:34:20,956 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:20,956 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6407225465572772, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:20,956 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:20,975 [fs_likelihood.fslikelihood] Computed log-likelihood = -37.0099
2023-07-02 10:34:20,975 [model] Computed derived parameters: {}
2023-07-02 10:34:20,976 [model] Posterior to be computed for parameters {'Omega_m': 0.282812065443168, 'b1': 0.5453700203196771}
2023-07-02 10:34:20,976 [prior] Evaluating prior at array([0.28281207, 0.54537002])
2023-07-02 10:34:20,976 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:20,976 [model] Got input parameters: {'Omega_m': 0.282812065443168, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5453700203196771, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:20,976 [classy] Got parameters {'Omega_m': 0.282812065443168, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:20,976 [classy] Computing new state
2023-07-02 10:34:20,976 [classy] Setting parameters: {'Omega_m': 0.282812065443168, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:21,022 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.98882709049585}
2023-07-02 10:34:21,022 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:21,024 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0584548
2023-07-02 10:34:21,024 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5453700203196771, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:21,024 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:21,043 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.28221
2023-07-02 10:34:21,044 [model] Computed derived parameters: {}
2023-07-02 10:34:21,044 [model] Posterior to be computed for parameters {'Omega_m': 0.30051780299900904, 'b1': 0.4935704175545021}
2023-07-02 10:34:21,044 [prior] Evaluating prior at array([0.3005178 , 0.49357042])
2023-07-02 10:34:21,044 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:21,044 [model] Got input parameters: {'Omega_m': 0.30051780299900904, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4935704175545021, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:21,044 [classy] Got parameters {'Omega_m': 0.30051780299900904, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:21,044 [classy] Re-using computed results
2023-07-02 10:34:21,044 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.72491798214503}
2023-07-02 10:34:21,044 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:21,044 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4935704175545021, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:21,044 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:21,064 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.1728
2023-07-02 10:34:21,064 [model] Computed derived parameters: {}
2023-07-02 10:34:21,064 [mcmc] New sample, #597:
Omega_m:0.3005178, b1:0.5169613
2023-07-02 10:34:21,064 [model] Posterior to be computed for parameters {'Omega_m': 0.3146345604643631, 'b1': 0.4709201915157138}
2023-07-02 10:34:21,064 [prior] Evaluating prior at array([0.31463456, 0.47092019])
2023-07-02 10:34:21,064 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:21,064 [model] Got input parameters: {'Omega_m': 0.3146345604643631, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4709201915157138, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:21,064 [classy] Got parameters {'Omega_m': 0.3146345604643631, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:21,064 [classy] Computing new state
2023-07-02 10:34:21,064 [classy] Setting parameters: {'Omega_m': 0.3146345604643631, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:21,110 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.00212601290167}
2023-07-02 10:34:21,110 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:21,112 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000484585
2023-07-02 10:34:21,112 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4709201915157138, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:21,112 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:21,133 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.557505
2023-07-02 10:34:21,134 [model] Computed derived parameters: {}
2023-07-02 10:34:21,134 [mcmc] New sample, #598:
Omega_m:0.3005178, b1:0.4935704
2023-07-02 10:34:21,134 [model] Posterior to be computed for parameters {'Omega_m': 0.3146345604643631, 'b1': 0.4520860352771344}
2023-07-02 10:34:21,134 [prior] Evaluating prior at array([0.31463456, 0.45208604])
2023-07-02 10:34:21,134 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:21,134 [model] Got input parameters: {'Omega_m': 0.3146345604643631, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4520860352771344, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:21,134 [classy] Got parameters {'Omega_m': 0.3146345604643631, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:21,134 [classy] Re-using computed results
2023-07-02 10:34:21,134 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.00212601290167}
2023-07-02 10:34:21,134 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:21,134 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4520860352771344, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:21,134 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:21,154 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.21501
2023-07-02 10:34:21,154 [model] Computed derived parameters: {}
2023-07-02 10:34:21,154 [model] Posterior to be computed for parameters {'Omega_m': 0.28950977016319035, 'b1': 0.5112327194383182}
2023-07-02 10:34:21,154 [prior] Evaluating prior at array([0.28950977, 0.51123272])
2023-07-02 10:34:21,154 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:21,154 [model] Got input parameters: {'Omega_m': 0.28950977016319035, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5112327194383182, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:21,154 [classy] Got parameters {'Omega_m': 0.28950977016319035, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:21,154 [classy] Computing new state
2023-07-02 10:34:21,154 [classy] Setting parameters: {'Omega_m': 0.28950977016319035, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:21,200 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.11835326864957}
2023-07-02 10:34:21,200 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:21,202 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0345168
2023-07-02 10:34:21,202 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5112327194383182, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:21,202 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:21,222 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.37288
2023-07-02 10:34:21,222 [model] Computed derived parameters: {}
2023-07-02 10:34:21,223 [model] Posterior to be computed for parameters {'Omega_m': 0.3146345604643631, 'b1': 0.4738382967158556}
2023-07-02 10:34:21,223 [prior] Evaluating prior at array([0.31463456, 0.4738383 ])
2023-07-02 10:34:21,223 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:21,223 [model] Got input parameters: {'Omega_m': 0.3146345604643631, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4738382967158556, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:21,223 [classy] Got parameters {'Omega_m': 0.3146345604643631, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:21,223 [classy] Re-using computed results
2023-07-02 10:34:21,223 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.00212601290167}
2023-07-02 10:34:21,223 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:21,223 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4738382967158556, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:21,223 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:21,242 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.988703
2023-07-02 10:34:21,243 [model] Computed derived parameters: {}
2023-07-02 10:34:21,243 [mcmc] New sample, #599:
Omega_m:0.3146346, b1:0.4709202
2023-07-02 10:34:21,243 [model] Posterior to be computed for parameters {'Omega_m': 0.3129953911671648, 'b1': 0.4764683309279262}
2023-07-02 10:34:21,243 [prior] Evaluating prior at array([0.31299539, 0.47646833])
2023-07-02 10:34:21,243 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:21,243 [model] Got input parameters: {'Omega_m': 0.3129953911671648, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4764683309279262, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:21,243 [classy] Got parameters {'Omega_m': 0.3129953911671648, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:21,243 [classy] Computing new state
2023-07-02 10:34:21,243 [classy] Setting parameters: {'Omega_m': 0.3129953911671648, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:21,289 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.19863184742343}
2023-07-02 10:34:21,290 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:21,291 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0002184
2023-07-02 10:34:21,291 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4764683309279262, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:21,291 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:21,311 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.917192
2023-07-02 10:34:21,311 [model] Computed derived parameters: {}
2023-07-02 10:34:21,311 [mcmc] New sample, #600:
Omega_m:0.3146346, b1:0.4738383
2023-07-02 10:34:21,311 [model] Posterior to be computed for parameters {'Omega_m': 0.3129953911671648, 'b1': 0.45650799551065896}
2023-07-02 10:34:21,311 [prior] Evaluating prior at array([0.31299539, 0.456508 ])
2023-07-02 10:34:21,311 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:21,311 [model] Got input parameters: {'Omega_m': 0.3129953911671648, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45650799551065896, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:21,311 [classy] Got parameters {'Omega_m': 0.3129953911671648, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:21,311 [classy] Re-using computed results
2023-07-02 10:34:21,311 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.19863184742343}
2023-07-02 10:34:21,311 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:21,312 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45650799551065896, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:21,312 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:21,332 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.88278
2023-07-02 10:34:21,332 [model] Computed derived parameters: {}
2023-07-02 10:34:21,332 [model] Posterior to be computed for parameters {'Omega_m': 0.28803829013921967, 'b1': 0.5165118027339112}
2023-07-02 10:34:21,332 [prior] Evaluating prior at array([0.28803829, 0.5165118 ])
2023-07-02 10:34:21,332 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:21,332 [model] Got input parameters: {'Omega_m': 0.28803829013921967, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5165118027339112, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:21,332 [classy] Got parameters {'Omega_m': 0.28803829013921967, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:21,332 [classy] Computing new state
2023-07-02 10:34:21,332 [classy] Setting parameters: {'Omega_m': 0.28803829013921967, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:21,380 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.3080849802368}
2023-07-02 10:34:21,380 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:21,382 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0392022
2023-07-02 10:34:21,382 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5165118027339112, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:21,382 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:21,402 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.43915
2023-07-02 10:34:21,402 [model] Computed derived parameters: {}
2023-07-02 10:34:21,402 [model] Posterior to be computed for parameters {'Omega_m': 0.3129953911671648, 'b1': 0.4851893495344608}
2023-07-02 10:34:21,402 [prior] Evaluating prior at array([0.31299539, 0.48518935])
2023-07-02 10:34:21,402 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:21,402 [model] Got input parameters: {'Omega_m': 0.3129953911671648, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4851893495344608, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:21,402 [classy] Got parameters {'Omega_m': 0.3129953911671648, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:21,402 [classy] Re-using computed results
2023-07-02 10:34:21,402 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.19863184742343}
2023-07-02 10:34:21,402 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:21,402 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4851893495344608, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:21,402 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:21,423 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.96626
2023-07-02 10:34:21,423 [model] Computed derived parameters: {}
2023-07-02 10:34:21,423 [mcmc] New sample, #601:
Omega_m:0.3129954, b1:0.4764683
2023-07-02 10:34:21,423 [model] Posterior to be computed for parameters {'Omega_m': 0.29513159474025175, 'b1': 0.5138516700406757}
2023-07-02 10:34:21,423 [prior] Evaluating prior at array([0.29513159, 0.51385167])
2023-07-02 10:34:21,423 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:21,423 [model] Got input parameters: {'Omega_m': 0.29513159474025175, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5138516700406757, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:21,423 [classy] Got parameters {'Omega_m': 0.29513159474025175, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:21,423 [classy] Computing new state
2023-07-02 10:34:21,423 [classy] Setting parameters: {'Omega_m': 0.29513159474025175, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:21,470 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.4010817908082}
2023-07-02 10:34:21,470 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:21,472 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0194955
2023-07-02 10:34:21,472 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5138516700406757, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:21,472 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:21,491 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.849759
2023-07-02 10:34:21,491 [model] Computed derived parameters: {}
2023-07-02 10:34:21,491 [model] Posterior to be computed for parameters {'Omega_m': 0.3129953911671648, 'b1': 0.4842399143259211}
2023-07-02 10:34:21,491 [prior] Evaluating prior at array([0.31299539, 0.48423991])
2023-07-02 10:34:21,492 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:21,492 [model] Got input parameters: {'Omega_m': 0.3129953911671648, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4842399143259211, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:21,492 [classy] Got parameters {'Omega_m': 0.3129953911671648, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:21,492 [classy] Re-using computed results
2023-07-02 10:34:21,492 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.19863184742343}
2023-07-02 10:34:21,492 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:21,492 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4842399143259211, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:21,492 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:21,512 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.87061
2023-07-02 10:34:21,512 [model] Computed derived parameters: {}
2023-07-02 10:34:21,512 [mcmc] New sample, #602:
Omega_m:0.3129954, b1:0.4851893
2023-07-02 10:34:21,512 [model] Posterior to be computed for parameters {'Omega_m': 0.32788641949432357, 'b1': 0.460347376794698}
2023-07-02 10:34:21,512 [prior] Evaluating prior at array([0.32788642, 0.46034738])
2023-07-02 10:34:21,512 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:21,512 [model] Got input parameters: {'Omega_m': 0.32788641949432357, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.460347376794698, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:21,512 [classy] Got parameters {'Omega_m': 0.32788641949432357, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:21,512 [classy] Computing new state
2023-07-02 10:34:21,512 [classy] Setting parameters: {'Omega_m': 0.32788641949432357, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:21,559 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.44632177313633}
2023-07-02 10:34:21,559 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:21,561 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0142106
2023-07-02 10:34:21,561 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.460347376794698, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:21,561 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:21,583 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.32627
2023-07-02 10:34:21,583 [model] Computed derived parameters: {}
2023-07-02 10:34:21,584 [mcmc] New sample, #603:
Omega_m:0.3129954, b1:0.4842399
2023-07-02 10:34:21,584 [model] Posterior to be computed for parameters {'Omega_m': 0.32788641949432357, 'b1': 0.47677877934968327}
2023-07-02 10:34:21,584 [prior] Evaluating prior at array([0.32788642, 0.47677878])
2023-07-02 10:34:21,584 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:21,584 [model] Got input parameters: {'Omega_m': 0.32788641949432357, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47677877934968327, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:21,584 [classy] Got parameters {'Omega_m': 0.32788641949432357, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:21,584 [classy] Re-using computed results
2023-07-02 10:34:21,584 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.44632177313633}
2023-07-02 10:34:21,584 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:21,584 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47677877934968327, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:21,584 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:21,604 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.0679
2023-07-02 10:34:21,604 [model] Computed derived parameters: {}
2023-07-02 10:34:21,604 [mcmc] New sample, #604:
Omega_m:0.3278864, b1:0.4603474
2023-07-02 10:34:21,604 [model] Posterior to be computed for parameters {'Omega_m': 0.31574844823166354, 'b1': 0.49625405852950244}
2023-07-02 10:34:21,604 [prior] Evaluating prior at array([0.31574845, 0.49625406])
2023-07-02 10:34:21,604 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:21,604 [model] Got input parameters: {'Omega_m': 0.31574844823166354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49625405852950244, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:21,604 [classy] Got parameters {'Omega_m': 0.31574844823166354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:21,604 [classy] Computing new state
2023-07-02 10:34:21,604 [classy] Setting parameters: {'Omega_m': 0.31574844823166354, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:21,651 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.86912751611536}
2023-07-02 10:34:21,651 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:21,653 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000850658
2023-07-02 10:34:21,653 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49625405852950244, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:21,653 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:21,673 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.90487
2023-07-02 10:34:21,673 [model] Computed derived parameters: {}
2023-07-02 10:34:21,673 [mcmc] New sample, #605:
Omega_m:0.3278864, b1:0.4767788
2023-07-02 10:34:21,673 [model] Posterior to be computed for parameters {'Omega_m': 0.31574844823166354, 'b1': 0.49301025299765733}
2023-07-02 10:34:21,673 [prior] Evaluating prior at array([0.31574845, 0.49301025])
2023-07-02 10:34:21,674 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:21,674 [model] Got input parameters: {'Omega_m': 0.31574844823166354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49301025299765733, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:21,674 [classy] Got parameters {'Omega_m': 0.31574844823166354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:21,674 [classy] Re-using computed results
2023-07-02 10:34:21,674 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.86912751611536}
2023-07-02 10:34:21,674 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:21,674 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49301025299765733, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:21,674 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:21,693 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.82913
2023-07-02 10:34:21,693 [model] Computed derived parameters: {}
2023-07-02 10:34:21,693 [mcmc] New sample, #606:
Omega_m:0.3157484, b1:0.4962541
2023-07-02 10:34:21,693 [model] Posterior to be computed for parameters {'Omega_m': 0.29222157278473726, 'b1': 0.5307589391366052}
2023-07-02 10:34:21,693 [prior] Evaluating prior at array([0.29222157, 0.53075894])
2023-07-02 10:34:21,693 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:21,694 [model] Got input parameters: {'Omega_m': 0.29222157278473726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5307589391366052, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:21,694 [classy] Got parameters {'Omega_m': 0.29222157278473726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:21,694 [classy] Computing new state
2023-07-02 10:34:21,694 [classy] Setting parameters: {'Omega_m': 0.29222157278473726, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:21,740 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.7708692822892}
2023-07-02 10:34:21,740 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:21,742 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0267073
2023-07-02 10:34:21,742 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5307589391366052, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:21,742 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:21,761 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.651519
2023-07-02 10:34:21,761 [model] Computed derived parameters: {}
2023-07-02 10:34:21,762 [model] Posterior to be computed for parameters {'Omega_m': 0.31574844823166354, 'b1': 0.47699224447515953}
2023-07-02 10:34:21,762 [prior] Evaluating prior at array([0.31574845, 0.47699224])
2023-07-02 10:34:21,762 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:21,762 [model] Got input parameters: {'Omega_m': 0.31574844823166354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47699224447515953, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:21,762 [classy] Got parameters {'Omega_m': 0.31574844823166354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:21,762 [classy] Re-using computed results
2023-07-02 10:34:21,762 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.86912751611536}
2023-07-02 10:34:21,762 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:21,762 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47699224447515953, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:21,762 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:21,782 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.64814
2023-07-02 10:34:21,782 [model] Computed derived parameters: {}
2023-07-02 10:34:21,782 [model] Posterior to be computed for parameters {'Omega_m': 0.3380993439858989, 'b1': 0.4571484170027206}
2023-07-02 10:34:21,782 [prior] Evaluating prior at array([0.33809934, 0.45714842])
2023-07-02 10:34:21,782 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:21,782 [model] Got input parameters: {'Omega_m': 0.3380993439858989, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4571484170027206, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:21,782 [classy] Got parameters {'Omega_m': 0.3380993439858989, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:21,782 [classy] Computing new state
2023-07-02 10:34:21,782 [classy] Setting parameters: {'Omega_m': 0.3380993439858989, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:21,829 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.28543484954614}
2023-07-02 10:34:21,829 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:21,830 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0380097
2023-07-02 10:34:21,831 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4571484170027206, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:21,831 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:21,850 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.244033
2023-07-02 10:34:21,850 [model] Computed derived parameters: {}
2023-07-02 10:34:21,850 [mcmc] New sample, #607:
Omega_m:0.3157484, b1:0.4930103
2023-07-02 10:34:21,850 [model] Posterior to be computed for parameters {'Omega_m': 0.3380993439858989, 'b1': 0.41367130281924835}
2023-07-02 10:34:21,850 [prior] Evaluating prior at array([0.33809934, 0.4136713 ])
2023-07-02 10:34:21,850 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:21,850 [model] Got input parameters: {'Omega_m': 0.3380993439858989, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.41367130281924835, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:21,850 [classy] Got parameters {'Omega_m': 0.3380993439858989, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:21,850 [classy] Re-using computed results
2023-07-02 10:34:21,850 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.28543484954614}
2023-07-02 10:34:21,850 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:21,850 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.41367130281924835, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:21,851 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:21,870 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.03428
2023-07-02 10:34:21,870 [model] Computed derived parameters: {}
2023-07-02 10:34:21,870 [model] Posterior to be computed for parameters {'Omega_m': 0.3391002618085866, 'b1': 0.45554245224872036}
2023-07-02 10:34:21,870 [prior] Evaluating prior at array([0.33910026, 0.45554245])
2023-07-02 10:34:21,870 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:21,870 [model] Got input parameters: {'Omega_m': 0.3391002618085866, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45554245224872036, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:21,870 [classy] Got parameters {'Omega_m': 0.3391002618085866, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:21,870 [classy] Computing new state
2023-07-02 10:34:21,870 [classy] Setting parameters: {'Omega_m': 0.3391002618085866, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:21,916 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.17337440615444}
2023-07-02 10:34:21,916 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:21,918 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0409255
2023-07-02 10:34:21,918 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45554245224872036, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:21,918 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:21,938 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.018712
2023-07-02 10:34:21,938 [model] Computed derived parameters: {}
2023-07-02 10:34:21,938 [mcmc] New sample, #608:
Omega_m:0.3380993, b1:0.4571484
2023-07-02 10:34:21,938 [model] Posterior to be computed for parameters {'Omega_m': 0.3391002618085866, 'b1': 0.5070018450731213}
2023-07-02 10:34:21,938 [prior] Evaluating prior at array([0.33910026, 0.50700185])
2023-07-02 10:34:21,938 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:21,938 [model] Got input parameters: {'Omega_m': 0.3391002618085866, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5070018450731213, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:21,938 [classy] Got parameters {'Omega_m': 0.3391002618085866, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:21,938 [classy] Re-using computed results
2023-07-02 10:34:21,938 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.17337440615444}
2023-07-02 10:34:21,939 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:21,939 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5070018450731213, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:21,939 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:21,958 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.30346
2023-07-02 10:34:21,958 [model] Computed derived parameters: {}
2023-07-02 10:34:21,958 [model] Posterior to be computed for parameters {'Omega_m': 0.32778744649878994, 'b1': 0.47369377520874356}
2023-07-02 10:34:21,958 [prior] Evaluating prior at array([0.32778745, 0.47369378])
2023-07-02 10:34:21,958 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:21,958 [model] Got input parameters: {'Omega_m': 0.32778744649878994, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47369377520874356, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:21,958 [classy] Got parameters {'Omega_m': 0.32778744649878994, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:21,958 [classy] Computing new state
2023-07-02 10:34:21,958 [classy] Setting parameters: {'Omega_m': 0.32778744649878994, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:22,004 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.4577324028305}
2023-07-02 10:34:22,004 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:22,006 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0140344
2023-07-02 10:34:22,006 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47369377520874356, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:22,006 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:22,029 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.0484
2023-07-02 10:34:22,029 [model] Computed derived parameters: {}
2023-07-02 10:34:22,029 [mcmc] New sample, #609:
Omega_m:0.3391003, b1:0.4555425
2023-07-02 10:34:22,029 [model] Posterior to be computed for parameters {'Omega_m': 0.32778744649878994, 'b1': 0.5263300507147055}
2023-07-02 10:34:22,029 [prior] Evaluating prior at array([0.32778745, 0.52633005])
2023-07-02 10:34:22,029 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:22,029 [model] Got input parameters: {'Omega_m': 0.32778744649878994, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5263300507147055, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:22,029 [classy] Got parameters {'Omega_m': 0.32778744649878994, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:22,029 [classy] Re-using computed results
2023-07-02 10:34:22,030 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.4577324028305}
2023-07-02 10:34:22,030 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:22,030 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5263300507147055, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:22,030 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:22,049 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.84752
2023-07-02 10:34:22,049 [model] Computed derived parameters: {}
2023-07-02 10:34:22,049 [model] Posterior to be computed for parameters {'Omega_m': 0.32906145800181924, 'b1': 0.47164963379805125}
2023-07-02 10:34:22,049 [prior] Evaluating prior at array([0.32906146, 0.47164963])
2023-07-02 10:34:22,049 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:22,049 [model] Got input parameters: {'Omega_m': 0.32906145800181924, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47164963379805125, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:22,050 [classy] Got parameters {'Omega_m': 0.32906145800181924, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:22,050 [classy] Computing new state
2023-07-02 10:34:22,050 [classy] Setting parameters: {'Omega_m': 0.32906145800181924, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:22,096 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.31109464996186}
2023-07-02 10:34:22,096 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:22,098 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0163839
2023-07-02 10:34:22,098 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47164963379805125, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:22,098 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:22,117 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.8789
2023-07-02 10:34:22,117 [model] Computed derived parameters: {}
2023-07-02 10:34:22,117 [mcmc] New sample, #610:
Omega_m:0.3277874, b1:0.4736938
2023-07-02 10:34:22,118 [model] Posterior to be computed for parameters {'Omega_m': 0.32906145800181924, 'b1': 0.45676367770691684}
2023-07-02 10:34:22,118 [prior] Evaluating prior at array([0.32906146, 0.45676368])
2023-07-02 10:34:22,118 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:22,118 [model] Got input parameters: {'Omega_m': 0.32906145800181924, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45676367770691684, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:22,118 [classy] Got parameters {'Omega_m': 0.32906145800181924, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:22,118 [classy] Re-using computed results
2023-07-02 10:34:22,118 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.31109464996186}
2023-07-02 10:34:22,118 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:22,118 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45676367770691684, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:22,118 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:22,140 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.02988
2023-07-02 10:34:22,140 [model] Computed derived parameters: {}
2023-07-02 10:34:22,140 [mcmc] New sample, #611:
Omega_m:0.3290615, b1:0.4716496
2023-07-02 10:34:22,140 [model] Posterior to be computed for parameters {'Omega_m': 0.3859305644671005, 'b1': 0.36551764481134263}
2023-07-02 10:34:22,140 [prior] Evaluating prior at array([0.38593056, 0.36551764])
2023-07-02 10:34:22,140 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:22,140 [model] Got input parameters: {'Omega_m': 0.3859305644671005, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.36551764481134263, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:22,140 [classy] Got parameters {'Omega_m': 0.3859305644671005, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:22,140 [classy] Computing new state
2023-07-02 10:34:22,141 [classy] Setting parameters: {'Omega_m': 0.3859305644671005, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:22,187 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 139.2436217381763}
2023-07-02 10:34:22,187 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:22,188 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.279005
2023-07-02 10:34:22,188 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.36551764481134263, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:22,188 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:22,208 [fs_likelihood.fslikelihood] Computed log-likelihood = -18.0436
2023-07-02 10:34:22,208 [model] Computed derived parameters: {}
2023-07-02 10:34:22,208 [model] Posterior to be computed for parameters {'Omega_m': 0.32906145800181924, 'b1': 0.4806656021888392}
2023-07-02 10:34:22,208 [prior] Evaluating prior at array([0.32906146, 0.4806656 ])
2023-07-02 10:34:22,208 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:22,208 [model] Got input parameters: {'Omega_m': 0.32906145800181924, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4806656021888392, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:22,208 [classy] Got parameters {'Omega_m': 0.32906145800181924, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:22,208 [classy] Re-using computed results
2023-07-02 10:34:22,208 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.31109464996186}
2023-07-02 10:34:22,208 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:22,208 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4806656021888392, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:22,208 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:22,228 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.81387
2023-07-02 10:34:22,228 [model] Computed derived parameters: {}
2023-07-02 10:34:22,228 [mcmc] New sample, #612:
Omega_m:0.3290615, b1:0.4567637
2023-07-02 10:34:22,229 [model] Posterior to be computed for parameters {'Omega_m': 0.3227762423449089, 'b1': 0.4907501811497614}
2023-07-02 10:34:22,229 [prior] Evaluating prior at array([0.32277624, 0.49075018])
2023-07-02 10:34:22,229 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:22,229 [model] Got input parameters: {'Omega_m': 0.3227762423449089, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4907501811497614, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:22,229 [classy] Got parameters {'Omega_m': 0.3227762423449089, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:22,229 [classy] Computing new state
2023-07-02 10:34:22,229 [classy] Setting parameters: {'Omega_m': 0.3227762423449089, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:22,275 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.03950798795478}
2023-07-02 10:34:22,275 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:22,277 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00653498
2023-07-02 10:34:22,277 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4907501811497614, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:22,277 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:22,296 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.55796
2023-07-02 10:34:22,297 [model] Computed derived parameters: {}
2023-07-02 10:34:22,297 [mcmc] New sample, #613:
Omega_m:0.3290615, b1:0.4806656
2023-07-02 10:34:22,297 [model] Posterior to be computed for parameters {'Omega_m': 0.3227762423449089, 'b1': 0.5229620379470178}
2023-07-02 10:34:22,297 [prior] Evaluating prior at array([0.32277624, 0.52296204])
2023-07-02 10:34:22,297 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:22,297 [model] Got input parameters: {'Omega_m': 0.3227762423449089, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5229620379470178, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:22,297 [classy] Got parameters {'Omega_m': 0.3227762423449089, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:22,297 [classy] Re-using computed results
2023-07-02 10:34:22,297 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.03950798795478}
2023-07-02 10:34:22,297 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:22,297 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5229620379470178, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:22,297 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:22,316 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.1861
2023-07-02 10:34:22,316 [model] Computed derived parameters: {}
2023-07-02 10:34:22,317 [model] Posterior to be computed for parameters {'Omega_m': 0.3333211968454511, 'b1': 0.4738308848034012}
2023-07-02 10:34:22,317 [prior] Evaluating prior at array([0.3333212 , 0.47383088])
2023-07-02 10:34:22,317 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:22,317 [model] Got input parameters: {'Omega_m': 0.3333211968454511, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4738308848034012, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:22,317 [classy] Got parameters {'Omega_m': 0.3333211968454511, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:22,317 [classy] Computing new state
2023-07-02 10:34:22,317 [classy] Setting parameters: {'Omega_m': 0.3333211968454511, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:22,363 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.82455330259165}
2023-07-02 10:34:22,363 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:22,365 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.025507
2023-07-02 10:34:22,365 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4738308848034012, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:22,365 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:22,385 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.09188
2023-07-02 10:34:22,385 [model] Computed derived parameters: {}
2023-07-02 10:34:22,385 [model] Posterior to be computed for parameters {'Omega_m': 0.3227762423449089, 'b1': 0.5415457835982515}
2023-07-02 10:34:22,385 [prior] Evaluating prior at array([0.32277624, 0.54154578])
2023-07-02 10:34:22,385 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:22,385 [model] Got input parameters: {'Omega_m': 0.3227762423449089, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5415457835982515, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:22,385 [classy] Got parameters {'Omega_m': 0.3227762423449089, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:22,385 [classy] Re-using computed results
2023-07-02 10:34:22,385 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.03950798795478}
2023-07-02 10:34:22,385 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:22,385 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5415457835982515, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:22,385 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:22,405 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.1652
2023-07-02 10:34:22,405 [model] Computed derived parameters: {}
2023-07-02 10:34:22,405 [model] Posterior to be computed for parameters {'Omega_m': 0.36248923502888203, 'b1': 0.4270309975357941}
2023-07-02 10:34:22,405 [prior] Evaluating prior at array([0.36248924, 0.427031 ])
2023-07-02 10:34:22,405 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:22,405 [model] Got input parameters: {'Omega_m': 0.36248923502888203, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4270309975357941, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:22,405 [classy] Got parameters {'Omega_m': 0.36248923502888203, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:22,405 [classy] Computing new state
2023-07-02 10:34:22,405 [classy] Setting parameters: {'Omega_m': 0.36248923502888203, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:22,452 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.63742665151466}
2023-07-02 10:34:22,452 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:22,454 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.13636
2023-07-02 10:34:22,454 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4270309975357941, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:22,454 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:22,473 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.78423
2023-07-02 10:34:22,473 [model] Computed derived parameters: {}
2023-07-02 10:34:22,473 [model] Posterior to be computed for parameters {'Omega_m': 0.3227762423449089, 'b1': 0.4669750119713177}
2023-07-02 10:34:22,473 [prior] Evaluating prior at array([0.32277624, 0.46697501])
2023-07-02 10:34:22,474 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:22,474 [model] Got input parameters: {'Omega_m': 0.3227762423449089, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4669750119713177, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:22,474 [classy] Got parameters {'Omega_m': 0.3227762423449089, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:22,474 [classy] Re-using computed results
2023-07-02 10:34:22,474 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.03950798795478}
2023-07-02 10:34:22,474 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:22,474 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4669750119713177, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:22,474 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:22,493 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.62535
2023-07-02 10:34:22,493 [model] Computed derived parameters: {}
2023-07-02 10:34:22,494 [model] Posterior to be computed for parameters {'Omega_m': 0.3799945227144013, 'b1': 0.39894390147820913}
2023-07-02 10:34:22,494 [prior] Evaluating prior at array([0.37999452, 0.3989439 ])
2023-07-02 10:34:22,494 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:22,494 [model] Got input parameters: {'Omega_m': 0.3799945227144013, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.39894390147820913, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:22,494 [classy] Got parameters {'Omega_m': 0.3799945227144013, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:22,494 [classy] Computing new state
2023-07-02 10:34:22,494 [classy] Setting parameters: {'Omega_m': 0.3799945227144013, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:22,540 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 139.83665481161862}
2023-07-02 10:34:22,540 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:22,542 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.238847
2023-07-02 10:34:22,542 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.39894390147820913, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:22,542 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:22,561 [fs_likelihood.fslikelihood] Computed log-likelihood = -15.6375
2023-07-02 10:34:22,561 [model] Computed derived parameters: {}
2023-07-02 10:34:22,562 [model] Posterior to be computed for parameters {'Omega_m': 0.3227762423449089, 'b1': 0.5095475538057875}
2023-07-02 10:34:22,562 [prior] Evaluating prior at array([0.32277624, 0.50954755])
2023-07-02 10:34:22,562 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:22,562 [model] Got input parameters: {'Omega_m': 0.3227762423449089, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5095475538057875, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:22,562 [classy] Got parameters {'Omega_m': 0.3227762423449089, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:22,562 [classy] Re-using computed results
2023-07-02 10:34:22,562 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.03950798795478}
2023-07-02 10:34:22,562 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:22,562 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5095475538057875, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:22,562 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:22,581 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.10311
2023-07-02 10:34:22,581 [model] Computed derived parameters: {}
2023-07-02 10:34:22,582 [model] Posterior to be computed for parameters {'Omega_m': 0.3064297043580926, 'b1': 0.5169780724528258}
2023-07-02 10:34:22,582 [prior] Evaluating prior at array([0.3064297 , 0.51697807])
2023-07-02 10:34:22,582 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:22,582 [model] Got input parameters: {'Omega_m': 0.3064297043580926, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5169780724528258, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:22,582 [classy] Got parameters {'Omega_m': 0.3064297043580926, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:22,582 [classy] Computing new state
2023-07-02 10:34:22,582 [classy] Setting parameters: {'Omega_m': 0.3064297043580926, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:22,628 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.99495637825544}
2023-07-02 10:34:22,628 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:22,630 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00248452
2023-07-02 10:34:22,630 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5169780724528258, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:22,630 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:22,650 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.47582
2023-07-02 10:34:22,650 [model] Computed derived parameters: {}
2023-07-02 10:34:22,650 [mcmc] New sample, #614:
Omega_m:0.3227762, b1:0.4907502
2023-07-02 10:34:22,650 [model] Posterior to be computed for parameters {'Omega_m': 0.3064297043580926, 'b1': 0.5188153296267065}
2023-07-02 10:34:22,650 [prior] Evaluating prior at array([0.3064297 , 0.51881533])
2023-07-02 10:34:22,650 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:22,651 [model] Got input parameters: {'Omega_m': 0.3064297043580926, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5188153296267065, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:22,651 [classy] Got parameters {'Omega_m': 0.3064297043580926, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:22,651 [classy] Re-using computed results
2023-07-02 10:34:22,651 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.99495637825544}
2023-07-02 10:34:22,651 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:22,651 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5188153296267065, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:22,651 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:22,670 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.45626
2023-07-02 10:34:22,670 [model] Computed derived parameters: {}
2023-07-02 10:34:22,670 [mcmc] New sample, #615:
Omega_m:0.3064297, b1:0.5169781
2023-07-02 10:34:22,670 [model] Posterior to be computed for parameters {'Omega_m': 0.2828969328262557, 'b1': 0.5565734759874011}
2023-07-02 10:34:22,670 [prior] Evaluating prior at array([0.28289693, 0.55657348])
2023-07-02 10:34:22,671 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:22,671 [model] Got input parameters: {'Omega_m': 0.2828969328262557, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5565734759874011, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:22,671 [classy] Got parameters {'Omega_m': 0.2828969328262557, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:22,671 [classy] Computing new state
2023-07-02 10:34:22,671 [classy] Setting parameters: {'Omega_m': 0.2828969328262557, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:22,716 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.9776866336281}
2023-07-02 10:34:22,717 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:22,718 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.058109
2023-07-02 10:34:22,718 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5565734759874011, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:22,718 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:22,738 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.79764
2023-07-02 10:34:22,738 [model] Computed derived parameters: {}
2023-07-02 10:34:22,738 [model] Posterior to be computed for parameters {'Omega_m': 0.3064297043580926, 'b1': 0.5084628442515837}
2023-07-02 10:34:22,738 [prior] Evaluating prior at array([0.3064297 , 0.50846284])
2023-07-02 10:34:22,739 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:22,739 [model] Got input parameters: {'Omega_m': 0.3064297043580926, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5084628442515837, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:22,739 [classy] Got parameters {'Omega_m': 0.3064297043580926, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:22,739 [classy] Re-using computed results
2023-07-02 10:34:22,739 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.99495637825544}
2023-07-02 10:34:22,739 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:22,739 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5084628442515837, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:22,739 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:22,758 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.33163
2023-07-02 10:34:22,758 [model] Computed derived parameters: {}
2023-07-02 10:34:22,758 [mcmc] New sample, #616:
Omega_m:0.3064297, b1:0.5188153
2023-07-02 10:34:22,758 [model] Posterior to be computed for parameters {'Omega_m': 0.2720418676786235, 'b1': 0.5636378570465901}
2023-07-02 10:34:22,759 [prior] Evaluating prior at array([0.27204187, 0.56363786])
2023-07-02 10:34:22,759 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:22,759 [model] Got input parameters: {'Omega_m': 0.2720418676786235, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5636378570465901, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:22,759 [classy] Got parameters {'Omega_m': 0.2720418676786235, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:22,759 [classy] Computing new state
2023-07-02 10:34:22,759 [classy] Setting parameters: {'Omega_m': 0.2720418676786235, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:22,805 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.42639930439992}
2023-07-02 10:34:22,805 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:22,807 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.111572
2023-07-02 10:34:22,807 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5636378570465901, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:22,807 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:22,827 [fs_likelihood.fslikelihood] Computed log-likelihood = -10.1409
2023-07-02 10:34:22,827 [model] Computed derived parameters: {}
2023-07-02 10:34:22,827 [model] Posterior to be computed for parameters {'Omega_m': 0.3064297043580926, 'b1': 0.5085546523174836}
2023-07-02 10:34:22,827 [prior] Evaluating prior at array([0.3064297 , 0.50855465])
2023-07-02 10:34:22,827 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:22,827 [model] Got input parameters: {'Omega_m': 0.3064297043580926, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5085546523174836, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:22,827 [classy] Got parameters {'Omega_m': 0.3064297043580926, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:22,827 [classy] Re-using computed results
2023-07-02 10:34:22,827 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.99495637825544}
2023-07-02 10:34:22,827 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:22,827 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5085546523174836, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:22,827 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:22,847 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.33523
2023-07-02 10:34:22,847 [model] Computed derived parameters: {}
2023-07-02 10:34:22,847 [mcmc] New sample, #617:
Omega_m:0.3064297, b1:0.5084628
2023-07-02 10:34:22,847 [model] Posterior to be computed for parameters {'Omega_m': 0.30397454625323694, 'b1': 0.5124939341371525}
2023-07-02 10:34:22,847 [prior] Evaluating prior at array([0.30397455, 0.51249393])
2023-07-02 10:34:22,847 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:22,847 [model] Got input parameters: {'Omega_m': 0.30397454625323694, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5124939341371525, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:22,847 [classy] Got parameters {'Omega_m': 0.30397454625323694, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:22,847 [classy] Computing new state
2023-07-02 10:34:22,847 [classy] Setting parameters: {'Omega_m': 0.30397454625323694, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:22,894 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2965890103057}
2023-07-02 10:34:22,894 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:22,896 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0047385
2023-07-02 10:34:22,896 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5124939341371525, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:22,896 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:22,915 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.02097
2023-07-02 10:34:22,915 [model] Computed derived parameters: {}
2023-07-02 10:34:22,915 [mcmc] New sample, #618:
Omega_m:0.3064297, b1:0.5085547
2023-07-02 10:34:22,915 [model] Posterior to be computed for parameters {'Omega_m': 0.30397454625323694, 'b1': 0.5512513758955078}
2023-07-02 10:34:22,915 [prior] Evaluating prior at array([0.30397455, 0.55125138])
2023-07-02 10:34:22,915 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:22,915 [model] Got input parameters: {'Omega_m': 0.30397454625323694, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5512513758955078, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:22,915 [classy] Got parameters {'Omega_m': 0.30397454625323694, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:22,915 [classy] Re-using computed results
2023-07-02 10:34:22,916 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2965890103057}
2023-07-02 10:34:22,916 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:22,916 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5512513758955078, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:22,916 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:22,935 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.436916
2023-07-02 10:34:22,935 [model] Computed derived parameters: {}
2023-07-02 10:34:22,935 [mcmc] New sample, #619:
Omega_m:0.3039745, b1:0.5124939
2023-07-02 10:34:22,935 [model] Posterior to be computed for parameters {'Omega_m': 0.3032105327408295, 'b1': 0.5524772295517166}
2023-07-02 10:34:22,935 [prior] Evaluating prior at array([0.30321053, 0.55247723])
2023-07-02 10:34:22,935 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:22,935 [model] Got input parameters: {'Omega_m': 0.3032105327408295, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5524772295517166, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:22,935 [classy] Got parameters {'Omega_m': 0.3032105327408295, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:22,935 [classy] Computing new state
2023-07-02 10:34:22,936 [classy] Setting parameters: {'Omega_m': 0.3032105327408295, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:22,982 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.3908907174827}
2023-07-02 10:34:22,982 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:22,984 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00559996
2023-07-02 10:34:22,984 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5524772295517166, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:22,984 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:23,003 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.514231
2023-07-02 10:34:23,004 [model] Computed derived parameters: {}
2023-07-02 10:34:23,004 [mcmc] New sample, #620:
Omega_m:0.3039745, b1:0.5512514
2023-07-02 10:34:23,004 [model] Posterior to be computed for parameters {'Omega_m': 0.3032105327408295, 'b1': 0.5723118045357374}
2023-07-02 10:34:23,004 [prior] Evaluating prior at array([0.30321053, 0.5723118 ])
2023-07-02 10:34:23,004 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:23,004 [model] Got input parameters: {'Omega_m': 0.3032105327408295, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5723118045357374, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:23,004 [classy] Got parameters {'Omega_m': 0.3032105327408295, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:23,004 [classy] Re-using computed results
2023-07-02 10:34:23,004 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.3908907174827}
2023-07-02 10:34:23,004 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:23,004 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5723118045357374, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:23,004 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:23,024 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.08048
2023-07-02 10:34:23,024 [model] Computed derived parameters: {}
2023-07-02 10:34:23,024 [model] Posterior to be computed for parameters {'Omega_m': 0.29091300316472607, 'b1': 0.5722085187872962}
2023-07-02 10:34:23,024 [prior] Evaluating prior at array([0.290913 , 0.57220852])
2023-07-02 10:34:23,024 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:23,024 [model] Got input parameters: {'Omega_m': 0.29091300316472607, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5722085187872962, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:23,024 [classy] Got parameters {'Omega_m': 0.29091300316472607, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:23,024 [classy] Computing new state
2023-07-02 10:34:23,024 [classy] Setting parameters: {'Omega_m': 0.29091300316472607, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:23,070 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.93819892457324}
2023-07-02 10:34:23,070 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:23,072 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0303433
2023-07-02 10:34:23,072 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5722085187872962, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:23,072 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:23,092 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.88357
2023-07-02 10:34:23,093 [model] Computed derived parameters: {}
2023-07-02 10:34:23,093 [model] Posterior to be computed for parameters {'Omega_m': 0.3032105327408295, 'b1': 0.5696462930821214}
2023-07-02 10:34:23,093 [prior] Evaluating prior at array([0.30321053, 0.56964629])
2023-07-02 10:34:23,093 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:23,093 [model] Got input parameters: {'Omega_m': 0.3032105327408295, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5696462930821214, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:23,093 [classy] Got parameters {'Omega_m': 0.3032105327408295, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:23,093 [classy] Re-using computed results
2023-07-02 10:34:23,093 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.3908907174827}
2023-07-02 10:34:23,093 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:23,093 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5696462930821214, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:23,093 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:23,114 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.32874
2023-07-02 10:34:23,114 [model] Computed derived parameters: {}
2023-07-02 10:34:23,114 [model] Posterior to be computed for parameters {'Omega_m': 0.2823036358121705, 'b1': 0.5860221808173293}
2023-07-02 10:34:23,114 [prior] Evaluating prior at array([0.28230364, 0.58602218])
2023-07-02 10:34:23,114 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:23,114 [model] Got input parameters: {'Omega_m': 0.2823036358121705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5860221808173293, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:23,115 [classy] Got parameters {'Omega_m': 0.2823036358121705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:23,115 [classy] Computing new state
2023-07-02 10:34:23,115 [classy] Setting parameters: {'Omega_m': 0.2823036358121705, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:23,164 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.0556307628839}
2023-07-02 10:34:23,164 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:23,166 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0605493
2023-07-02 10:34:23,166 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5860221808173293, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:23,166 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:23,185 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.91288
2023-07-02 10:34:23,186 [model] Computed derived parameters: {}
2023-07-02 10:34:23,186 [model] Posterior to be computed for parameters {'Omega_m': 0.3032105327408295, 'b1': 0.61633662283627}
2023-07-02 10:34:23,186 [prior] Evaluating prior at array([0.30321053, 0.61633662])
2023-07-02 10:34:23,186 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:23,186 [model] Got input parameters: {'Omega_m': 0.3032105327408295, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.61633662283627, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:23,186 [classy] Got parameters {'Omega_m': 0.3032105327408295, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:23,186 [classy] Re-using computed results
2023-07-02 10:34:23,186 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.3908907174827}
2023-07-02 10:34:23,186 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:23,186 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.61633662283627, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:23,186 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:23,205 [fs_likelihood.fslikelihood] Computed log-likelihood = -24.0742
2023-07-02 10:34:23,205 [model] Computed derived parameters: {}
2023-07-02 10:34:23,206 [model] Posterior to be computed for parameters {'Omega_m': 0.2827987976343764, 'b1': 0.5852276975780821}
2023-07-02 10:34:23,206 [prior] Evaluating prior at array([0.2827988, 0.5852277])
2023-07-02 10:34:23,206 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:23,206 [model] Got input parameters: {'Omega_m': 0.2827987976343764, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5852276975780821, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:23,206 [classy] Got parameters {'Omega_m': 0.2827987976343764, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:23,206 [classy] Computing new state
2023-07-02 10:34:23,206 [classy] Setting parameters: {'Omega_m': 0.2827987976343764, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:23,252 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.99057018180818}
2023-07-02 10:34:23,252 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:23,254 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.058509
2023-07-02 10:34:23,254 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5852276975780821, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:23,254 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:23,273 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.70567
2023-07-02 10:34:23,274 [model] Computed derived parameters: {}
2023-07-02 10:34:23,274 [model] Posterior to be computed for parameters {'Omega_m': 0.3032105327408295, 'b1': 0.6015972343661647}
2023-07-02 10:34:23,274 [prior] Evaluating prior at array([0.30321053, 0.60159723])
2023-07-02 10:34:23,274 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:23,274 [model] Got input parameters: {'Omega_m': 0.3032105327408295, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6015972343661647, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:23,274 [classy] Got parameters {'Omega_m': 0.3032105327408295, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:23,274 [classy] Re-using computed results
2023-07-02 10:34:23,274 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.3908907174827}
2023-07-02 10:34:23,274 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:23,274 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6015972343661647, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:23,274 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:23,293 [fs_likelihood.fslikelihood] Computed log-likelihood = -16.2939
2023-07-02 10:34:23,294 [model] Computed derived parameters: {}
2023-07-02 10:34:23,294 [model] Posterior to be computed for parameters {'Omega_m': 0.2991654293152863, 'b1': 0.5589675661012886}
2023-07-02 10:34:23,294 [prior] Evaluating prior at array([0.29916543, 0.55896757])
2023-07-02 10:34:23,294 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:23,294 [model] Got input parameters: {'Omega_m': 0.2991654293152863, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5589675661012886, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:23,294 [classy] Got parameters {'Omega_m': 0.2991654293152863, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:23,294 [classy] Computing new state
2023-07-02 10:34:23,294 [classy] Setting parameters: {'Omega_m': 0.2991654293152863, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:23,340 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.89369091505128}
2023-07-02 10:34:23,340 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:23,342 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0114507
2023-07-02 10:34:23,342 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5589675661012886, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:23,342 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:23,361 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.05541
2023-07-02 10:34:23,361 [model] Computed derived parameters: {}
2023-07-02 10:34:23,361 [mcmc] New sample, #621:
Omega_m:0.3032105, b1:0.5524772
2023-07-02 10:34:23,362 [model] Posterior to be computed for parameters {'Omega_m': 0.2991654293152863, 'b1': 0.5218876467665031}
2023-07-02 10:34:23,362 [prior] Evaluating prior at array([0.29916543, 0.52188765])
2023-07-02 10:34:23,362 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:23,362 [model] Got input parameters: {'Omega_m': 0.2991654293152863, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5218876467665031, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:23,362 [classy] Got parameters {'Omega_m': 0.2991654293152863, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:23,362 [classy] Re-using computed results
2023-07-02 10:34:23,362 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.89369091505128}
2023-07-02 10:34:23,362 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:23,362 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5218876467665031, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:23,362 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:23,381 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.24496
2023-07-02 10:34:23,382 [model] Computed derived parameters: {}
2023-07-02 10:34:23,382 [mcmc] New sample, #622:
Omega_m:0.2991654, b1:0.5589676
2023-07-02 10:34:23,382 [model] Posterior to be computed for parameters {'Omega_m': 0.2762234136268267, 'b1': 0.5586979300347653}
2023-07-02 10:34:23,382 [prior] Evaluating prior at array([0.27622341, 0.55869793])
2023-07-02 10:34:23,382 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:23,382 [model] Got input parameters: {'Omega_m': 0.2762234136268267, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5586979300347653, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:23,382 [classy] Got parameters {'Omega_m': 0.2762234136268267, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:23,382 [classy] Computing new state
2023-07-02 10:34:23,382 [classy] Setting parameters: {'Omega_m': 0.2762234136268267, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:23,428 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.86259655193544}
2023-07-02 10:34:23,428 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:23,430 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0887334
2023-07-02 10:34:23,430 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5586979300347653, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:23,430 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:23,450 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.48428
2023-07-02 10:34:23,450 [model] Computed derived parameters: {}
2023-07-02 10:34:23,451 [model] Posterior to be computed for parameters {'Omega_m': 0.2991654293152863, 'b1': 0.4871447661295815}
2023-07-02 10:34:23,451 [prior] Evaluating prior at array([0.29916543, 0.48714477])
2023-07-02 10:34:23,451 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:23,451 [model] Got input parameters: {'Omega_m': 0.2991654293152863, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4871447661295815, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:23,451 [classy] Got parameters {'Omega_m': 0.2991654293152863, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:23,451 [classy] Re-using computed results
2023-07-02 10:34:23,451 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.89369091505128}
2023-07-02 10:34:23,451 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:23,451 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4871447661295815, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:23,451 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:23,471 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.09564
2023-07-02 10:34:23,471 [model] Computed derived parameters: {}
2023-07-02 10:34:23,471 [model] Posterior to be computed for parameters {'Omega_m': 0.2769523586635247, 'b1': 0.5575283434713081}
2023-07-02 10:34:23,471 [prior] Evaluating prior at array([0.27695236, 0.55752834])
2023-07-02 10:34:23,471 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:23,471 [model] Got input parameters: {'Omega_m': 0.2769523586635247, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5575283434713081, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:23,471 [classy] Got parameters {'Omega_m': 0.2769523586635247, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:23,471 [classy] Computing new state
2023-07-02 10:34:23,471 [classy] Setting parameters: {'Omega_m': 0.2769523586635247, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:23,518 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.7650575944623}
2023-07-02 10:34:23,518 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:23,519 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0850445
2023-07-02 10:34:23,519 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5575283434713081, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:23,520 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:23,539 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.07438
2023-07-02 10:34:23,539 [model] Computed derived parameters: {}
2023-07-02 10:34:23,539 [model] Posterior to be computed for parameters {'Omega_m': 0.2991654293152863, 'b1': 0.520730747909928}
2023-07-02 10:34:23,539 [prior] Evaluating prior at array([0.29916543, 0.52073075])
2023-07-02 10:34:23,539 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:23,539 [model] Got input parameters: {'Omega_m': 0.2991654293152863, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.520730747909928, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:23,539 [classy] Got parameters {'Omega_m': 0.2991654293152863, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:23,539 [classy] Re-using computed results
2023-07-02 10:34:23,539 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.89369091505128}
2023-07-02 10:34:23,539 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:23,539 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.520730747909928, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:23,539 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:23,559 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.19769
2023-07-02 10:34:23,559 [model] Computed derived parameters: {}
2023-07-02 10:34:23,559 [mcmc] New sample, #623:
Omega_m:0.2991654, b1:0.5218876
2023-07-02 10:34:23,559 [model] Posterior to be computed for parameters {'Omega_m': 0.30475766795410936, 'b1': 0.5117580451102195}
2023-07-02 10:34:23,559 [prior] Evaluating prior at array([0.30475767, 0.51175805])
2023-07-02 10:34:23,559 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:23,559 [model] Got input parameters: {'Omega_m': 0.30475766795410936, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5117580451102195, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:23,559 [classy] Got parameters {'Omega_m': 0.30475766795410936, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:23,560 [classy] Computing new state
2023-07-02 10:34:23,560 [classy] Setting parameters: {'Omega_m': 0.30475766795410936, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:23,606 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.20014596533642}
2023-07-02 10:34:23,606 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:23,608 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00393468
2023-07-02 10:34:23,608 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5117580451102195, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:23,608 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:23,627 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.15016
2023-07-02 10:34:23,627 [model] Computed derived parameters: {}
2023-07-02 10:34:23,627 [mcmc] New sample, #624:
Omega_m:0.2991654, b1:0.5207307
2023-07-02 10:34:23,628 [model] Posterior to be computed for parameters {'Omega_m': 0.30475766795410936, 'b1': 0.5317703700182342}
2023-07-02 10:34:23,628 [prior] Evaluating prior at array([0.30475767, 0.53177037])
2023-07-02 10:34:23,628 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:23,628 [model] Got input parameters: {'Omega_m': 0.30475766795410936, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5317703700182342, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:23,628 [classy] Got parameters {'Omega_m': 0.30475766795410936, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:23,628 [classy] Re-using computed results
2023-07-02 10:34:23,628 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.20014596533642}
2023-07-02 10:34:23,628 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:23,628 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5317703700182342, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:23,628 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:23,648 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.84275
2023-07-02 10:34:23,648 [model] Computed derived parameters: {}
2023-07-02 10:34:23,648 [mcmc] New sample, #625:
Omega_m:0.3047577, b1:0.511758
2023-07-02 10:34:23,648 [model] Posterior to be computed for parameters {'Omega_m': 0.28966968137688587, 'b1': 0.5559789255086183}
2023-07-02 10:34:23,648 [prior] Evaluating prior at array([0.28966968, 0.55597893])
2023-07-02 10:34:23,648 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:23,648 [model] Got input parameters: {'Omega_m': 0.28966968137688587, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5559789255086183, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:23,648 [classy] Got parameters {'Omega_m': 0.28966968137688587, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:23,648 [classy] Computing new state
2023-07-02 10:34:23,648 [classy] Setting parameters: {'Omega_m': 0.28966968137688587, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:23,695 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.09778805534918}
2023-07-02 10:34:23,695 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:23,697 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0340269
2023-07-02 10:34:23,697 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5559789255086183, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:23,697 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:23,716 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.39721
2023-07-02 10:34:23,716 [model] Computed derived parameters: {}
2023-07-02 10:34:23,716 [model] Posterior to be computed for parameters {'Omega_m': 0.30475766795410936, 'b1': 0.5115332617529503}
2023-07-02 10:34:23,716 [prior] Evaluating prior at array([0.30475767, 0.51153326])
2023-07-02 10:34:23,716 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:23,716 [model] Got input parameters: {'Omega_m': 0.30475766795410936, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5115332617529503, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:23,717 [classy] Got parameters {'Omega_m': 0.30475766795410936, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:23,717 [classy] Re-using computed results
2023-07-02 10:34:23,717 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.20014596533642}
2023-07-02 10:34:23,717 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:23,717 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5115332617529503, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:23,717 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:23,736 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.1415
2023-07-02 10:34:23,736 [model] Computed derived parameters: {}
2023-07-02 10:34:23,736 [mcmc] New sample, #626:
Omega_m:0.3047577, b1:0.5317704
2023-07-02 10:34:23,736 [model] Posterior to be computed for parameters {'Omega_m': 0.32395193384246734, 'b1': 0.4807362134869512}
2023-07-02 10:34:23,736 [prior] Evaluating prior at array([0.32395193, 0.48073621])
2023-07-02 10:34:23,736 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:23,736 [model] Got input parameters: {'Omega_m': 0.32395193384246734, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4807362134869512, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:23,736 [classy] Got parameters {'Omega_m': 0.32395193384246734, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:23,736 [classy] Computing new state
2023-07-02 10:34:23,737 [classy] Setting parameters: {'Omega_m': 0.32395193384246734, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:23,782 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.90229367627933}
2023-07-02 10:34:23,782 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:23,784 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00804199
2023-07-02 10:34:23,784 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4807362134869512, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:23,784 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:23,804 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.48018
2023-07-02 10:34:23,804 [model] Computed derived parameters: {}
2023-07-02 10:34:23,804 [mcmc] New sample, #627:
Omega_m:0.3047577, b1:0.5115333
2023-07-02 10:34:23,805 [model] Posterior to be computed for parameters {'Omega_m': 0.32395193384246734, 'b1': 0.48139359166374995}
2023-07-02 10:34:23,805 [prior] Evaluating prior at array([0.32395193, 0.48139359])
2023-07-02 10:34:23,805 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:23,805 [model] Got input parameters: {'Omega_m': 0.32395193384246734, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48139359166374995, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:23,805 [classy] Got parameters {'Omega_m': 0.32395193384246734, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:23,805 [classy] Re-using computed results
2023-07-02 10:34:23,805 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.90229367627933}
2023-07-02 10:34:23,805 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:23,805 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48139359166374995, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:23,805 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:23,825 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.491
2023-07-02 10:34:23,825 [model] Computed derived parameters: {}
2023-07-02 10:34:23,825 [mcmc] New sample, #628:
Omega_m:0.3239519, b1:0.4807362
2023-07-02 10:34:23,825 [model] Posterior to be computed for parameters {'Omega_m': 0.30412960243880965, 'b1': 0.5131983660965845}
2023-07-02 10:34:23,825 [prior] Evaluating prior at array([0.3041296 , 0.51319837])
2023-07-02 10:34:23,825 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:23,825 [model] Got input parameters: {'Omega_m': 0.30412960243880965, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5131983660965845, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:23,825 [classy] Got parameters {'Omega_m': 0.30412960243880965, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:23,825 [classy] Computing new state
2023-07-02 10:34:23,825 [classy] Setting parameters: {'Omega_m': 0.30412960243880965, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:23,871 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.27747665659018}
2023-07-02 10:34:23,871 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:23,873 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.004573
2023-07-02 10:34:23,873 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5131983660965845, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:23,873 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:23,892 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.08018
2023-07-02 10:34:23,893 [model] Computed derived parameters: {}
2023-07-02 10:34:23,893 [mcmc] New sample, #629:
Omega_m:0.3239519, b1:0.4813936
2023-07-02 10:34:23,893 [model] Posterior to be computed for parameters {'Omega_m': 0.30412960243880965, 'b1': 0.5080086781054344}
2023-07-02 10:34:23,893 [prior] Evaluating prior at array([0.3041296 , 0.50800868])
2023-07-02 10:34:23,893 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:23,893 [model] Got input parameters: {'Omega_m': 0.30412960243880965, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5080086781054344, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:23,893 [classy] Got parameters {'Omega_m': 0.30412960243880965, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:23,893 [classy] Re-using computed results
2023-07-02 10:34:23,893 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.27747665659018}
2023-07-02 10:34:23,893 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:23,893 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5080086781054344, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:23,893 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:23,913 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.82142
2023-07-02 10:34:23,913 [model] Computed derived parameters: {}
2023-07-02 10:34:23,913 [mcmc] New sample, #630:
Omega_m:0.3041296, b1:0.5131984
2023-07-02 10:34:23,913 [model] Posterior to be computed for parameters {'Omega_m': 0.30248727299258243, 'b1': 0.5106437827517032}
2023-07-02 10:34:23,913 [prior] Evaluating prior at array([0.30248727, 0.51064378])
2023-07-02 10:34:23,913 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:23,913 [model] Got input parameters: {'Omega_m': 0.30248727299258243, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5106437827517032, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:23,913 [classy] Got parameters {'Omega_m': 0.30248727299258243, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:23,913 [classy] Computing new state
2023-07-02 10:34:23,913 [classy] Setting parameters: {'Omega_m': 0.30248727299258243, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:23,959 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.4803543506021}
2023-07-02 10:34:23,959 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:23,961 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00648617
2023-07-02 10:34:23,961 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5106437827517032, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:23,961 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:23,980 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.56336
2023-07-02 10:34:23,980 [model] Computed derived parameters: {}
2023-07-02 10:34:23,980 [mcmc] New sample, #631:
Omega_m:0.3041296, b1:0.5080087
2023-07-02 10:34:23,980 [model] Posterior to be computed for parameters {'Omega_m': 0.30248727299258243, 'b1': 0.4791357691439814}
2023-07-02 10:34:23,980 [prior] Evaluating prior at array([0.30248727, 0.47913577])
2023-07-02 10:34:23,981 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:23,981 [model] Got input parameters: {'Omega_m': 0.30248727299258243, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4791357691439814, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:23,981 [classy] Got parameters {'Omega_m': 0.30248727299258243, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:23,981 [classy] Re-using computed results
2023-07-02 10:34:23,981 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.4803543506021}
2023-07-02 10:34:23,981 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:23,981 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4791357691439814, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:23,981 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:24,000 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.94797
2023-07-02 10:34:24,000 [model] Computed derived parameters: {}
2023-07-02 10:34:24,000 [model] Posterior to be computed for parameters {'Omega_m': 0.3288167908076349, 'b1': 0.46839827903267445}
2023-07-02 10:34:24,000 [prior] Evaluating prior at array([0.32881679, 0.46839828])
2023-07-02 10:34:24,000 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:24,000 [model] Got input parameters: {'Omega_m': 0.3288167908076349, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46839827903267445, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:24,001 [classy] Got parameters {'Omega_m': 0.3288167908076349, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:24,001 [classy] Computing new state
2023-07-02 10:34:24,001 [classy] Setting parameters: {'Omega_m': 0.3288167908076349, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:24,047 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.33921777466418}
2023-07-02 10:34:24,047 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:24,049 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0159189
2023-07-02 10:34:24,049 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46839827903267445, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:24,049 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:24,069 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.81256
2023-07-02 10:34:24,069 [model] Computed derived parameters: {}
2023-07-02 10:34:24,069 [mcmc] New sample, #632:
Omega_m:0.3024873, b1:0.5106438
2023-07-02 10:34:24,069 [model] Posterior to be computed for parameters {'Omega_m': 0.3288167908076349, 'b1': 0.5402921511833714}
2023-07-02 10:34:24,069 [prior] Evaluating prior at array([0.32881679, 0.54029215])
2023-07-02 10:34:24,069 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:24,069 [model] Got input parameters: {'Omega_m': 0.3288167908076349, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5402921511833714, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:24,069 [classy] Got parameters {'Omega_m': 0.3288167908076349, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:24,069 [classy] Re-using computed results
2023-07-02 10:34:24,069 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.33921777466418}
2023-07-02 10:34:24,069 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:24,069 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5402921511833714, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:24,069 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:24,089 [fs_likelihood.fslikelihood] Computed log-likelihood = -10.3676
2023-07-02 10:34:24,089 [model] Computed derived parameters: {}
2023-07-02 10:34:24,089 [model] Posterior to be computed for parameters {'Omega_m': 0.3207607547953617, 'b1': 0.48132412529038865}
2023-07-02 10:34:24,089 [prior] Evaluating prior at array([0.32076075, 0.48132413])
2023-07-02 10:34:24,089 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:24,089 [model] Got input parameters: {'Omega_m': 0.3207607547953617, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48132412529038865, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:24,089 [classy] Got parameters {'Omega_m': 0.3207607547953617, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:24,089 [classy] Computing new state
2023-07-02 10:34:24,089 [classy] Setting parameters: {'Omega_m': 0.3207607547953617, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:24,137 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.27577440451998}
2023-07-02 10:34:24,137 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:24,139 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00431783
2023-07-02 10:34:24,139 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48132412529038865, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:24,139 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:24,159 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.5591
2023-07-02 10:34:24,159 [model] Computed derived parameters: {}
2023-07-02 10:34:24,159 [mcmc] New sample, #633:
Omega_m:0.3288168, b1:0.4683983
2023-07-02 10:34:24,159 [model] Posterior to be computed for parameters {'Omega_m': 0.3207607547953617, 'b1': 0.5238641458877586}
2023-07-02 10:34:24,160 [prior] Evaluating prior at array([0.32076075, 0.52386415])
2023-07-02 10:34:24,160 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:24,160 [model] Got input parameters: {'Omega_m': 0.3207607547953617, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5238641458877586, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:24,160 [classy] Got parameters {'Omega_m': 0.3207607547953617, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:24,160 [classy] Re-using computed results
2023-07-02 10:34:24,160 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.27577440451998}
2023-07-02 10:34:24,160 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:24,160 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5238641458877586, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:24,160 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:24,179 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.479895
2023-07-02 10:34:24,180 [model] Computed derived parameters: {}
2023-07-02 10:34:24,180 [model] Posterior to be computed for parameters {'Omega_m': 0.3342411170951309, 'b1': 0.4596949902766368}
2023-07-02 10:34:24,180 [prior] Evaluating prior at array([0.33424112, 0.45969499])
2023-07-02 10:34:24,180 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:24,180 [model] Got input parameters: {'Omega_m': 0.3342411170951309, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4596949902766368, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:24,180 [classy] Got parameters {'Omega_m': 0.3342411170951309, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:24,180 [classy] Computing new state
2023-07-02 10:34:24,180 [classy] Setting parameters: {'Omega_m': 0.3342411170951309, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:24,226 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.72021833296682}
2023-07-02 10:34:24,227 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:24,228 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0277299
2023-07-02 10:34:24,228 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4596949902766368, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:24,228 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:24,248 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.953271
2023-07-02 10:34:24,248 [model] Computed derived parameters: {}
2023-07-02 10:34:24,248 [mcmc] New sample, #634:
Omega_m:0.3207608, b1:0.4813241
2023-07-02 10:34:24,248 [model] Posterior to be computed for parameters {'Omega_m': 0.3342411170951309, 'b1': 0.5180125286952466}
2023-07-02 10:34:24,248 [prior] Evaluating prior at array([0.33424112, 0.51801253])
2023-07-02 10:34:24,248 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:24,248 [model] Got input parameters: {'Omega_m': 0.3342411170951309, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5180125286952466, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:24,248 [classy] Got parameters {'Omega_m': 0.3342411170951309, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:24,248 [classy] Re-using computed results
2023-07-02 10:34:24,248 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.72021833296682}
2023-07-02 10:34:24,248 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:24,248 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5180125286952466, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:24,248 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:24,268 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.93352
2023-07-02 10:34:24,268 [model] Computed derived parameters: {}
2023-07-02 10:34:24,268 [model] Posterior to be computed for parameters {'Omega_m': 0.34313262453008814, 'b1': 0.44542863670913946}
2023-07-02 10:34:24,268 [prior] Evaluating prior at array([0.34313262, 0.44542864])
2023-07-02 10:34:24,268 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:24,268 [model] Got input parameters: {'Omega_m': 0.34313262453008814, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44542863670913946, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:24,268 [classy] Got parameters {'Omega_m': 0.34313262453008814, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:24,268 [classy] Computing new state
2023-07-02 10:34:24,268 [classy] Setting parameters: {'Omega_m': 0.34313262453008814, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:24,314 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.72493596161004}
2023-07-02 10:34:24,315 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:24,316 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0536898
2023-07-02 10:34:24,316 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44542863670913946, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:24,316 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:24,336 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.01658
2023-07-02 10:34:24,336 [model] Computed derived parameters: {}
2023-07-02 10:34:24,336 [model] Posterior to be computed for parameters {'Omega_m': 0.3342411170951309, 'b1': 0.4815162766483814}
2023-07-02 10:34:24,336 [prior] Evaluating prior at array([0.33424112, 0.48151628])
2023-07-02 10:34:24,336 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:24,336 [model] Got input parameters: {'Omega_m': 0.3342411170951309, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4815162766483814, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:24,336 [classy] Got parameters {'Omega_m': 0.3342411170951309, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:24,336 [classy] Re-using computed results
2023-07-02 10:34:24,336 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.72021833296682}
2023-07-02 10:34:24,336 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:24,336 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4815162766483814, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:24,336 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:24,356 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.327881
2023-07-02 10:34:24,356 [model] Computed derived parameters: {}
2023-07-02 10:34:24,356 [model] Posterior to be computed for parameters {'Omega_m': 0.34763522329684704, 'b1': 0.43820425249205885}
2023-07-02 10:34:24,356 [prior] Evaluating prior at array([0.34763522, 0.43820425])
2023-07-02 10:34:24,356 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:24,356 [model] Got input parameters: {'Omega_m': 0.34763522329684704, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.43820425249205885, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:24,356 [classy] Got parameters {'Omega_m': 0.34763522329684704, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:24,357 [classy] Computing new state
2023-07-02 10:34:24,357 [classy] Setting parameters: {'Omega_m': 0.34763522329684704, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:24,402 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.22988539667287}
2023-07-02 10:34:24,402 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:24,404 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0698216
2023-07-02 10:34:24,404 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.43820425249205885, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:24,404 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:24,424 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.25743
2023-07-02 10:34:24,424 [model] Computed derived parameters: {}
2023-07-02 10:34:24,424 [model] Posterior to be computed for parameters {'Omega_m': 0.3342411170951309, 'b1': 0.4588897392813515}
2023-07-02 10:34:24,425 [prior] Evaluating prior at array([0.33424112, 0.45888974])
2023-07-02 10:34:24,425 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:24,425 [model] Got input parameters: {'Omega_m': 0.3342411170951309, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4588897392813515, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:24,425 [classy] Got parameters {'Omega_m': 0.3342411170951309, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:24,425 [classy] Re-using computed results
2023-07-02 10:34:24,425 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.72021833296682}
2023-07-02 10:34:24,425 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:24,425 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4588897392813515, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:24,425 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:24,444 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.926198
2023-07-02 10:34:24,444 [model] Computed derived parameters: {}
2023-07-02 10:34:24,444 [mcmc] New sample, #635:
Omega_m:0.3342411, b1:0.459695
2023-07-02 10:34:24,444 [model] Posterior to be computed for parameters {'Omega_m': 0.36686816203618766, 'b1': 0.4065399029463184}
2023-07-02 10:34:24,444 [prior] Evaluating prior at array([0.36686816, 0.4065399 ])
2023-07-02 10:34:24,444 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:24,444 [model] Got input parameters: {'Omega_m': 0.36686816203618766, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4065399029463184, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:24,444 [classy] Got parameters {'Omega_m': 0.36686816203618766, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:24,445 [classy] Computing new state
2023-07-02 10:34:24,445 [classy] Setting parameters: {'Omega_m': 0.36686816203618766, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:24,490 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.17949725417077}
2023-07-02 10:34:24,491 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:24,492 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.159662
2023-07-02 10:34:24,492 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4065399029463184, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:24,492 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:24,512 [fs_likelihood.fslikelihood] Computed log-likelihood = -9.12262
2023-07-02 10:34:24,512 [model] Computed derived parameters: {}
2023-07-02 10:34:24,512 [model] Posterior to be computed for parameters {'Omega_m': 0.3342411170951309, 'b1': 0.44476619380700344}
2023-07-02 10:34:24,512 [prior] Evaluating prior at array([0.33424112, 0.44476619])
2023-07-02 10:34:24,513 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:24,513 [model] Got input parameters: {'Omega_m': 0.3342411170951309, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44476619380700344, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:24,513 [classy] Got parameters {'Omega_m': 0.3342411170951309, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:24,513 [classy] Re-using computed results
2023-07-02 10:34:24,513 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.72021833296682}
2023-07-02 10:34:24,513 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:24,513 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44476619380700344, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:24,513 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:24,532 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.1076
2023-07-02 10:34:24,532 [model] Computed derived parameters: {}
2023-07-02 10:34:24,532 [mcmc] New sample, #636:
Omega_m:0.3342411, b1:0.4588897
2023-07-02 10:34:24,532 [model] Posterior to be computed for parameters {'Omega_m': 0.31676147068122745, 'b1': 0.47281214864646903}
2023-07-02 10:34:24,532 [prior] Evaluating prior at array([0.31676147, 0.47281215])
2023-07-02 10:34:24,532 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:24,532 [model] Got input parameters: {'Omega_m': 0.31676147068122745, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47281214864646903, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:24,533 [classy] Got parameters {'Omega_m': 0.31676147068122745, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:24,533 [classy] Computing new state
2023-07-02 10:34:24,533 [classy] Setting parameters: {'Omega_m': 0.31676147068122745, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:24,579 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.74853437447192}
2023-07-02 10:34:24,579 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:24,581 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00131253
2023-07-02 10:34:24,581 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47281214864646903, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:24,581 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:24,600 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.35209
2023-07-02 10:34:24,600 [model] Computed derived parameters: {}
2023-07-02 10:34:24,600 [mcmc] New sample, #637:
Omega_m:0.3342411, b1:0.4447662
2023-07-02 10:34:24,600 [model] Posterior to be computed for parameters {'Omega_m': 0.31676147068122745, 'b1': 0.4823902058030781}
2023-07-02 10:34:24,600 [prior] Evaluating prior at array([0.31676147, 0.48239021])
2023-07-02 10:34:24,600 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:24,600 [model] Got input parameters: {'Omega_m': 0.31676147068122745, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4823902058030781, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:24,600 [classy] Got parameters {'Omega_m': 0.31676147068122745, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:24,600 [classy] Re-using computed results
2023-07-02 10:34:24,600 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.74853437447192}
2023-07-02 10:34:24,600 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:24,600 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4823902058030781, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:24,600 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:24,620 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.33331
2023-07-02 10:34:24,620 [model] Computed derived parameters: {}
2023-07-02 10:34:24,620 [mcmc] New sample, #638:
Omega_m:0.3167615, b1:0.4728121
2023-07-02 10:34:24,620 [model] Posterior to be computed for parameters {'Omega_m': 0.30823459303396417, 'b1': 0.496071513751423}
2023-07-02 10:34:24,621 [prior] Evaluating prior at array([0.30823459, 0.49607151])
2023-07-02 10:34:24,621 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:24,621 [model] Got input parameters: {'Omega_m': 0.30823459303396417, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.496071513751423, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:24,621 [classy] Got parameters {'Omega_m': 0.30823459303396417, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:24,621 [classy] Computing new state
2023-07-02 10:34:24,621 [classy] Setting parameters: {'Omega_m': 0.30823459303396417, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:24,667 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.77456122260148}
2023-07-02 10:34:24,667 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:24,669 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00132158
2023-07-02 10:34:24,669 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.496071513751423, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:24,669 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:24,688 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.92395
2023-07-02 10:34:24,689 [model] Computed derived parameters: {}
2023-07-02 10:34:24,689 [model] Posterior to be computed for parameters {'Omega_m': 0.31676147068122745, 'b1': 0.46354884532833285}
2023-07-02 10:34:24,689 [prior] Evaluating prior at array([0.31676147, 0.46354885])
2023-07-02 10:34:24,689 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:24,689 [model] Got input parameters: {'Omega_m': 0.31676147068122745, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46354884532833285, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:24,689 [classy] Got parameters {'Omega_m': 0.31676147068122745, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:24,689 [classy] Re-using computed results
2023-07-02 10:34:24,689 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.74853437447192}
2023-07-02 10:34:24,689 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:24,689 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46354884532833285, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:24,689 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:24,708 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.0343967
2023-07-02 10:34:24,708 [model] Computed derived parameters: {}
2023-07-02 10:34:24,708 [model] Posterior to be computed for parameters {'Omega_m': 0.33367174672391486, 'b1': 0.4552578012345925}
2023-07-02 10:34:24,708 [prior] Evaluating prior at array([0.33367175, 0.4552578 ])
2023-07-02 10:34:24,709 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:24,709 [model] Got input parameters: {'Omega_m': 0.33367174672391486, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4552578012345925, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:24,709 [classy] Got parameters {'Omega_m': 0.33367174672391486, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:24,709 [classy] Computing new state
2023-07-02 10:34:24,709 [classy] Setting parameters: {'Omega_m': 0.33367174672391486, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:24,754 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.7847650730614}
2023-07-02 10:34:24,755 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:24,756 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0263435
2023-07-02 10:34:24,756 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4552578012345925, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:24,756 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:24,776 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.807995
2023-07-02 10:34:24,776 [model] Computed derived parameters: {}
2023-07-02 10:34:24,776 [mcmc] New sample, #639:
Omega_m:0.3167615, b1:0.4823902
2023-07-02 10:34:24,776 [model] Posterior to be computed for parameters {'Omega_m': 0.33367174672391486, 'b1': 0.4005117986214789}
2023-07-02 10:34:24,776 [prior] Evaluating prior at array([0.33367175, 0.4005118 ])
2023-07-02 10:34:24,776 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:24,776 [model] Got input parameters: {'Omega_m': 0.33367174672391486, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4005117986214789, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:24,776 [classy] Got parameters {'Omega_m': 0.33367174672391486, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:24,776 [classy] Re-using computed results
2023-07-02 10:34:24,776 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.7847650730614}
2023-07-02 10:34:24,776 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:24,777 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4005117986214789, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:24,777 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:24,796 [fs_likelihood.fslikelihood] Computed log-likelihood = -10.0083
2023-07-02 10:34:24,796 [model] Computed derived parameters: {}
2023-07-02 10:34:24,796 [model] Posterior to be computed for parameters {'Omega_m': 0.35352167088856196, 'b1': 0.42340875443432663}
2023-07-02 10:34:24,796 [prior] Evaluating prior at array([0.35352167, 0.42340875])
2023-07-02 10:34:24,796 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:24,796 [model] Got input parameters: {'Omega_m': 0.35352167088856196, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42340875443432663, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:24,796 [classy] Got parameters {'Omega_m': 0.35352167088856196, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:24,796 [classy] Computing new state
2023-07-02 10:34:24,796 [classy] Setting parameters: {'Omega_m': 0.35352167088856196, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:24,842 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.59146439464664}
2023-07-02 10:34:24,842 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:24,844 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.093804
2023-07-02 10:34:24,844 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42340875443432663, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:24,844 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:24,864 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.24282
2023-07-02 10:34:24,864 [model] Computed derived parameters: {}
2023-07-02 10:34:24,864 [model] Posterior to be computed for parameters {'Omega_m': 0.33367174672391486, 'b1': 0.46806260222737}
2023-07-02 10:34:24,864 [prior] Evaluating prior at array([0.33367175, 0.4680626 ])
2023-07-02 10:34:24,865 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:24,865 [model] Got input parameters: {'Omega_m': 0.33367174672391486, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46806260222737, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:24,865 [classy] Got parameters {'Omega_m': 0.33367174672391486, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:24,865 [classy] Re-using computed results
2023-07-02 10:34:24,865 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.7847650730614}
2023-07-02 10:34:24,865 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:24,865 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46806260222737, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:24,865 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:24,884 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.14446
2023-07-02 10:34:24,884 [model] Computed derived parameters: {}
2023-07-02 10:34:24,884 [mcmc] New sample, #640:
Omega_m:0.3336717, b1:0.4552578
2023-07-02 10:34:24,884 [mcmc] Learn + convergence test @ 640 samples accepted.
2023-07-02 10:34:24,884 [mcmc] Ready to check convergence and learn a new proposal covmat
2023-07-02 10:34:24,889 [mcmc] - Acceptance rate: 0.475
2023-07-02 10:34:24,889 [mcmc] - Condition number = 18.1812
2023-07-02 10:34:24,889 [mcmc] - Eigenvalues = array([0.00466148, 0.08475108])
2023-07-02 10:34:24,890 [mcmc] - Convergence of means: R-1 = 0.084751 after 512 accepted steps
2023-07-02 10:34:24,890 [mcmc] - Updated covariance matrix of proposal pdf.
2023-07-02 10:34:24,890 [mcmc] array([[ 0.00010358, -0.00017195],
[-0.00017195, 0.00046429]])
2023-07-02 10:34:24,900 [mcmc] Dumped checkpoint and progress info, and current covmat.
2023-07-02 10:34:24,900 [model] Posterior to be computed for parameters {'Omega_m': 0.30453218163579315, 'b1': 0.5164357133108873}
2023-07-02 10:34:24,900 [prior] Evaluating prior at array([0.30453218, 0.51643571])
2023-07-02 10:34:24,900 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:24,900 [model] Got input parameters: {'Omega_m': 0.30453218163579315, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5164357133108873, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:24,900 [classy] Got parameters {'Omega_m': 0.30453218163579315, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:24,900 [classy] Computing new state
2023-07-02 10:34:24,900 [classy] Setting parameters: {'Omega_m': 0.30453218163579315, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:24,948 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.22789359814456}
2023-07-02 10:34:24,948 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:24,950 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00415795
2023-07-02 10:34:24,950 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5164357133108873, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:24,950 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:24,971 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.23585
2023-07-02 10:34:24,971 [model] Computed derived parameters: {}
2023-07-02 10:34:24,971 [mcmc] New sample, #641:
Omega_m:0.3336717, b1:0.4680626
2023-07-02 10:34:24,971 [model] Posterior to be computed for parameters {'Omega_m': 0.30453218163579315, 'b1': 0.5372895902961363}
2023-07-02 10:34:24,971 [prior] Evaluating prior at array([0.30453218, 0.53728959])
2023-07-02 10:34:24,971 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:24,971 [model] Got input parameters: {'Omega_m': 0.30453218163579315, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5372895902961363, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:24,971 [classy] Got parameters {'Omega_m': 0.30453218163579315, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:24,971 [classy] Re-using computed results
2023-07-02 10:34:24,971 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.22789359814456}
2023-07-02 10:34:24,971 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:24,971 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5372895902961363, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:24,971 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:24,991 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.38521
2023-07-02 10:34:24,991 [model] Computed derived parameters: {}
2023-07-02 10:34:24,991 [mcmc] New sample, #642:
Omega_m:0.3045322, b1:0.5164357
2023-07-02 10:34:24,991 [model] Posterior to be computed for parameters {'Omega_m': 0.3000674928633739, 'b1': 0.5447011932246099}
2023-07-02 10:34:24,991 [prior] Evaluating prior at array([0.30006749, 0.54470119])
2023-07-02 10:34:24,991 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:24,991 [model] Got input parameters: {'Omega_m': 0.3000674928633739, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5447011932246099, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:24,991 [classy] Got parameters {'Omega_m': 0.3000674928633739, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:24,991 [classy] Computing new state
2023-07-02 10:34:24,991 [classy] Setting parameters: {'Omega_m': 0.3000674928633739, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:25,038 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.78104038734946}
2023-07-02 10:34:25,038 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:25,040 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00995593
2023-07-02 10:34:25,040 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5447011932246099, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:25,040 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:25,059 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.753538
2023-07-02 10:34:25,059 [model] Computed derived parameters: {}
2023-07-02 10:34:25,059 [mcmc] New sample, #643:
Omega_m:0.3045322, b1:0.5372896
2023-07-02 10:34:25,059 [model] Posterior to be computed for parameters {'Omega_m': 0.3000674928633739, 'b1': 0.5557023943511958}
2023-07-02 10:34:25,059 [prior] Evaluating prior at array([0.30006749, 0.55570239])
2023-07-02 10:34:25,059 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:25,059 [model] Got input parameters: {'Omega_m': 0.3000674928633739, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5557023943511958, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:25,060 [classy] Got parameters {'Omega_m': 0.3000674928633739, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:25,060 [classy] Re-using computed results
2023-07-02 10:34:25,060 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.78104038734946}
2023-07-02 10:34:25,060 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:25,060 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5557023943511958, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:25,060 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:25,079 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.621411
2023-07-02 10:34:25,079 [model] Computed derived parameters: {}
2023-07-02 10:34:25,079 [model] Posterior to be computed for parameters {'Omega_m': 0.2831730848475549, 'b1': 0.5727467413708522}
2023-07-02 10:34:25,080 [prior] Evaluating prior at array([0.28317308, 0.57274674])
2023-07-02 10:34:25,080 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:25,080 [model] Got input parameters: {'Omega_m': 0.2831730848475549, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5727467413708522, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:25,080 [classy] Got parameters {'Omega_m': 0.2831730848475549, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:25,080 [classy] Computing new state
2023-07-02 10:34:25,080 [classy] Setting parameters: {'Omega_m': 0.2831730848475549, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:25,127 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.94145238875436}
2023-07-02 10:34:25,127 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:25,128 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0569915
2023-07-02 10:34:25,128 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5727467413708522, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:25,128 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:25,149 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.23534
2023-07-02 10:34:25,149 [model] Computed derived parameters: {}
2023-07-02 10:34:25,149 [model] Posterior to be computed for parameters {'Omega_m': 0.3000674928633739, 'b1': 0.5136822893523919}
2023-07-02 10:34:25,149 [prior] Evaluating prior at array([0.30006749, 0.51368229])
2023-07-02 10:34:25,149 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:25,149 [model] Got input parameters: {'Omega_m': 0.3000674928633739, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5136822893523919, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:25,149 [classy] Got parameters {'Omega_m': 0.3000674928633739, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:25,149 [classy] Re-using computed results
2023-07-02 10:34:25,149 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.78104038734946}
2023-07-02 10:34:25,149 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:25,149 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5136822893523919, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:25,149 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:25,169 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.05876
2023-07-02 10:34:25,169 [model] Computed derived parameters: {}
2023-07-02 10:34:25,169 [mcmc] New sample, #644:
Omega_m:0.3000675, b1:0.5447012
2023-07-02 10:34:25,169 [model] Posterior to be computed for parameters {'Omega_m': 0.33629683107478214, 'b1': 0.45353980622050877}
2023-07-02 10:34:25,169 [prior] Evaluating prior at array([0.33629683, 0.45353981])
2023-07-02 10:34:25,169 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:25,169 [model] Got input parameters: {'Omega_m': 0.33629683107478214, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45353980622050877, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:25,169 [classy] Got parameters {'Omega_m': 0.33629683107478214, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:25,169 [classy] Computing new state
2023-07-02 10:34:25,169 [classy] Setting parameters: {'Omega_m': 0.33629683107478214, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:25,215 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.48799897594725}
2023-07-02 10:34:25,216 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:25,217 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0330161
2023-07-02 10:34:25,218 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45353980622050877, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:25,218 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:25,237 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.452087
2023-07-02 10:34:25,237 [model] Computed derived parameters: {}
2023-07-02 10:34:25,237 [mcmc] New sample, #645:
Omega_m:0.3000675, b1:0.5136823
2023-07-02 10:34:25,238 [model] Posterior to be computed for parameters {'Omega_m': 0.33629683107478214, 'b1': 0.4849462018302281}
2023-07-02 10:34:25,238 [prior] Evaluating prior at array([0.33629683, 0.4849462 ])
2023-07-02 10:34:25,238 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:25,238 [model] Got input parameters: {'Omega_m': 0.33629683107478214, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4849462018302281, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:25,238 [classy] Got parameters {'Omega_m': 0.33629683107478214, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:25,238 [classy] Re-using computed results
2023-07-02 10:34:25,238 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.48799897594725}
2023-07-02 10:34:25,238 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:25,238 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4849462018302281, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:25,238 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:25,257 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.874281
2023-07-02 10:34:25,257 [model] Computed derived parameters: {}
2023-07-02 10:34:25,257 [model] Posterior to be computed for parameters {'Omega_m': 0.33958092609964635, 'b1': 0.4480880469726901}
2023-07-02 10:34:25,257 [prior] Evaluating prior at array([0.33958093, 0.44808805])
2023-07-02 10:34:25,257 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:25,257 [model] Got input parameters: {'Omega_m': 0.33958092609964635, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4480880469726901, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:25,258 [classy] Got parameters {'Omega_m': 0.33958092609964635, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:25,258 [classy] Computing new state
2023-07-02 10:34:25,258 [classy] Setting parameters: {'Omega_m': 0.33958092609964635, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:25,304 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.11966615646188}
2023-07-02 10:34:25,304 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:25,306 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0423618
2023-07-02 10:34:25,306 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4480880469726901, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:25,306 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:25,326 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.253556
2023-07-02 10:34:25,326 [model] Computed derived parameters: {}
2023-07-02 10:34:25,326 [mcmc] New sample, #646:
Omega_m:0.3362968, b1:0.4535398
2023-07-02 10:34:25,326 [model] Posterior to be computed for parameters {'Omega_m': 0.33958092609964635, 'b1': 0.4468493555511388}
2023-07-02 10:34:25,326 [prior] Evaluating prior at array([0.33958093, 0.44684936])
2023-07-02 10:34:25,326 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:25,326 [model] Got input parameters: {'Omega_m': 0.33958092609964635, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4468493555511388, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:25,326 [classy] Got parameters {'Omega_m': 0.33958092609964635, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:25,326 [classy] Re-using computed results
2023-07-02 10:34:25,326 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.11966615646188}
2023-07-02 10:34:25,327 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:25,327 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4468493555511388, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:25,327 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:25,346 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.309947
2023-07-02 10:34:25,346 [model] Computed derived parameters: {}
2023-07-02 10:34:25,346 [mcmc] New sample, #647:
Omega_m:0.3395809, b1:0.448088
2023-07-02 10:34:25,346 [model] Posterior to be computed for parameters {'Omega_m': 0.31424623715146294, 'b1': 0.4889061851246316}
2023-07-02 10:34:25,346 [prior] Evaluating prior at array([0.31424624, 0.48890619])
2023-07-02 10:34:25,346 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:25,346 [model] Got input parameters: {'Omega_m': 0.31424623715146294, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4889061851246316, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:25,346 [classy] Got parameters {'Omega_m': 0.31424623715146294, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:25,346 [classy] Computing new state
2023-07-02 10:34:25,346 [classy] Setting parameters: {'Omega_m': 0.31424623715146294, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:25,393 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.04859954639085}
2023-07-02 10:34:25,393 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:25,395 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000392036
2023-07-02 10:34:25,395 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4889061851246316, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:25,395 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:25,414 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.48522
2023-07-02 10:34:25,414 [model] Computed derived parameters: {}
2023-07-02 10:34:25,414 [mcmc] New sample, #648:
Omega_m:0.3395809, b1:0.4468494
2023-07-02 10:34:25,414 [model] Posterior to be computed for parameters {'Omega_m': 0.31424623715146294, 'b1': 0.5171685871882612}
2023-07-02 10:34:25,414 [prior] Evaluating prior at array([0.31424624, 0.51716859])
2023-07-02 10:34:25,414 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:25,415 [model] Got input parameters: {'Omega_m': 0.31424623715146294, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5171685871882612, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:25,415 [classy] Got parameters {'Omega_m': 0.31424623715146294, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:25,415 [classy] Re-using computed results
2023-07-02 10:34:25,415 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.04859954639085}
2023-07-02 10:34:25,415 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:25,415 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5171685871882612, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:25,415 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:25,435 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.26841
2023-07-02 10:34:25,435 [model] Computed derived parameters: {}
2023-07-02 10:34:25,435 [mcmc] New sample, #649:
Omega_m:0.3142462, b1:0.4889062
2023-07-02 10:34:25,435 [model] Posterior to be computed for parameters {'Omega_m': 0.2952522510530034, 'b1': 0.548699538205581}
2023-07-02 10:34:25,435 [prior] Evaluating prior at array([0.29525225, 0.54869954])
2023-07-02 10:34:25,435 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:25,435 [model] Got input parameters: {'Omega_m': 0.2952522510530034, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.548699538205581, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:25,435 [classy] Got parameters {'Omega_m': 0.2952522510530034, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:25,435 [classy] Computing new state
2023-07-02 10:34:25,435 [classy] Setting parameters: {'Omega_m': 0.2952522510530034, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:25,481 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.38581860890665}
2023-07-02 10:34:25,482 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:25,483 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0192222
2023-07-02 10:34:25,484 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.548699538205581, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:25,484 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:25,503 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.0781293
2023-07-02 10:34:25,503 [model] Computed derived parameters: {}
2023-07-02 10:34:25,503 [model] Posterior to be computed for parameters {'Omega_m': 0.31424623715146294, 'b1': 0.5018672050831509}
2023-07-02 10:34:25,503 [prior] Evaluating prior at array([0.31424624, 0.50186721])
2023-07-02 10:34:25,503 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:25,503 [model] Got input parameters: {'Omega_m': 0.31424623715146294, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5018672050831509, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:25,503 [classy] Got parameters {'Omega_m': 0.31424623715146294, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:25,503 [classy] Re-using computed results
2023-07-02 10:34:25,503 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.04859954639085}
2023-07-02 10:34:25,503 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:25,503 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5018672050831509, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:25,503 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:25,523 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.92163
2023-07-02 10:34:25,523 [model] Computed derived parameters: {}
2023-07-02 10:34:25,523 [mcmc] New sample, #650:
Omega_m:0.3142462, b1:0.5171686
2023-07-02 10:34:25,523 [model] Posterior to be computed for parameters {'Omega_m': 0.34880705003835855, 'b1': 0.44449455604536725}
2023-07-02 10:34:25,523 [prior] Evaluating prior at array([0.34880705, 0.44449456])
2023-07-02 10:34:25,523 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:25,523 [model] Got input parameters: {'Omega_m': 0.34880705003835855, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44449455604536725, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:25,523 [classy] Got parameters {'Omega_m': 0.34880705003835855, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:25,523 [classy] Computing new state
2023-07-02 10:34:25,523 [classy] Setting parameters: {'Omega_m': 0.34880705003835855, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:25,569 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.10200856158238}
2023-07-02 10:34:25,569 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:25,571 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0743379
2023-07-02 10:34:25,571 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44449455604536725, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:25,571 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:25,591 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.65885
2023-07-02 10:34:25,591 [model] Computed derived parameters: {}
2023-07-02 10:34:25,591 [model] Posterior to be computed for parameters {'Omega_m': 0.31424623715146294, 'b1': 0.5456354677866205}
2023-07-02 10:34:25,591 [prior] Evaluating prior at array([0.31424624, 0.54563547])
2023-07-02 10:34:25,591 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:25,591 [model] Got input parameters: {'Omega_m': 0.31424623715146294, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5456354677866205, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:25,591 [classy] Got parameters {'Omega_m': 0.31424623715146294, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:25,591 [classy] Re-using computed results
2023-07-02 10:34:25,591 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.04859954639085}
2023-07-02 10:34:25,591 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:25,591 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5456354677866205, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:25,591 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:25,610 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.50731
2023-07-02 10:34:25,610 [model] Computed derived parameters: {}
2023-07-02 10:34:25,611 [model] Posterior to be computed for parameters {'Omega_m': 0.307948076645282, 'b1': 0.5123224612568781}
2023-07-02 10:34:25,611 [prior] Evaluating prior at array([0.30794808, 0.51232246])
2023-07-02 10:34:25,611 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:25,611 [model] Got input parameters: {'Omega_m': 0.307948076645282, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5123224612568781, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:25,611 [classy] Got parameters {'Omega_m': 0.307948076645282, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:25,611 [classy] Computing new state
2023-07-02 10:34:25,611 [classy] Setting parameters: {'Omega_m': 0.307948076645282, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:25,658 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.80947073287007}
2023-07-02 10:34:25,658 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:25,660 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00147851
2023-07-02 10:34:25,660 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5123224612568781, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:25,660 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:25,681 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.62074
2023-07-02 10:34:25,681 [model] Computed derived parameters: {}
2023-07-02 10:34:25,681 [mcmc] New sample, #651:
Omega_m:0.3142462, b1:0.5018672
2023-07-02 10:34:25,681 [model] Posterior to be computed for parameters {'Omega_m': 0.307948076645282, 'b1': 0.4671608381228353}
2023-07-02 10:34:25,681 [prior] Evaluating prior at array([0.30794808, 0.46716084])
2023-07-02 10:34:25,681 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:25,681 [model] Got input parameters: {'Omega_m': 0.307948076645282, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4671608381228353, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:25,681 [classy] Got parameters {'Omega_m': 0.307948076645282, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:25,681 [classy] Re-using computed results
2023-07-02 10:34:25,681 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.80947073287007}
2023-07-02 10:34:25,681 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:25,681 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4671608381228353, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:25,681 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:25,701 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.78494
2023-07-02 10:34:25,701 [model] Computed derived parameters: {}
2023-07-02 10:34:25,701 [model] Posterior to be computed for parameters {'Omega_m': 0.30382114559235485, 'b1': 0.51917336976061}
2023-07-02 10:34:25,701 [prior] Evaluating prior at array([0.30382115, 0.51917337])
2023-07-02 10:34:25,701 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:25,701 [model] Got input parameters: {'Omega_m': 0.30382114559235485, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.51917336976061, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:25,701 [classy] Got parameters {'Omega_m': 0.30382114559235485, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:25,701 [classy] Computing new state
2023-07-02 10:34:25,701 [classy] Setting parameters: {'Omega_m': 0.30382114559235485, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:25,749 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.3155071779159}
2023-07-02 10:34:25,749 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:25,751 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00490534
2023-07-02 10:34:25,751 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.51917336976061, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:25,751 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:25,771 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.15839
2023-07-02 10:34:25,771 [model] Computed derived parameters: {}
2023-07-02 10:34:25,771 [model] Posterior to be computed for parameters {'Omega_m': 0.307948076645282, 'b1': 0.5458057948874686}
2023-07-02 10:34:25,771 [prior] Evaluating prior at array([0.30794808, 0.54580579])
2023-07-02 10:34:25,771 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:25,771 [model] Got input parameters: {'Omega_m': 0.307948076645282, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5458057948874686, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:25,771 [classy] Got parameters {'Omega_m': 0.307948076645282, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:25,771 [classy] Re-using computed results
2023-07-02 10:34:25,771 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.80947073287007}
2023-07-02 10:34:25,771 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:25,771 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5458057948874686, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:25,771 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:25,791 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.326092
2023-07-02 10:34:25,791 [model] Computed derived parameters: {}
2023-07-02 10:34:25,791 [model] Posterior to be computed for parameters {'Omega_m': 0.30566116849497127, 'b1': 0.5161188412528814}
2023-07-02 10:34:25,791 [prior] Evaluating prior at array([0.30566117, 0.51611884])
2023-07-02 10:34:25,791 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:25,791 [model] Got input parameters: {'Omega_m': 0.30566116849497127, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5161188412528814, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:25,791 [classy] Got parameters {'Omega_m': 0.30566116849497127, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:25,791 [classy] Computing new state
2023-07-02 10:34:25,792 [classy] Setting parameters: {'Omega_m': 0.30566116849497127, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:25,838 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.08914655669415}
2023-07-02 10:34:25,838 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:25,840 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00310624
2023-07-02 10:34:25,840 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5161188412528814, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:25,840 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:25,861 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.39137
2023-07-02 10:34:25,861 [model] Computed derived parameters: {}
2023-07-02 10:34:25,861 [model] Posterior to be computed for parameters {'Omega_m': 0.307948076645282, 'b1': 0.4644212829912632}
2023-07-02 10:34:25,861 [prior] Evaluating prior at array([0.30794808, 0.46442128])
2023-07-02 10:34:25,861 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:25,861 [model] Got input parameters: {'Omega_m': 0.307948076645282, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4644212829912632, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:25,861 [classy] Got parameters {'Omega_m': 0.307948076645282, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:25,861 [classy] Re-using computed results
2023-07-02 10:34:25,861 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.80947073287007}
2023-07-02 10:34:25,861 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:25,861 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4644212829912632, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:25,861 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:25,881 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.43147
2023-07-02 10:34:25,881 [model] Computed derived parameters: {}
2023-07-02 10:34:25,882 [model] Posterior to be computed for parameters {'Omega_m': 0.3081335792428361, 'b1': 0.5120145178222171}
2023-07-02 10:34:25,882 [prior] Evaluating prior at array([0.30813358, 0.51201452])
2023-07-02 10:34:25,882 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:25,882 [model] Got input parameters: {'Omega_m': 0.3081335792428361, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5120145178222171, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:25,882 [classy] Got parameters {'Omega_m': 0.3081335792428361, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:25,882 [classy] Computing new state
2023-07-02 10:34:25,882 [classy] Setting parameters: {'Omega_m': 0.3081335792428361, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:25,928 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.78686425001317}
2023-07-02 10:34:25,928 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:25,930 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00137571
2023-07-02 10:34:25,930 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5120145178222171, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:25,930 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:25,949 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.63647
2023-07-02 10:34:25,949 [model] Computed derived parameters: {}
2023-07-02 10:34:25,949 [mcmc] New sample, #652:
Omega_m:0.3079481, b1:0.5123225
2023-07-02 10:34:25,950 [model] Posterior to be computed for parameters {'Omega_m': 0.3081335792428361, 'b1': 0.4964335927346454}
2023-07-02 10:34:25,950 [prior] Evaluating prior at array([0.30813358, 0.49643359])
2023-07-02 10:34:25,950 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:25,950 [model] Got input parameters: {'Omega_m': 0.3081335792428361, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4964335927346454, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:25,950 [classy] Got parameters {'Omega_m': 0.3081335792428361, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:25,950 [classy] Re-using computed results
2023-07-02 10:34:25,950 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.78686425001317}
2023-07-02 10:34:25,950 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:25,950 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4964335927346454, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:25,950 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:25,969 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.93107
2023-07-02 10:34:25,969 [model] Computed derived parameters: {}
2023-07-02 10:34:25,969 [model] Posterior to be computed for parameters {'Omega_m': 0.3159191734807206, 'b1': 0.4990900485042484}
2023-07-02 10:34:25,969 [prior] Evaluating prior at array([0.31591917, 0.49909005])
2023-07-02 10:34:25,970 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:25,970 [model] Got input parameters: {'Omega_m': 0.3159191734807206, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4990900485042484, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:25,970 [classy] Got parameters {'Omega_m': 0.3159191734807206, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:25,970 [classy] Computing new state
2023-07-02 10:34:25,970 [classy] Setting parameters: {'Omega_m': 0.3159191734807206, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:26,016 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.84877774018676}
2023-07-02 10:34:26,016 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:26,018 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000919939
2023-07-02 10:34:26,018 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4990900485042484, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:26,018 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:26,038 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.92331
2023-07-02 10:34:26,038 [model] Computed derived parameters: {}
2023-07-02 10:34:26,038 [mcmc] New sample, #653:
Omega_m:0.3081336, b1:0.5120145
2023-07-02 10:34:26,039 [model] Posterior to be computed for parameters {'Omega_m': 0.3159191734807206, 'b1': 0.40318878978431283}
2023-07-02 10:34:26,039 [prior] Evaluating prior at array([0.31591917, 0.40318879])
2023-07-02 10:34:26,039 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:26,039 [model] Got input parameters: {'Omega_m': 0.3159191734807206, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.40318878978431283, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:26,039 [classy] Got parameters {'Omega_m': 0.3159191734807206, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:26,039 [classy] Re-using computed results
2023-07-02 10:34:26,039 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.84877774018676}
2023-07-02 10:34:26,039 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:26,039 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.40318878978431283, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:26,039 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:26,058 [fs_likelihood.fslikelihood] Computed log-likelihood = -19.4012
2023-07-02 10:34:26,058 [model] Computed derived parameters: {}
2023-07-02 10:34:26,059 [model] Posterior to be computed for parameters {'Omega_m': 0.32222400051027866, 'b1': 0.4886237255738662}
2023-07-02 10:34:26,059 [prior] Evaluating prior at array([0.322224 , 0.48862373])
2023-07-02 10:34:26,059 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:26,059 [model] Got input parameters: {'Omega_m': 0.32222400051027866, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4886237255738662, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:26,059 [classy] Got parameters {'Omega_m': 0.32222400051027866, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:26,059 [classy] Computing new state
2023-07-02 10:34:26,059 [classy] Setting parameters: {'Omega_m': 0.32222400051027866, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:26,105 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.1041119058428}
2023-07-02 10:34:26,105 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:26,107 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00588131
2023-07-02 10:34:26,107 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4886237255738662, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:26,107 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:26,127 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.65162
2023-07-02 10:34:26,128 [model] Computed derived parameters: {}
2023-07-02 10:34:26,128 [mcmc] New sample, #654:
Omega_m:0.3159192, b1:0.49909
2023-07-02 10:34:26,128 [model] Posterior to be computed for parameters {'Omega_m': 0.32222400051027866, 'b1': 0.459444787556578}
2023-07-02 10:34:26,128 [prior] Evaluating prior at array([0.322224 , 0.45944479])
2023-07-02 10:34:26,128 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:26,128 [model] Got input parameters: {'Omega_m': 0.32222400051027866, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.459444787556578, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:26,128 [classy] Got parameters {'Omega_m': 0.32222400051027866, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:26,128 [classy] Re-using computed results
2023-07-02 10:34:26,128 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.1041119058428}
2023-07-02 10:34:26,128 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:26,128 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.459444787556578, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:26,128 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:26,158 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.618233
2023-07-02 10:34:26,158 [model] Computed derived parameters: {}
2023-07-02 10:34:26,158 [model] Posterior to be computed for parameters {'Omega_m': 0.3536381417562883, 'b1': 0.43647470620823503}
2023-07-02 10:34:26,158 [prior] Evaluating prior at array([0.35363814, 0.43647471])
2023-07-02 10:34:26,158 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:26,158 [model] Got input parameters: {'Omega_m': 0.3536381417562883, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.43647470620823503, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:26,158 [classy] Got parameters {'Omega_m': 0.3536381417562883, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:26,158 [classy] Computing new state
2023-07-02 10:34:26,158 [classy] Setting parameters: {'Omega_m': 0.3536381417562883, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:26,204 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.57893199995527}
2023-07-02 10:34:26,204 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:26,206 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0943107
2023-07-02 10:34:26,206 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.43647470620823503, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:26,206 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:26,225 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.22908
2023-07-02 10:34:26,225 [model] Computed derived parameters: {}
2023-07-02 10:34:26,226 [model] Posterior to be computed for parameters {'Omega_m': 0.32222400051027866, 'b1': 0.5267836238332567}
2023-07-02 10:34:26,226 [prior] Evaluating prior at array([0.322224 , 0.52678362])
2023-07-02 10:34:26,226 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:26,226 [model] Got input parameters: {'Omega_m': 0.32222400051027866, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5267836238332567, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:26,226 [classy] Got parameters {'Omega_m': 0.32222400051027866, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:26,226 [classy] Re-using computed results
2023-07-02 10:34:26,226 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.1041119058428}
2023-07-02 10:34:26,226 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:26,226 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5267836238332567, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:26,226 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:26,246 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.7589
2023-07-02 10:34:26,246 [model] Computed derived parameters: {}
2023-07-02 10:34:26,246 [model] Posterior to be computed for parameters {'Omega_m': 0.34812448864411255, 'b1': 0.44562764152709394}
2023-07-02 10:34:26,246 [prior] Evaluating prior at array([0.34812449, 0.44562764])
2023-07-02 10:34:26,246 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:26,246 [model] Got input parameters: {'Omega_m': 0.34812448864411255, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44562764152709394, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:26,246 [classy] Got parameters {'Omega_m': 0.34812448864411255, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:26,246 [classy] Computing new state
2023-07-02 10:34:26,246 [classy] Setting parameters: {'Omega_m': 0.34812448864411255, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:26,292 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.1764455031036}
2023-07-02 10:34:26,292 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:26,294 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0716915
2023-07-02 10:34:26,294 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44562764152709394, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:26,294 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:26,313 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.45012
2023-07-02 10:34:26,313 [model] Computed derived parameters: {}
2023-07-02 10:34:26,314 [model] Posterior to be computed for parameters {'Omega_m': 0.32222400051027866, 'b1': 0.47337002743556816}
2023-07-02 10:34:26,314 [prior] Evaluating prior at array([0.322224 , 0.47337003])
2023-07-02 10:34:26,314 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:26,314 [model] Got input parameters: {'Omega_m': 0.32222400051027866, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47337002743556816, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:26,314 [classy] Got parameters {'Omega_m': 0.32222400051027866, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:26,314 [classy] Re-using computed results
2023-07-02 10:34:26,314 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.1041119058428}
2023-07-02 10:34:26,314 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:26,314 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47337002743556816, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:26,314 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:26,333 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.14202
2023-07-02 10:34:26,334 [model] Computed derived parameters: {}
2023-07-02 10:34:26,334 [mcmc] New sample, #655:
Omega_m:0.322224, b1:0.4886237
2023-07-02 10:34:26,334 [model] Posterior to be computed for parameters {'Omega_m': 0.3332632803916596, 'b1': 0.4550442799383361}
2023-07-02 10:34:26,334 [prior] Evaluating prior at array([0.33326328, 0.45504428])
2023-07-02 10:34:26,334 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:26,334 [model] Got input parameters: {'Omega_m': 0.3332632803916596, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4550442799383361, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:26,334 [classy] Got parameters {'Omega_m': 0.3332632803916596, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:26,334 [classy] Computing new state
2023-07-02 10:34:26,334 [classy] Setting parameters: {'Omega_m': 0.3332632803916596, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:26,380 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.83112799168265}
2023-07-02 10:34:26,380 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:26,381 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0253701
2023-07-02 10:34:26,381 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4550442799383361, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:26,382 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:26,401 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.822697
2023-07-02 10:34:26,401 [model] Computed derived parameters: {}
2023-07-02 10:34:26,401 [model] Posterior to be computed for parameters {'Omega_m': 0.32222400051027866, 'b1': 0.47985304491470115}
2023-07-02 10:34:26,401 [prior] Evaluating prior at array([0.322224 , 0.47985304])
2023-07-02 10:34:26,401 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:26,402 [model] Got input parameters: {'Omega_m': 0.32222400051027866, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47985304491470115, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:26,402 [classy] Got parameters {'Omega_m': 0.32222400051027866, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:26,402 [classy] Re-using computed results
2023-07-02 10:34:26,402 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.1041119058428}
2023-07-02 10:34:26,402 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:26,402 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47985304491470115, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:26,402 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:26,421 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.50986
2023-07-02 10:34:26,421 [model] Computed derived parameters: {}
2023-07-02 10:34:26,421 [mcmc] New sample, #656:
Omega_m:0.322224, b1:0.47337
2023-07-02 10:34:26,421 [model] Posterior to be computed for parameters {'Omega_m': 0.3759788387536629, 'b1': 0.39061736985365847}
2023-07-02 10:34:26,421 [prior] Evaluating prior at array([0.37597884, 0.39061737])
2023-07-02 10:34:26,421 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:26,421 [model] Got input parameters: {'Omega_m': 0.3759788387536629, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.39061736985365847, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:26,421 [classy] Got parameters {'Omega_m': 0.3759788387536629, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:26,421 [classy] Computing new state
2023-07-02 10:34:26,421 [classy] Setting parameters: {'Omega_m': 0.3759788387536629, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:26,472 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.24277616946878}
2023-07-02 10:34:26,473 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:26,475 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.213186
2023-07-02 10:34:26,475 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.39061736985365847, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:26,476 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:26,505 [fs_likelihood.fslikelihood] Computed log-likelihood = -13.1038
2023-07-02 10:34:26,506 [model] Computed derived parameters: {}
2023-07-02 10:34:26,506 [model] Posterior to be computed for parameters {'Omega_m': 0.32222400051027866, 'b1': 0.46853041511335153}
2023-07-02 10:34:26,506 [prior] Evaluating prior at array([0.322224 , 0.46853042])
2023-07-02 10:34:26,506 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:26,506 [model] Got input parameters: {'Omega_m': 0.32222400051027866, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46853041511335153, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:26,506 [classy] Got parameters {'Omega_m': 0.32222400051027866, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:26,506 [classy] Re-using computed results
2023-07-02 10:34:26,506 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.1041119058428}
2023-07-02 10:34:26,506 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:26,506 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46853041511335153, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:26,506 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:26,536 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.72463
2023-07-02 10:34:26,536 [model] Computed derived parameters: {}
2023-07-02 10:34:26,536 [mcmc] New sample, #657:
Omega_m:0.322224, b1:0.479853
2023-07-02 10:34:26,536 [model] Posterior to be computed for parameters {'Omega_m': 0.33298331747475146, 'b1': 0.4506694198263157}
2023-07-02 10:34:26,536 [prior] Evaluating prior at array([0.33298332, 0.45066942])
2023-07-02 10:34:26,536 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:26,536 [model] Got input parameters: {'Omega_m': 0.33298331747475146, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4506694198263157, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:26,536 [classy] Got parameters {'Omega_m': 0.33298331747475146, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:26,536 [classy] Computing new state
2023-07-02 10:34:26,536 [classy] Setting parameters: {'Omega_m': 0.33298331747475146, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:26,585 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.8629400222411}
2023-07-02 10:34:26,586 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:26,587 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0247128
2023-07-02 10:34:26,588 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4506694198263157, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:26,588 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:26,608 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.49024
2023-07-02 10:34:26,608 [model] Computed derived parameters: {}
2023-07-02 10:34:26,608 [model] Posterior to be computed for parameters {'Omega_m': 0.32222400051027866, 'b1': 0.477830742568947}
2023-07-02 10:34:26,608 [prior] Evaluating prior at array([0.322224 , 0.47783074])
2023-07-02 10:34:26,608 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:26,608 [model] Got input parameters: {'Omega_m': 0.32222400051027866, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.477830742568947, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:26,608 [classy] Got parameters {'Omega_m': 0.32222400051027866, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:26,608 [classy] Re-using computed results
2023-07-02 10:34:26,608 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.1041119058428}
2023-07-02 10:34:26,608 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:26,608 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.477830742568947, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:26,608 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:26,630 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.41885
2023-07-02 10:34:26,630 [model] Computed derived parameters: {}
2023-07-02 10:34:26,630 [mcmc] New sample, #658:
Omega_m:0.322224, b1:0.4685304
2023-07-02 10:34:26,630 [model] Posterior to be computed for parameters {'Omega_m': 0.411455357690119, 'b1': 0.32970230139489043}
2023-07-02 10:34:26,630 [prior] Evaluating prior at array([0.41145536, 0.3297023 ])
2023-07-02 10:34:26,630 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:26,630 [model] Got input parameters: {'Omega_m': 0.411455357690119, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.32970230139489043, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:26,630 [classy] Got parameters {'Omega_m': 0.411455357690119, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:26,630 [classy] Computing new state
2023-07-02 10:34:26,630 [classy] Setting parameters: {'Omega_m': 0.411455357690119, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:26,678 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 136.7882417086518}
2023-07-02 10:34:26,678 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:26,680 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.479592
2023-07-02 10:34:26,680 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.32970230139489043, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:26,680 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:26,700 [fs_likelihood.fslikelihood] Computed log-likelihood = -31.536
2023-07-02 10:34:26,700 [model] Computed derived parameters: {}
2023-07-02 10:34:26,700 [model] Posterior to be computed for parameters {'Omega_m': 0.32222400051027866, 'b1': 0.5310828142991628}
2023-07-02 10:34:26,700 [prior] Evaluating prior at array([0.322224 , 0.53108281])
2023-07-02 10:34:26,700 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:26,700 [model] Got input parameters: {'Omega_m': 0.32222400051027866, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5310828142991628, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:26,700 [classy] Got parameters {'Omega_m': 0.32222400051027866, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:26,700 [classy] Re-using computed results
2023-07-02 10:34:26,700 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.1041119058428}
2023-07-02 10:34:26,700 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:26,700 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5310828142991628, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:26,700 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:26,720 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.7945
2023-07-02 10:34:26,720 [model] Computed derived parameters: {}
2023-07-02 10:34:26,720 [model] Posterior to be computed for parameters {'Omega_m': 0.3158117417123645, 'b1': 0.488475407518123}
2023-07-02 10:34:26,720 [prior] Evaluating prior at array([0.31581174, 0.48847541])
2023-07-02 10:34:26,720 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:26,720 [model] Got input parameters: {'Omega_m': 0.3158117417123645, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.488475407518123, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:26,720 [classy] Got parameters {'Omega_m': 0.3158117417123645, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:26,720 [classy] Computing new state
2023-07-02 10:34:26,720 [classy] Setting parameters: {'Omega_m': 0.3158117417123645, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:26,767 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.8615837788733}
2023-07-02 10:34:26,767 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:26,769 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000875919
2023-07-02 10:34:26,769 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.488475407518123, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:26,769 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:26,788 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.63584
2023-07-02 10:34:26,788 [model] Computed derived parameters: {}
2023-07-02 10:34:26,788 [mcmc] New sample, #659:
Omega_m:0.322224, b1:0.4778307
2023-07-02 10:34:26,789 [model] Posterior to be computed for parameters {'Omega_m': 0.3158117417123645, 'b1': 0.46507094795764364}
2023-07-02 10:34:26,789 [prior] Evaluating prior at array([0.31581174, 0.46507095])
2023-07-02 10:34:26,789 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:26,789 [model] Got input parameters: {'Omega_m': 0.3158117417123645, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46507094795764364, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:26,789 [classy] Got parameters {'Omega_m': 0.3158117417123645, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:26,789 [classy] Re-using computed results
2023-07-02 10:34:26,789 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.8615837788733}
2023-07-02 10:34:26,789 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:26,789 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46507094795764364, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:26,789 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:26,808 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.0550902
2023-07-02 10:34:26,809 [model] Computed derived parameters: {}
2023-07-02 10:34:26,809 [model] Posterior to be computed for parameters {'Omega_m': 0.33629002383698603, 'b1': 0.4544804521020681}
2023-07-02 10:34:26,809 [prior] Evaluating prior at array([0.33629002, 0.45448045])
2023-07-02 10:34:26,809 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:26,809 [model] Got input parameters: {'Omega_m': 0.33629002383698603, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4544804521020681, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:26,809 [classy] Got parameters {'Omega_m': 0.33629002383698603, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:26,809 [classy] Computing new state
2023-07-02 10:34:26,809 [classy] Setting parameters: {'Omega_m': 0.33629002383698603, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:26,856 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.48876665234016}
2023-07-02 10:34:26,856 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:26,858 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0329978
2023-07-02 10:34:26,858 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4544804521020681, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:26,858 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:26,877 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.492623
2023-07-02 10:34:26,877 [model] Computed derived parameters: {}
2023-07-02 10:34:26,877 [model] Posterior to be computed for parameters {'Omega_m': 0.3158117417123645, 'b1': 0.48849094684824146}
2023-07-02 10:34:26,877 [prior] Evaluating prior at array([0.31581174, 0.48849095])
2023-07-02 10:34:26,878 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:26,878 [model] Got input parameters: {'Omega_m': 0.3158117417123645, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48849094684824146, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:26,878 [classy] Got parameters {'Omega_m': 0.3158117417123645, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:26,878 [classy] Re-using computed results
2023-07-02 10:34:26,878 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.8615837788733}
2023-07-02 10:34:26,878 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:26,878 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48849094684824146, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:26,878 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:26,897 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.6367
2023-07-02 10:34:26,898 [model] Computed derived parameters: {}
2023-07-02 10:34:26,898 [mcmc] New sample, #660:
Omega_m:0.3158117, b1:0.4884754
2023-07-02 10:34:26,898 [model] Posterior to be computed for parameters {'Omega_m': 0.3204177102300361, 'b1': 0.4808448125947368}
2023-07-02 10:34:26,898 [prior] Evaluating prior at array([0.32041771, 0.48084481])
2023-07-02 10:34:26,898 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:26,898 [model] Got input parameters: {'Omega_m': 0.3204177102300361, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4808448125947368, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:26,898 [classy] Got parameters {'Omega_m': 0.3204177102300361, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:26,898 [classy] Computing new state
2023-07-02 10:34:26,898 [classy] Setting parameters: {'Omega_m': 0.3204177102300361, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:26,945 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.31611911198027}
2023-07-02 10:34:26,945 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:26,947 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00398695
2023-07-02 10:34:26,947 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4808448125947368, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:26,947 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:26,966 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.52558
2023-07-02 10:34:26,966 [model] Computed derived parameters: {}
2023-07-02 10:34:26,966 [mcmc] New sample, #661:
Omega_m:0.3158117, b1:0.4884909
2023-07-02 10:34:26,967 [model] Posterior to be computed for parameters {'Omega_m': 0.3204177102300361, 'b1': 0.43676935405998435}
2023-07-02 10:34:26,967 [prior] Evaluating prior at array([0.32041771, 0.43676935])
2023-07-02 10:34:26,967 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:26,967 [model] Got input parameters: {'Omega_m': 0.3204177102300361, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.43676935405998435, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:26,967 [classy] Got parameters {'Omega_m': 0.3204177102300361, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:26,967 [classy] Re-using computed results
2023-07-02 10:34:26,967 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.31611911198027}
2023-07-02 10:34:26,967 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:26,967 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.43676935405998435, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:26,967 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:26,986 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.63541
2023-07-02 10:34:26,986 [model] Computed derived parameters: {}
2023-07-02 10:34:26,986 [model] Posterior to be computed for parameters {'Omega_m': 0.31743703255982736, 'b1': 0.48579288411224697}
2023-07-02 10:34:26,986 [prior] Evaluating prior at array([0.31743703, 0.48579288])
2023-07-02 10:34:26,987 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:26,987 [model] Got input parameters: {'Omega_m': 0.31743703255982736, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48579288411224697, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:26,987 [classy] Got parameters {'Omega_m': 0.31743703255982736, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:26,987 [classy] Computing new state
2023-07-02 10:34:26,987 [classy] Setting parameters: {'Omega_m': 0.31743703255982736, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:27,037 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.6683066025225}
2023-07-02 10:34:27,037 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:27,039 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00168832
2023-07-02 10:34:27,039 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48579288411224697, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:27,039 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:27,059 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.62411
2023-07-02 10:34:27,059 [model] Computed derived parameters: {}
2023-07-02 10:34:27,059 [mcmc] New sample, #662:
Omega_m:0.3204177, b1:0.4808448
2023-07-02 10:34:27,059 [model] Posterior to be computed for parameters {'Omega_m': 0.31743703255982736, 'b1': 0.5048650255043015}
2023-07-02 10:34:27,059 [prior] Evaluating prior at array([0.31743703, 0.50486503])
2023-07-02 10:34:27,059 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:27,059 [model] Got input parameters: {'Omega_m': 0.31743703255982736, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5048650255043015, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:27,059 [classy] Got parameters {'Omega_m': 0.31743703255982736, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:27,059 [classy] Re-using computed results
2023-07-02 10:34:27,060 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.6683066025225}
2023-07-02 10:34:27,060 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:27,060 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5048650255043015, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:27,060 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:27,079 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.6807
2023-07-02 10:34:27,079 [model] Computed derived parameters: {}
2023-07-02 10:34:27,079 [mcmc] New sample, #663:
Omega_m:0.317437, b1:0.4857929
2023-07-02 10:34:27,079 [model] Posterior to be computed for parameters {'Omega_m': 0.3392104508316875, 'b1': 0.46872008039110497}
2023-07-02 10:34:27,079 [prior] Evaluating prior at array([0.33921045, 0.46872008])
2023-07-02 10:34:27,079 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:27,079 [model] Got input parameters: {'Omega_m': 0.3392104508316875, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46872008039110497, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:27,079 [classy] Got parameters {'Omega_m': 0.3392104508316875, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:27,079 [classy] Computing new state
2023-07-02 10:34:27,079 [classy] Setting parameters: {'Omega_m': 0.3392104508316875, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:27,130 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.161056504803}
2023-07-02 10:34:27,130 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:27,132 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0412527
2023-07-02 10:34:27,133 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46872008039110497, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:27,133 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:27,156 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.418649
2023-07-02 10:34:27,156 [model] Computed derived parameters: {}
2023-07-02 10:34:27,156 [model] Posterior to be computed for parameters {'Omega_m': 0.31743703255982736, 'b1': 0.509268578774452}
2023-07-02 10:34:27,156 [prior] Evaluating prior at array([0.31743703, 0.50926858])
2023-07-02 10:34:27,156 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:27,156 [model] Got input parameters: {'Omega_m': 0.31743703255982736, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.509268578774452, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:27,157 [classy] Got parameters {'Omega_m': 0.31743703255982736, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:27,157 [classy] Re-using computed results
2023-07-02 10:34:27,157 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.6683066025225}
2023-07-02 10:34:27,157 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:27,157 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.509268578774452, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:27,157 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:27,178 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.41098
2023-07-02 10:34:27,178 [model] Computed derived parameters: {}
2023-07-02 10:34:27,179 [model] Posterior to be computed for parameters {'Omega_m': 0.32347521506249954, 'b1': 0.4948413456017014}
2023-07-02 10:34:27,179 [prior] Evaluating prior at array([0.32347522, 0.49484135])
2023-07-02 10:34:27,179 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:27,179 [model] Got input parameters: {'Omega_m': 0.32347521506249954, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4948413456017014, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:27,179 [classy] Got parameters {'Omega_m': 0.32347521506249954, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:27,179 [classy] Computing new state
2023-07-02 10:34:27,179 [classy] Setting parameters: {'Omega_m': 0.32347521506249954, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:27,227 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.95787736807372}
2023-07-02 10:34:27,227 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:27,229 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00741208
2023-07-02 10:34:27,230 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4948413456017014, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:27,230 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:27,252 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.28682
2023-07-02 10:34:27,252 [model] Computed derived parameters: {}
2023-07-02 10:34:27,252 [mcmc] New sample, #664:
Omega_m:0.317437, b1:0.504865
2023-07-02 10:34:27,252 [model] Posterior to be computed for parameters {'Omega_m': 0.32347521506249954, 'b1': 0.4777915370986712}
2023-07-02 10:34:27,252 [prior] Evaluating prior at array([0.32347522, 0.47779154])
2023-07-02 10:34:27,252 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:27,252 [model] Got input parameters: {'Omega_m': 0.32347521506249954, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4777915370986712, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:27,252 [classy] Got parameters {'Omega_m': 0.32347521506249954, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:27,252 [classy] Re-using computed results
2023-07-02 10:34:27,252 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.95787736807372}
2023-07-02 10:34:27,252 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:27,252 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4777915370986712, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:27,252 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:27,272 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.41519
2023-07-02 10:34:27,272 [model] Computed derived parameters: {}
2023-07-02 10:34:27,272 [mcmc] New sample, #665:
Omega_m:0.3234752, b1:0.4948413
2023-07-02 10:34:27,272 [model] Posterior to be computed for parameters {'Omega_m': 0.3613987522957856, 'b1': 0.414836600272471}
2023-07-02 10:34:27,272 [prior] Evaluating prior at array([0.36139875, 0.4148366 ])
2023-07-02 10:34:27,272 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:27,272 [model] Got input parameters: {'Omega_m': 0.3613987522957856, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.414836600272471, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:27,273 [classy] Got parameters {'Omega_m': 0.3613987522957856, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:27,273 [classy] Computing new state
2023-07-02 10:34:27,273 [classy] Setting parameters: {'Omega_m': 0.3613987522957856, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:27,319 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.75225975293353}
2023-07-02 10:34:27,319 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:27,321 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.130811
2023-07-02 10:34:27,321 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.414836600272471, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:27,321 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:27,341 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.94536
2023-07-02 10:34:27,341 [model] Computed derived parameters: {}
2023-07-02 10:34:27,341 [model] Posterior to be computed for parameters {'Omega_m': 0.32347521506249954, 'b1': 0.4541539673057772}
2023-07-02 10:34:27,341 [prior] Evaluating prior at array([0.32347522, 0.45415397])
2023-07-02 10:34:27,341 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:27,341 [model] Got input parameters: {'Omega_m': 0.32347521506249954, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4541539673057772, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:27,341 [classy] Got parameters {'Omega_m': 0.32347521506249954, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:27,341 [classy] Re-using computed results
2023-07-02 10:34:27,341 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.95787736807372}
2023-07-02 10:34:27,341 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:27,342 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4541539673057772, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:27,342 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:27,361 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.0531484
2023-07-02 10:34:27,361 [model] Computed derived parameters: {}
2023-07-02 10:34:27,362 [model] Posterior to be computed for parameters {'Omega_m': 0.300987281724381, 'b1': 0.5151226123605656}
2023-07-02 10:34:27,362 [prior] Evaluating prior at array([0.30098728, 0.51512261])
2023-07-02 10:34:27,362 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:27,362 [model] Got input parameters: {'Omega_m': 0.300987281724381, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5151226123605656, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:27,362 [classy] Got parameters {'Omega_m': 0.300987281724381, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:27,362 [classy] Computing new state
2023-07-02 10:34:27,362 [classy] Setting parameters: {'Omega_m': 0.300987281724381, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:27,408 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.66649284965064}
2023-07-02 10:34:27,408 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:27,410 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00854486
2023-07-02 10:34:27,410 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5151226123605656, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:27,410 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:27,430 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.42299
2023-07-02 10:34:27,430 [model] Computed derived parameters: {}
2023-07-02 10:34:27,430 [model] Posterior to be computed for parameters {'Omega_m': 0.32347521506249954, 'b1': 0.5085610802448892}
2023-07-02 10:34:27,430 [prior] Evaluating prior at array([0.32347522, 0.50856108])
2023-07-02 10:34:27,430 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:27,430 [model] Got input parameters: {'Omega_m': 0.32347521506249954, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5085610802448892, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:27,430 [classy] Got parameters {'Omega_m': 0.32347521506249954, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:27,430 [classy] Re-using computed results
2023-07-02 10:34:27,430 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.95787736807372}
2023-07-02 10:34:27,430 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:27,430 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5085610802448892, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:27,430 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:27,451 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.00579
2023-07-02 10:34:27,451 [model] Computed derived parameters: {}
2023-07-02 10:34:27,451 [model] Posterior to be computed for parameters {'Omega_m': 0.30782635576805834, 'b1': 0.5037694131133311}
2023-07-02 10:34:27,451 [prior] Evaluating prior at array([0.30782636, 0.50376941])
2023-07-02 10:34:27,451 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:27,451 [model] Got input parameters: {'Omega_m': 0.30782635576805834, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5037694131133311, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:27,451 [classy] Got parameters {'Omega_m': 0.30782635576805834, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:27,451 [classy] Computing new state
2023-07-02 10:34:27,451 [classy] Setting parameters: {'Omega_m': 0.30782635576805834, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:27,498 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.82431291899152}
2023-07-02 10:34:27,498 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:27,500 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00154834
2023-07-02 10:34:27,500 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5037694131133311, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:27,500 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:27,519 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.36746
2023-07-02 10:34:27,519 [model] Computed derived parameters: {}
2023-07-02 10:34:27,519 [model] Posterior to be computed for parameters {'Omega_m': 0.32347521506249954, 'b1': 0.5191033793095934}
2023-07-02 10:34:27,519 [prior] Evaluating prior at array([0.32347522, 0.51910338])
2023-07-02 10:34:27,519 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:27,520 [model] Got input parameters: {'Omega_m': 0.32347521506249954, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5191033793095934, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:27,520 [classy] Got parameters {'Omega_m': 0.32347521506249954, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:27,520 [classy] Re-using computed results
2023-07-02 10:34:27,520 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.95787736807372}
2023-07-02 10:34:27,520 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:27,520 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5191033793095934, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:27,520 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:27,539 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.721708
2023-07-02 10:34:27,539 [model] Computed derived parameters: {}
2023-07-02 10:34:27,539 [model] Posterior to be computed for parameters {'Omega_m': 0.32401597620154776, 'b1': 0.4768938470140827}
2023-07-02 10:34:27,539 [prior] Evaluating prior at array([0.32401598, 0.47689385])
2023-07-02 10:34:27,540 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:27,540 [model] Got input parameters: {'Omega_m': 0.32401597620154776, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4768938470140827, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:27,540 [classy] Got parameters {'Omega_m': 0.32401597620154776, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:27,540 [classy] Computing new state
2023-07-02 10:34:27,540 [classy] Setting parameters: {'Omega_m': 0.32401597620154776, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:27,586 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.89483143145048}
2023-07-02 10:34:27,586 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:27,588 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00812858
2023-07-02 10:34:27,588 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4768938470140827, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:27,588 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:27,608 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.36904
2023-07-02 10:34:27,608 [model] Computed derived parameters: {}
2023-07-02 10:34:27,608 [mcmc] New sample, #666:
Omega_m:0.3234752, b1:0.4777915
2023-07-02 10:34:27,608 [model] Posterior to be computed for parameters {'Omega_m': 0.32401597620154776, 'b1': 0.4501961613248355}
2023-07-02 10:34:27,608 [prior] Evaluating prior at array([0.32401598, 0.45019616])
2023-07-02 10:34:27,608 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:27,609 [model] Got input parameters: {'Omega_m': 0.32401597620154776, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4501961613248355, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:27,609 [classy] Got parameters {'Omega_m': 0.32401597620154776, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:27,609 [classy] Re-using computed results
2023-07-02 10:34:27,609 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.89483143145048}
2023-07-02 10:34:27,609 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:27,609 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4501961613248355, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:27,609 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:27,628 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.495073
2023-07-02 10:34:27,628 [model] Computed derived parameters: {}
2023-07-02 10:34:27,628 [model] Posterior to be computed for parameters {'Omega_m': 0.3300342481952417, 'b1': 0.4669032195355536}
2023-07-02 10:34:27,628 [prior] Evaluating prior at array([0.33003425, 0.46690322])
2023-07-02 10:34:27,628 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:27,628 [model] Got input parameters: {'Omega_m': 0.3300342481952417, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4669032195355536, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:27,628 [classy] Got parameters {'Omega_m': 0.3300342481952417, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:27,628 [classy] Computing new state
2023-07-02 10:34:27,628 [classy] Setting parameters: {'Omega_m': 0.3300342481952417, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:27,676 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.1994797898442}
2023-07-02 10:34:27,676 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:27,678 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0182963
2023-07-02 10:34:27,678 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4669032195355536, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:27,678 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:27,697 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.65958
2023-07-02 10:34:27,697 [model] Computed derived parameters: {}
2023-07-02 10:34:27,697 [mcmc] New sample, #667:
Omega_m:0.324016, b1:0.4768938
2023-07-02 10:34:27,697 [model] Posterior to be computed for parameters {'Omega_m': 0.3300342481952417, 'b1': 0.4937271729091959}
2023-07-02 10:34:27,697 [prior] Evaluating prior at array([0.33003425, 0.49372717])
2023-07-02 10:34:27,697 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:27,697 [model] Got input parameters: {'Omega_m': 0.3300342481952417, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4937271729091959, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:27,697 [classy] Got parameters {'Omega_m': 0.3300342481952417, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:27,697 [classy] Re-using computed results
2023-07-02 10:34:27,697 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.1994797898442}
2023-07-02 10:34:27,697 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:27,697 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4937271729091959, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:27,697 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:27,717 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.575068
2023-07-02 10:34:27,717 [model] Computed derived parameters: {}
2023-07-02 10:34:27,717 [mcmc] New sample, #668:
Omega_m:0.3300342, b1:0.4669032
2023-07-02 10:34:27,717 [model] Posterior to be computed for parameters {'Omega_m': 0.3555628740856584, 'b1': 0.451348398474087}
2023-07-02 10:34:27,718 [prior] Evaluating prior at array([0.35556287, 0.4513484 ])
2023-07-02 10:34:27,718 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:27,718 [model] Got input parameters: {'Omega_m': 0.3555628740856584, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.451348398474087, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:27,718 [classy] Got parameters {'Omega_m': 0.3555628740856584, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:27,718 [classy] Computing new state
2023-07-02 10:34:27,718 [classy] Setting parameters: {'Omega_m': 0.3555628740856584, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:27,764 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.3723564571013}
2023-07-02 10:34:27,764 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:27,766 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.102864
2023-07-02 10:34:27,766 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.451348398474087, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:27,766 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:27,786 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.46719
2023-07-02 10:34:27,786 [model] Computed derived parameters: {}
2023-07-02 10:34:27,786 [model] Posterior to be computed for parameters {'Omega_m': 0.3300342481952417, 'b1': 0.5133901763103446}
2023-07-02 10:34:27,786 [prior] Evaluating prior at array([0.33003425, 0.51339018])
2023-07-02 10:34:27,786 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:27,786 [model] Got input parameters: {'Omega_m': 0.3300342481952417, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5133901763103446, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:27,786 [classy] Got parameters {'Omega_m': 0.3300342481952417, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:27,786 [classy] Re-using computed results
2023-07-02 10:34:27,786 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.1994797898442}
2023-07-02 10:34:27,786 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:27,786 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5133901763103446, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:27,786 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:27,808 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.85844
2023-07-02 10:34:27,808 [model] Computed derived parameters: {}
2023-07-02 10:34:27,809 [model] Posterior to be computed for parameters {'Omega_m': 0.2945255713712757, 'b1': 0.5526733226969497}
2023-07-02 10:34:27,809 [prior] Evaluating prior at array([0.29452557, 0.55267332])
2023-07-02 10:34:27,809 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:27,809 [model] Got input parameters: {'Omega_m': 0.2945255713712757, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5526733226969497, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:27,809 [classy] Got parameters {'Omega_m': 0.2945255713712757, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:27,809 [classy] Computing new state
2023-07-02 10:34:27,810 [classy] Setting parameters: {'Omega_m': 0.2945255713712757, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:27,860 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.47782903336713}
2023-07-02 10:34:27,860 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:27,862 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0208988
2023-07-02 10:34:27,862 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5526733226969497, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:27,862 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:27,882 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.307783
2023-07-02 10:34:27,882 [model] Computed derived parameters: {}
2023-07-02 10:34:27,882 [model] Posterior to be computed for parameters {'Omega_m': 0.3300342481952417, 'b1': 0.49239712107443523}
2023-07-02 10:34:27,882 [prior] Evaluating prior at array([0.33003425, 0.49239712])
2023-07-02 10:34:27,882 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:27,882 [model] Got input parameters: {'Omega_m': 0.3300342481952417, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49239712107443523, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:27,882 [classy] Got parameters {'Omega_m': 0.3300342481952417, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:27,882 [classy] Re-using computed results
2023-07-02 10:34:27,882 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.1994797898442}
2023-07-02 10:34:27,882 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:27,882 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49239712107443523, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:27,882 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:27,902 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.7247
2023-07-02 10:34:27,902 [model] Computed derived parameters: {}
2023-07-02 10:34:27,902 [mcmc] New sample, #669:
Omega_m:0.3300342, b1:0.4937272
2023-07-02 10:34:27,902 [model] Posterior to be computed for parameters {'Omega_m': 0.3502426894010373, 'b1': 0.45885011485397653}
2023-07-02 10:34:27,902 [prior] Evaluating prior at array([0.35024269, 0.45885011])
2023-07-02 10:34:27,902 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:27,902 [model] Got input parameters: {'Omega_m': 0.3502426894010373, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45885011485397653, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:27,902 [classy] Got parameters {'Omega_m': 0.3502426894010373, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:27,902 [classy] Computing new state
2023-07-02 10:34:27,902 [classy] Setting parameters: {'Omega_m': 0.3502426894010373, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:27,948 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.9458781846698}
2023-07-02 10:34:27,949 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:27,950 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.080047
2023-07-02 10:34:27,950 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45885011485397653, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:27,950 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:27,970 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.42367
2023-07-02 10:34:27,970 [model] Computed derived parameters: {}
2023-07-02 10:34:27,971 [model] Posterior to be computed for parameters {'Omega_m': 0.3300342481952417, 'b1': 0.488145821476959}
2023-07-02 10:34:27,971 [prior] Evaluating prior at array([0.33003425, 0.48814582])
2023-07-02 10:34:27,971 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:27,971 [model] Got input parameters: {'Omega_m': 0.3300342481952417, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.488145821476959, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:27,971 [classy] Got parameters {'Omega_m': 0.3300342481952417, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:27,971 [classy] Re-using computed results
2023-07-02 10:34:27,971 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.1994797898442}
2023-07-02 10:34:27,971 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:27,971 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.488145821476959, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:27,971 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:27,990 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.13448
2023-07-02 10:34:27,990 [model] Computed derived parameters: {}
2023-07-02 10:34:27,990 [mcmc] New sample, #670:
Omega_m:0.3300342, b1:0.4923971
2023-07-02 10:34:27,991 [model] Posterior to be computed for parameters {'Omega_m': 0.3161238809807235, 'b1': 0.5112377151426849}
2023-07-02 10:34:27,991 [prior] Evaluating prior at array([0.31612388, 0.51123772])
2023-07-02 10:34:27,991 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:27,991 [model] Got input parameters: {'Omega_m': 0.3161238809807235, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5112377151426849, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:27,991 [classy] Got parameters {'Omega_m': 0.3161238809807235, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:27,991 [classy] Computing new state
2023-07-02 10:34:27,991 [classy] Setting parameters: {'Omega_m': 0.3161238809807235, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:28,038 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.82439463601958}
2023-07-02 10:34:28,038 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:28,040 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00100756
2023-07-02 10:34:28,040 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5112377151426849, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:28,040 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:28,060 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.46477
2023-07-02 10:34:28,060 [model] Computed derived parameters: {}
2023-07-02 10:34:28,060 [mcmc] New sample, #671:
Omega_m:0.3300342, b1:0.4881458
2023-07-02 10:34:28,061 [model] Posterior to be computed for parameters {'Omega_m': 0.3161238809807235, 'b1': 0.4948521415773958}
2023-07-02 10:34:28,061 [prior] Evaluating prior at array([0.31612388, 0.49485214])
2023-07-02 10:34:28,061 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:28,061 [model] Got input parameters: {'Omega_m': 0.3161238809807235, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4948521415773958, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:28,061 [classy] Got parameters {'Omega_m': 0.3161238809807235, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:28,061 [classy] Re-using computed results
2023-07-02 10:34:28,061 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.82439463601958}
2023-07-02 10:34:28,061 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:28,061 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4948521415773958, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:28,061 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:28,081 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.88975
2023-07-02 10:34:28,081 [model] Computed derived parameters: {}
2023-07-02 10:34:28,081 [mcmc] New sample, #672:
Omega_m:0.3161239, b1:0.5112377
2023-07-02 10:34:28,081 [model] Posterior to be computed for parameters {'Omega_m': 0.30818458792618164, 'b1': 0.5080317584896779}
2023-07-02 10:34:28,081 [prior] Evaluating prior at array([0.30818459, 0.50803176])
2023-07-02 10:34:28,081 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:28,081 [model] Got input parameters: {'Omega_m': 0.30818458792618164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5080317584896779, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:28,081 [classy] Got parameters {'Omega_m': 0.30818458792618164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:28,081 [classy] Computing new state
2023-07-02 10:34:28,081 [classy] Setting parameters: {'Omega_m': 0.30818458792618164, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:28,131 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.78064932286327}
2023-07-02 10:34:28,131 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:28,133 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00134821
2023-07-02 10:34:28,133 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5080317584896779, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:28,133 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:28,154 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.5837
2023-07-02 10:34:28,154 [model] Computed derived parameters: {}
2023-07-02 10:34:28,154 [mcmc] New sample, #673:
Omega_m:0.3161239, b1:0.4948521
2023-07-02 10:34:28,154 [model] Posterior to be computed for parameters {'Omega_m': 0.30818458792618164, 'b1': 0.4605028802481791}
2023-07-02 10:34:28,154 [prior] Evaluating prior at array([0.30818459, 0.46050288])
2023-07-02 10:34:28,154 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:28,154 [model] Got input parameters: {'Omega_m': 0.30818458792618164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4605028802481791, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:28,154 [classy] Got parameters {'Omega_m': 0.30818458792618164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:28,154 [classy] Re-using computed results
2023-07-02 10:34:28,154 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.78064932286327}
2023-07-02 10:34:28,154 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:28,154 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4605028802481791, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:28,154 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:28,175 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.28655
2023-07-02 10:34:28,175 [model] Computed derived parameters: {}
2023-07-02 10:34:28,175 [model] Posterior to be computed for parameters {'Omega_m': 0.2909433465217033, 'b1': 0.5366530671178064}
2023-07-02 10:34:28,175 [prior] Evaluating prior at array([0.29094335, 0.53665307])
2023-07-02 10:34:28,175 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:28,175 [model] Got input parameters: {'Omega_m': 0.2909433465217033, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5366530671178064, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:28,175 [classy] Got parameters {'Omega_m': 0.2909433465217033, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:28,175 [classy] Computing new state
2023-07-02 10:34:28,175 [classy] Setting parameters: {'Omega_m': 0.2909433465217033, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:28,222 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.93431215213093}
2023-07-02 10:34:28,222 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:28,224 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0302562
2023-07-02 10:34:28,224 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5366530671178064, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:28,224 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:28,243 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.87462
2023-07-02 10:34:28,243 [model] Computed derived parameters: {}
2023-07-02 10:34:28,244 [model] Posterior to be computed for parameters {'Omega_m': 0.30818458792618164, 'b1': 0.5122751487607266}
2023-07-02 10:34:28,244 [prior] Evaluating prior at array([0.30818459, 0.51227515])
2023-07-02 10:34:28,244 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:28,244 [model] Got input parameters: {'Omega_m': 0.30818458792618164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5122751487607266, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:28,244 [classy] Got parameters {'Omega_m': 0.30818458792618164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:28,244 [classy] Re-using computed results
2023-07-02 10:34:28,244 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.78064932286327}
2023-07-02 10:34:28,244 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:28,244 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5122751487607266, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:28,244 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:28,264 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.64187
2023-07-02 10:34:28,264 [model] Computed derived parameters: {}
2023-07-02 10:34:28,264 [mcmc] New sample, #674:
Omega_m:0.3081846, b1:0.5080318
2023-07-02 10:34:28,264 [model] Posterior to be computed for parameters {'Omega_m': 0.29329634312139774, 'b1': 0.5369903673167505}
2023-07-02 10:34:28,264 [prior] Evaluating prior at array([0.29329634, 0.53699037])
2023-07-02 10:34:28,264 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:28,264 [model] Got input parameters: {'Omega_m': 0.29329634312139774, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5369903673167505, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:28,264 [classy] Got parameters {'Omega_m': 0.29329634312139774, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:28,264 [classy] Computing new state
2023-07-02 10:34:28,264 [classy] Setting parameters: {'Omega_m': 0.29329634312139774, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:28,310 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.63392355470125}
2023-07-02 10:34:28,310 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:28,312 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0239042
2023-07-02 10:34:28,312 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5369903673167505, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:28,312 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:28,332 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.0483115
2023-07-02 10:34:28,332 [model] Computed derived parameters: {}
2023-07-02 10:34:28,332 [model] Posterior to be computed for parameters {'Omega_m': 0.30818458792618164, 'b1': 0.5263175419786233}
2023-07-02 10:34:28,332 [prior] Evaluating prior at array([0.30818459, 0.52631754])
2023-07-02 10:34:28,333 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:28,333 [model] Got input parameters: {'Omega_m': 0.30818458792618164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5263175419786233, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:28,333 [classy] Got parameters {'Omega_m': 0.30818458792618164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:28,333 [classy] Re-using computed results
2023-07-02 10:34:28,333 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.78064932286327}
2023-07-02 10:34:28,333 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:28,333 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5263175419786233, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:28,333 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:28,352 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.14083
2023-07-02 10:34:28,352 [model] Computed derived parameters: {}
2023-07-02 10:34:28,352 [model] Posterior to be computed for parameters {'Omega_m': 0.29853242946857, 'b1': 0.5282982064780871}
2023-07-02 10:34:28,352 [prior] Evaluating prior at array([0.29853243, 0.52829821])
2023-07-02 10:34:28,352 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:28,352 [model] Got input parameters: {'Omega_m': 0.29853242946857, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5282982064780871, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:28,353 [classy] Got parameters {'Omega_m': 0.29853242946857, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:28,353 [classy] Computing new state
2023-07-02 10:34:28,353 [classy] Setting parameters: {'Omega_m': 0.29853242946857, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:28,399 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.97291662000035}
2023-07-02 10:34:28,399 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:28,401 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0125655
2023-07-02 10:34:28,401 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5282982064780871, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:28,401 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:28,421 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.24304
2023-07-02 10:34:28,421 [model] Computed derived parameters: {}
2023-07-02 10:34:28,421 [model] Posterior to be computed for parameters {'Omega_m': 0.30818458792618164, 'b1': 0.5082847508536987}
2023-07-02 10:34:28,421 [prior] Evaluating prior at array([0.30818459, 0.50828475])
2023-07-02 10:34:28,421 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:28,421 [model] Got input parameters: {'Omega_m': 0.30818458792618164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5082847508536987, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:28,421 [classy] Got parameters {'Omega_m': 0.30818458792618164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:28,421 [classy] Re-using computed results
2023-07-02 10:34:28,421 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.78064932286327}
2023-07-02 10:34:28,421 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:28,421 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5082847508536987, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:28,421 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:28,441 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.58985
2023-07-02 10:34:28,441 [model] Computed derived parameters: {}
2023-07-02 10:34:28,441 [mcmc] New sample, #675:
Omega_m:0.3081846, b1:0.5122751
2023-07-02 10:34:28,441 [model] Posterior to be computed for parameters {'Omega_m': 0.3295320030870295, 'b1': 0.4728469918549347}
2023-07-02 10:34:28,441 [prior] Evaluating prior at array([0.329532 , 0.47284699])
2023-07-02 10:34:28,441 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:28,441 [model] Got input parameters: {'Omega_m': 0.3295320030870295, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4728469918549347, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:28,441 [classy] Got parameters {'Omega_m': 0.3295320030870295, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:28,441 [classy] Computing new state
2023-07-02 10:34:28,441 [classy] Setting parameters: {'Omega_m': 0.3295320030870295, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:28,488 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.25706610657542}
2023-07-02 10:34:28,488 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:28,489 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0172962
2023-07-02 10:34:28,490 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4728469918549347, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:28,490 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:28,509 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.83495
2023-07-02 10:34:28,509 [model] Computed derived parameters: {}
2023-07-02 10:34:28,509 [model] Posterior to be computed for parameters {'Omega_m': 0.30818458792618164, 'b1': 0.5191353964663232}
2023-07-02 10:34:28,509 [prior] Evaluating prior at array([0.30818459, 0.5191354 ])
2023-07-02 10:34:28,509 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:28,509 [model] Got input parameters: {'Omega_m': 0.30818458792618164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5191353964663232, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:28,509 [classy] Got parameters {'Omega_m': 0.30818458792618164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:28,509 [classy] Re-using computed results
2023-07-02 10:34:28,509 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.78064932286327}
2023-07-02 10:34:28,509 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:28,509 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5191353964663232, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:28,509 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:28,529 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.53164
2023-07-02 10:34:28,529 [model] Computed derived parameters: {}
2023-07-02 10:34:28,529 [mcmc] New sample, #676:
Omega_m:0.3081846, b1:0.5082848
2023-07-02 10:34:28,530 [model] Posterior to be computed for parameters {'Omega_m': 0.328691348921757, 'b1': 0.4850931647239397}
2023-07-02 10:34:28,530 [prior] Evaluating prior at array([0.32869135, 0.48509316])
2023-07-02 10:34:28,530 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:28,530 [model] Got input parameters: {'Omega_m': 0.328691348921757, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4850931647239397, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:28,530 [classy] Got parameters {'Omega_m': 0.328691348921757, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:28,530 [classy] Computing new state
2023-07-02 10:34:28,530 [classy] Setting parameters: {'Omega_m': 0.328691348921757, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:28,576 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.35364232550143}
2023-07-02 10:34:28,577 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:28,578 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0156831
2023-07-02 10:34:28,578 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4850931647239397, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:28,578 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:28,598 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.70637
2023-07-02 10:34:28,598 [model] Computed derived parameters: {}
2023-07-02 10:34:28,598 [model] Posterior to be computed for parameters {'Omega_m': 0.30818458792618164, 'b1': 0.4928617499551069}
2023-07-02 10:34:28,598 [prior] Evaluating prior at array([0.30818459, 0.49286175])
2023-07-02 10:34:28,598 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:28,598 [model] Got input parameters: {'Omega_m': 0.30818458792618164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4928617499551069, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:28,598 [classy] Got parameters {'Omega_m': 0.30818458792618164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:28,598 [classy] Re-using computed results
2023-07-02 10:34:28,598 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.78064932286327}
2023-07-02 10:34:28,598 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:28,598 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4928617499551069, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:28,598 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:28,618 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.60666
2023-07-02 10:34:28,618 [model] Computed derived parameters: {}
2023-07-02 10:34:28,618 [mcmc] New sample, #677:
Omega_m:0.3081846, b1:0.5191354
2023-07-02 10:34:28,619 [model] Posterior to be computed for parameters {'Omega_m': 0.3115782114424989, 'b1': 0.48722816802504}
2023-07-02 10:34:28,619 [prior] Evaluating prior at array([0.31157821, 0.48722817])
2023-07-02 10:34:28,619 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:28,619 [model] Got input parameters: {'Omega_m': 0.3115782114424989, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48722816802504, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:28,619 [classy] Got parameters {'Omega_m': 0.3115782114424989, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:28,619 [classy] Computing new state
2023-07-02 10:34:28,619 [classy] Setting parameters: {'Omega_m': 0.3115782114424989, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:28,665 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.36925905071544}
2023-07-02 10:34:28,665 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:28,667 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000252795
2023-07-02 10:34:28,667 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48722816802504, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:28,667 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:28,687 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.86713
2023-07-02 10:34:28,687 [model] Computed derived parameters: {}
2023-07-02 10:34:28,687 [mcmc] New sample, #678:
Omega_m:0.3081846, b1:0.4928617
2023-07-02 10:34:28,688 [model] Posterior to be computed for parameters {'Omega_m': 0.3115782114424989, 'b1': 0.4592189537722995}
2023-07-02 10:34:28,688 [prior] Evaluating prior at array([0.31157821, 0.45921895])
2023-07-02 10:34:28,688 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:28,688 [model] Got input parameters: {'Omega_m': 0.3115782114424989, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4592189537722995, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:28,688 [classy] Got parameters {'Omega_m': 0.3115782114424989, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:28,688 [classy] Re-using computed results
2023-07-02 10:34:28,688 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.36925905071544}
2023-07-02 10:34:28,688 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:28,688 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4592189537722995, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:28,688 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:28,707 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.88959
2023-07-02 10:34:28,707 [model] Computed derived parameters: {}
2023-07-02 10:34:28,707 [model] Posterior to be computed for parameters {'Omega_m': 0.3252947548256633, 'b1': 0.46445803145130765}
2023-07-02 10:34:28,707 [prior] Evaluating prior at array([0.32529475, 0.46445803])
2023-07-02 10:34:28,708 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:28,708 [model] Got input parameters: {'Omega_m': 0.3252947548256633, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46445803145130765, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:28,708 [classy] Got parameters {'Omega_m': 0.3252947548256633, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:28,708 [classy] Computing new state
2023-07-02 10:34:28,708 [classy] Setting parameters: {'Omega_m': 0.3252947548256633, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:28,754 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.7461182056545}
2023-07-02 10:34:28,754 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:28,756 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00995369
2023-07-02 10:34:28,756 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46445803145130765, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:28,756 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:28,776 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.58429
2023-07-02 10:34:28,776 [model] Computed derived parameters: {}
2023-07-02 10:34:28,776 [mcmc] New sample, #679:
Omega_m:0.3115782, b1:0.4872282
2023-07-02 10:34:28,776 [model] Posterior to be computed for parameters {'Omega_m': 0.3252947548256633, 'b1': 0.4654409403304877}
2023-07-02 10:34:28,776 [prior] Evaluating prior at array([0.32529475, 0.46544094])
2023-07-02 10:34:28,776 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:28,776 [model] Got input parameters: {'Omega_m': 0.3252947548256633, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4654409403304877, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:28,776 [classy] Got parameters {'Omega_m': 0.3252947548256633, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:28,777 [classy] Re-using computed results
2023-07-02 10:34:28,777 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.7461182056545}
2023-07-02 10:34:28,777 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:28,777 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4654409403304877, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:28,777 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:28,796 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.67151
2023-07-02 10:34:28,796 [model] Computed derived parameters: {}
2023-07-02 10:34:28,796 [mcmc] New sample, #680:
Omega_m:0.3252948, b1:0.464458
2023-07-02 10:34:28,796 [model] Posterior to be computed for parameters {'Omega_m': 0.35821203583268013, 'b1': 0.41079663503957375}
2023-07-02 10:34:28,796 [prior] Evaluating prior at array([0.35821204, 0.41079664])
2023-07-02 10:34:28,796 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:28,796 [model] Got input parameters: {'Omega_m': 0.35821203583268013, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.41079663503957375, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:28,796 [classy] Got parameters {'Omega_m': 0.35821203583268013, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:28,796 [classy] Computing new state
2023-07-02 10:34:28,797 [classy] Setting parameters: {'Omega_m': 0.35821203583268013, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:28,843 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.08970233560763}
2023-07-02 10:34:28,843 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:28,845 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.11518
2023-07-02 10:34:28,845 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.41079663503957375, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:28,845 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:28,865 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.11112
2023-07-02 10:34:28,865 [model] Computed derived parameters: {}
2023-07-02 10:34:28,865 [model] Posterior to be computed for parameters {'Omega_m': 0.3252947548256633, 'b1': 0.4736693811831151}
2023-07-02 10:34:28,865 [prior] Evaluating prior at array([0.32529475, 0.47366938])
2023-07-02 10:34:28,865 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:28,865 [model] Got input parameters: {'Omega_m': 0.3252947548256633, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4736693811831151, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:28,865 [classy] Got parameters {'Omega_m': 0.3252947548256633, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:28,865 [classy] Re-using computed results
2023-07-02 10:34:28,865 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.7461182056545}
2023-07-02 10:34:28,865 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:28,865 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4736693811831151, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:28,865 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:28,885 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.20394
2023-07-02 10:34:28,885 [model] Computed derived parameters: {}
2023-07-02 10:34:28,885 [mcmc] New sample, #681:
Omega_m:0.3252948, b1:0.4654409
2023-07-02 10:34:28,885 [model] Posterior to be computed for parameters {'Omega_m': 0.27926486118989297, 'b1': 0.5500812682950901}
2023-07-02 10:34:28,885 [prior] Evaluating prior at array([0.27926486, 0.55008127])
2023-07-02 10:34:28,886 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:28,886 [model] Got input parameters: {'Omega_m': 0.27926486118989297, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5500812682950901, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:28,886 [classy] Got parameters {'Omega_m': 0.27926486118989297, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:28,886 [classy] Computing new state
2023-07-02 10:34:28,886 [classy] Setting parameters: {'Omega_m': 0.27926486118989297, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:28,932 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.4570632109594}
2023-07-02 10:34:28,932 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:28,934 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.073905
2023-07-02 10:34:28,934 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5500812682950901, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:28,934 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:28,953 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.08541
2023-07-02 10:34:28,953 [model] Computed derived parameters: {}
2023-07-02 10:34:28,953 [model] Posterior to be computed for parameters {'Omega_m': 0.3252947548256633, 'b1': 0.46599749560486586}
2023-07-02 10:34:28,953 [prior] Evaluating prior at array([0.32529475, 0.4659975 ])
2023-07-02 10:34:28,953 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:28,954 [model] Got input parameters: {'Omega_m': 0.3252947548256633, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46599749560486586, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:28,954 [classy] Got parameters {'Omega_m': 0.3252947548256633, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:28,954 [classy] Re-using computed results
2023-07-02 10:34:28,954 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.7461182056545}
2023-07-02 10:34:28,954 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:28,954 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46599749560486586, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:28,954 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:28,973 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.71868
2023-07-02 10:34:28,973 [model] Computed derived parameters: {}
2023-07-02 10:34:28,973 [mcmc] New sample, #682:
Omega_m:0.3252948, b1:0.4736694
2023-07-02 10:34:28,973 [model] Posterior to be computed for parameters {'Omega_m': 0.37360684724760046, 'b1': 0.3857970462729653}
2023-07-02 10:34:28,974 [prior] Evaluating prior at array([0.37360685, 0.38579705])
2023-07-02 10:34:28,974 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:28,974 [model] Got input parameters: {'Omega_m': 0.37360684724760046, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.3857970462729653, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:28,974 [classy] Got parameters {'Omega_m': 0.37360684724760046, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:28,974 [classy] Computing new state
2023-07-02 10:34:28,974 [classy] Setting parameters: {'Omega_m': 0.37360684724760046, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:29,020 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.48459710060587}
2023-07-02 10:34:29,020 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:29,022 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.198613
2023-07-02 10:34:29,022 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.3857970462729653, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:29,022 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:29,042 [fs_likelihood.fslikelihood] Computed log-likelihood = -12.2688
2023-07-02 10:34:29,042 [model] Computed derived parameters: {}
2023-07-02 10:34:29,042 [model] Posterior to be computed for parameters {'Omega_m': 0.3252947548256633, 'b1': 0.45974265645886486}
2023-07-02 10:34:29,042 [prior] Evaluating prior at array([0.32529475, 0.45974266])
2023-07-02 10:34:29,042 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:29,042 [model] Got input parameters: {'Omega_m': 0.3252947548256633, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45974265645886486, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:29,042 [classy] Got parameters {'Omega_m': 0.3252947548256633, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:29,042 [classy] Re-using computed results
2023-07-02 10:34:29,042 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.7461182056545}
2023-07-02 10:34:29,042 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:29,042 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45974265645886486, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:29,042 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:29,062 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.09677
2023-07-02 10:34:29,062 [model] Computed derived parameters: {}
2023-07-02 10:34:29,062 [model] Posterior to be computed for parameters {'Omega_m': 0.35038457977314286, 'b1': 0.4243471523145616}
2023-07-02 10:34:29,062 [prior] Evaluating prior at array([0.35038458, 0.42434715])
2023-07-02 10:34:29,062 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:29,062 [model] Got input parameters: {'Omega_m': 0.35038457977314286, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4243471523145616, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:29,062 [classy] Got parameters {'Omega_m': 0.35038457977314286, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:29,062 [classy] Computing new state
2023-07-02 10:34:29,062 [classy] Setting parameters: {'Omega_m': 0.35038457977314286, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:29,108 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.9304799511133}
2023-07-02 10:34:29,108 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:29,110 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0806217
2023-07-02 10:34:29,110 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4243471523145616, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:29,110 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:29,133 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.46939
2023-07-02 10:34:29,134 [model] Computed derived parameters: {}
2023-07-02 10:34:29,134 [model] Posterior to be computed for parameters {'Omega_m': 0.3252947548256633, 'b1': 0.49052242499793525}
2023-07-02 10:34:29,134 [prior] Evaluating prior at array([0.32529475, 0.49052242])
2023-07-02 10:34:29,134 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:29,134 [model] Got input parameters: {'Omega_m': 0.3252947548256633, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49052242499793525, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:29,134 [classy] Got parameters {'Omega_m': 0.3252947548256633, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:29,134 [classy] Re-using computed results
2023-07-02 10:34:29,134 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.7461182056545}
2023-07-02 10:34:29,134 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:29,134 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49052242499793525, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:29,134 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:29,158 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.16176
2023-07-02 10:34:29,158 [model] Computed derived parameters: {}
2023-07-02 10:34:29,158 [mcmc] New sample, #683:
Omega_m:0.3252948, b1:0.4659975
2023-07-02 10:34:29,158 [model] Posterior to be computed for parameters {'Omega_m': 0.3295028183558439, 'b1': 0.48353683259199703}
2023-07-02 10:34:29,158 [prior] Evaluating prior at array([0.32950282, 0.48353683])
2023-07-02 10:34:29,158 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:29,158 [model] Got input parameters: {'Omega_m': 0.3295028183558439, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48353683259199703, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:29,158 [classy] Got parameters {'Omega_m': 0.3295028183558439, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:29,158 [classy] Computing new state
2023-07-02 10:34:29,158 [classy] Setting parameters: {'Omega_m': 0.3295028183558439, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:29,205 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.26041568284825}
2023-07-02 10:34:29,206 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:29,207 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0172389
2023-07-02 10:34:29,207 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48353683259199703, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:29,207 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:29,227 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.5947
2023-07-02 10:34:29,227 [model] Computed derived parameters: {}
2023-07-02 10:34:29,227 [mcmc] New sample, #684:
Omega_m:0.3252948, b1:0.4905224
2023-07-02 10:34:29,228 [model] Posterior to be computed for parameters {'Omega_m': 0.3295028183558439, 'b1': 0.46601786264738176}
2023-07-02 10:34:29,228 [prior] Evaluating prior at array([0.32950282, 0.46601786])
2023-07-02 10:34:29,228 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:29,228 [model] Got input parameters: {'Omega_m': 0.3295028183558439, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46601786264738176, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:29,228 [classy] Got parameters {'Omega_m': 0.3295028183558439, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:29,228 [classy] Re-using computed results
2023-07-02 10:34:29,228 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.26041568284825}
2023-07-02 10:34:29,228 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:29,228 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46601786264738176, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:29,228 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:29,248 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.66803
2023-07-02 10:34:29,248 [model] Computed derived parameters: {}
2023-07-02 10:34:29,248 [mcmc] New sample, #685:
Omega_m:0.3295028, b1:0.4835368
2023-07-02 10:34:29,248 [model] Posterior to be computed for parameters {'Omega_m': 0.38527693751726805, 'b1': 0.37343008195738486}
2023-07-02 10:34:29,248 [prior] Evaluating prior at array([0.38527694, 0.37343008])
2023-07-02 10:34:29,248 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:29,248 [model] Got input parameters: {'Omega_m': 0.38527693751726805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.37343008195738486, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:29,248 [classy] Got parameters {'Omega_m': 0.38527693751726805, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:29,248 [classy] Computing new state
2023-07-02 10:34:29,248 [classy] Setting parameters: {'Omega_m': 0.38527693751726805, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:29,295 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 139.30850046681243}
2023-07-02 10:34:29,295 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:29,297 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.274456
2023-07-02 10:34:29,297 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.37343008195738486, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:29,297 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:29,316 [fs_likelihood.fslikelihood] Computed log-likelihood = -17.5471
2023-07-02 10:34:29,316 [model] Computed derived parameters: {}
2023-07-02 10:34:29,316 [model] Posterior to be computed for parameters {'Omega_m': 0.3295028183558439, 'b1': 0.5306528399301558}
2023-07-02 10:34:29,317 [prior] Evaluating prior at array([0.32950282, 0.53065284])
2023-07-02 10:34:29,317 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:29,317 [model] Got input parameters: {'Omega_m': 0.3295028183558439, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5306528399301558, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:29,317 [classy] Got parameters {'Omega_m': 0.3295028183558439, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:29,317 [classy] Re-using computed results
2023-07-02 10:34:29,317 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.26041568284825}
2023-07-02 10:34:29,317 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:29,317 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5306528399301558, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:29,317 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:29,337 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.41924
2023-07-02 10:34:29,337 [model] Computed derived parameters: {}
2023-07-02 10:34:29,337 [model] Posterior to be computed for parameters {'Omega_m': 0.2944792283675266, 'b1': 0.5241587444321636}
2023-07-02 10:34:29,337 [prior] Evaluating prior at array([0.29447923, 0.52415874])
2023-07-02 10:34:29,337 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:29,337 [model] Got input parameters: {'Omega_m': 0.2944792283675266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5241587444321636, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:29,337 [classy] Got parameters {'Omega_m': 0.2944792283675266, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:29,337 [classy] Computing new state
2023-07-02 10:34:29,337 [classy] Setting parameters: {'Omega_m': 0.2944792283675266, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:29,384 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.4837030668277}
2023-07-02 10:34:29,384 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:29,386 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0210083
2023-07-02 10:34:29,386 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5241587444321636, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:29,386 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:29,405 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.175151
2023-07-02 10:34:29,405 [model] Computed derived parameters: {}
2023-07-02 10:34:29,405 [model] Posterior to be computed for parameters {'Omega_m': 0.3295028183558439, 'b1': 0.40508761705818375}
2023-07-02 10:34:29,405 [prior] Evaluating prior at array([0.32950282, 0.40508762])
2023-07-02 10:34:29,405 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:29,406 [model] Got input parameters: {'Omega_m': 0.3295028183558439, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.40508761705818375, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:29,406 [classy] Got parameters {'Omega_m': 0.3295028183558439, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:29,406 [classy] Re-using computed results
2023-07-02 10:34:29,406 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.26041568284825}
2023-07-02 10:34:29,406 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:29,406 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.40508761705818375, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:29,406 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:29,425 [fs_likelihood.fslikelihood] Computed log-likelihood = -10.2641
2023-07-02 10:34:29,425 [model] Computed derived parameters: {}
2023-07-02 10:34:29,425 [model] Posterior to be computed for parameters {'Omega_m': 0.3194870274705619, 'b1': 0.4826445680775367}
2023-07-02 10:34:29,425 [prior] Evaluating prior at array([0.31948703, 0.48264457])
2023-07-02 10:34:29,425 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:29,425 [model] Got input parameters: {'Omega_m': 0.3194870274705619, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4826445680775367, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:29,426 [classy] Got parameters {'Omega_m': 0.3194870274705619, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:29,426 [classy] Computing new state
2023-07-02 10:34:29,426 [classy] Setting parameters: {'Omega_m': 0.3194870274705619, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:29,472 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.4257706174018}
2023-07-02 10:34:29,472 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:29,474 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00315786
2023-07-02 10:34:29,474 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4826445680775367, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:29,474 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:29,494 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.57983
2023-07-02 10:34:29,494 [model] Computed derived parameters: {}
2023-07-02 10:34:29,494 [mcmc] New sample, #686:
Omega_m:0.3295028, b1:0.4660179
2023-07-02 10:34:29,494 [model] Posterior to be computed for parameters {'Omega_m': 0.3194870274705619, 'b1': 0.4391179894855841}
2023-07-02 10:34:29,495 [prior] Evaluating prior at array([0.31948703, 0.43911799])
2023-07-02 10:34:29,495 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:29,495 [model] Got input parameters: {'Omega_m': 0.3194870274705619, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4391179894855841, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:29,495 [classy] Got parameters {'Omega_m': 0.3194870274705619, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:29,495 [classy] Re-using computed results
2023-07-02 10:34:29,495 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.4257706174018}
2023-07-02 10:34:29,495 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:29,495 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4391179894855841, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:29,495 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:29,514 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.40503
2023-07-02 10:34:29,514 [model] Computed derived parameters: {}
2023-07-02 10:34:29,515 [model] Posterior to be computed for parameters {'Omega_m': 0.3407379655303091, 'b1': 0.4473669658111894}
2023-07-02 10:34:29,515 [prior] Evaluating prior at array([0.34073797, 0.44736697])
2023-07-02 10:34:29,515 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:29,515 [model] Got input parameters: {'Omega_m': 0.3407379655303091, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4473669658111894, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:29,515 [classy] Got parameters {'Omega_m': 0.3407379655303091, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:29,515 [classy] Computing new state
2023-07-02 10:34:29,515 [classy] Setting parameters: {'Omega_m': 0.3407379655303091, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:29,561 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.99066356827603}
2023-07-02 10:34:29,562 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:29,563 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0459144
2023-07-02 10:34:29,563 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4473669658111894, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:29,563 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:29,584 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.477776
2023-07-02 10:34:29,584 [model] Computed derived parameters: {}
2023-07-02 10:34:29,584 [model] Posterior to be computed for parameters {'Omega_m': 0.3194870274705619, 'b1': 0.5017006218552754}
2023-07-02 10:34:29,584 [prior] Evaluating prior at array([0.31948703, 0.50170062])
2023-07-02 10:34:29,584 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:29,584 [model] Got input parameters: {'Omega_m': 0.3194870274705619, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5017006218552754, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:29,584 [classy] Got parameters {'Omega_m': 0.3194870274705619, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:29,584 [classy] Re-using computed results
2023-07-02 10:34:29,584 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.4257706174018}
2023-07-02 10:34:29,584 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:29,584 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5017006218552754, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:29,584 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:29,604 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.57836
2023-07-02 10:34:29,604 [model] Computed derived parameters: {}
2023-07-02 10:34:29,604 [mcmc] New sample, #687:
Omega_m:0.319487, b1:0.4826446
2023-07-02 10:34:29,604 [model] Posterior to be computed for parameters {'Omega_m': 0.276657160856017, 'b1': 0.5728003067398022}
2023-07-02 10:34:29,604 [prior] Evaluating prior at array([0.27665716, 0.57280031])
2023-07-02 10:34:29,604 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:29,604 [model] Got input parameters: {'Omega_m': 0.276657160856017, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5728003067398022, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:29,604 [classy] Got parameters {'Omega_m': 0.276657160856017, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:29,604 [classy] Computing new state
2023-07-02 10:34:29,604 [classy] Setting parameters: {'Omega_m': 0.276657160856017, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:29,651 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.80453124860398}
2023-07-02 10:34:29,652 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:29,653 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0865281
2023-07-02 10:34:29,653 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5728003067398022, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:29,653 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:29,673 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.90742
2023-07-02 10:34:29,673 [model] Computed derived parameters: {}
2023-07-02 10:34:29,673 [model] Posterior to be computed for parameters {'Omega_m': 0.3194870274705619, 'b1': 0.5540754427149882}
2023-07-02 10:34:29,673 [prior] Evaluating prior at array([0.31948703, 0.55407544])
2023-07-02 10:34:29,673 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:29,673 [model] Got input parameters: {'Omega_m': 0.3194870274705619, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5540754427149882, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:29,673 [classy] Got parameters {'Omega_m': 0.3194870274705619, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:29,673 [classy] Re-using computed results
2023-07-02 10:34:29,673 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.4257706174018}
2023-07-02 10:34:29,673 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:29,673 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5540754427149882, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:29,673 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:29,694 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.19845
2023-07-02 10:34:29,694 [model] Computed derived parameters: {}
2023-07-02 10:34:29,694 [model] Posterior to be computed for parameters {'Omega_m': 0.3491482447057602, 'b1': 0.45246154255359217}
2023-07-02 10:34:29,694 [prior] Evaluating prior at array([0.34914824, 0.45246154])
2023-07-02 10:34:29,694 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:29,694 [model] Got input parameters: {'Omega_m': 0.3491482447057602, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45246154255359217, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:29,694 [classy] Got parameters {'Omega_m': 0.3491482447057602, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:29,694 [classy] Computing new state
2023-07-02 10:34:29,694 [classy] Setting parameters: {'Omega_m': 0.3491482447057602, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:29,741 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.06485011048932}
2023-07-02 10:34:29,741 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:29,743 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0756772
2023-07-02 10:34:29,743 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45246154255359217, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:29,743 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:29,762 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.22454
2023-07-02 10:34:29,762 [model] Computed derived parameters: {}
2023-07-02 10:34:29,762 [model] Posterior to be computed for parameters {'Omega_m': 0.3194870274705619, 'b1': 0.5133977457386354}
2023-07-02 10:34:29,762 [prior] Evaluating prior at array([0.31948703, 0.51339775])
2023-07-02 10:34:29,763 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:29,763 [model] Got input parameters: {'Omega_m': 0.3194870274705619, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5133977457386354, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:29,763 [classy] Got parameters {'Omega_m': 0.3194870274705619, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:29,763 [classy] Re-using computed results
2023-07-02 10:34:29,763 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.4257706174018}
2023-07-02 10:34:29,763 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:29,763 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5133977457386354, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:29,763 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:29,782 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.58265
2023-07-02 10:34:29,782 [model] Computed derived parameters: {}
2023-07-02 10:34:29,782 [mcmc] New sample, #688:
Omega_m:0.319487, b1:0.5017006
2023-07-02 10:34:29,782 [model] Posterior to be computed for parameters {'Omega_m': 0.29929061942482466, 'b1': 0.5469247763216256}
2023-07-02 10:34:29,782 [prior] Evaluating prior at array([0.29929062, 0.54692478])
2023-07-02 10:34:29,782 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:29,782 [model] Got input parameters: {'Omega_m': 0.29929061942482466, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5469247763216256, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:29,782 [classy] Got parameters {'Omega_m': 0.29929061942482466, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:29,782 [classy] Computing new state
2023-07-02 10:34:29,782 [classy] Setting parameters: {'Omega_m': 0.29929061942482466, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:29,829 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.87803966877365}
2023-07-02 10:34:29,829 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:29,831 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0112367
2023-07-02 10:34:29,831 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5469247763216256, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:29,831 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:29,851 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.526662
2023-07-02 10:34:29,851 [model] Computed derived parameters: {}
2023-07-02 10:34:29,851 [model] Posterior to be computed for parameters {'Omega_m': 0.3194870274705619, 'b1': 0.5091465664976124}
2023-07-02 10:34:29,851 [prior] Evaluating prior at array([0.31948703, 0.50914657])
2023-07-02 10:34:29,851 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:29,852 [model] Got input parameters: {'Omega_m': 0.3194870274705619, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5091465664976124, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:29,852 [classy] Got parameters {'Omega_m': 0.3194870274705619, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:29,852 [classy] Re-using computed results
2023-07-02 10:34:29,852 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.4257706174018}
2023-07-02 10:34:29,852 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:29,852 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5091465664976124, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:29,852 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:29,871 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.03438
2023-07-02 10:34:29,871 [model] Computed derived parameters: {}
2023-07-02 10:34:29,871 [mcmc] New sample, #689:
Omega_m:0.319487, b1:0.5133977
2023-07-02 10:34:29,871 [model] Posterior to be computed for parameters {'Omega_m': 0.31878494751373443, 'b1': 0.5103120537531161}
2023-07-02 10:34:29,871 [prior] Evaluating prior at array([0.31878495, 0.51031205])
2023-07-02 10:34:29,871 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:29,871 [model] Got input parameters: {'Omega_m': 0.31878494751373443, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5103120537531161, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:29,871 [classy] Got parameters {'Omega_m': 0.31878494751373443, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:29,871 [classy] Computing new state
2023-07-02 10:34:29,871 [classy] Setting parameters: {'Omega_m': 0.31878494751373443, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:29,918 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.50867872041206}
2023-07-02 10:34:29,918 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:29,920 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00259909
2023-07-02 10:34:29,920 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5103120537531161, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:29,920 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:29,941 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.07543
2023-07-02 10:34:29,941 [model] Computed derived parameters: {}
2023-07-02 10:34:29,941 [mcmc] New sample, #690:
Omega_m:0.319487, b1:0.5091466
2023-07-02 10:34:29,941 [model] Posterior to be computed for parameters {'Omega_m': 0.31878494751373443, 'b1': 0.5270728788759755}
2023-07-02 10:34:29,941 [prior] Evaluating prior at array([0.31878495, 0.52707288])
2023-07-02 10:34:29,942 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:29,942 [model] Got input parameters: {'Omega_m': 0.31878494751373443, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5270728788759755, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:29,942 [classy] Got parameters {'Omega_m': 0.31878494751373443, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:29,942 [classy] Re-using computed results
2023-07-02 10:34:29,942 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.50867872041206}
2023-07-02 10:34:29,942 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:29,942 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5270728788759755, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:29,942 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:29,962 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.302792
2023-07-02 10:34:29,962 [model] Computed derived parameters: {}
2023-07-02 10:34:29,963 [model] Posterior to be computed for parameters {'Omega_m': 0.2940226396523268, 'b1': 0.5514187025737741}
2023-07-02 10:34:29,963 [prior] Evaluating prior at array([0.29402264, 0.5514187 ])
2023-07-02 10:34:29,963 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:29,963 [model] Got input parameters: {'Omega_m': 0.2940226396523268, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5514187025737741, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:29,963 [classy] Got parameters {'Omega_m': 0.2940226396523268, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:29,963 [classy] Computing new state
2023-07-02 10:34:29,963 [classy] Setting parameters: {'Omega_m': 0.2940226396523268, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:30,011 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.54162804456496}
2023-07-02 10:34:30,011 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:30,013 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0221028
2023-07-02 10:34:30,013 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5514187025737741, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:30,013 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:30,034 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.278024
2023-07-02 10:34:30,034 [model] Computed derived parameters: {}
2023-07-02 10:34:30,034 [model] Posterior to be computed for parameters {'Omega_m': 0.31878494751373443, 'b1': 0.526091577755176}
2023-07-02 10:34:30,034 [prior] Evaluating prior at array([0.31878495, 0.52609158])
2023-07-02 10:34:30,034 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:30,034 [model] Got input parameters: {'Omega_m': 0.31878494751373443, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.526091577755176, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:30,034 [classy] Got parameters {'Omega_m': 0.31878494751373443, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:30,034 [classy] Re-using computed results
2023-07-02 10:34:30,034 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.50867872041206}
2023-07-02 10:34:30,034 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:30,035 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.526091577755176, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:30,035 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:30,055 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.11809
2023-07-02 10:34:30,055 [model] Computed derived parameters: {}
2023-07-02 10:34:30,056 [mcmc] New sample, #691:
Omega_m:0.3187849, b1:0.5103121
2023-07-02 10:34:30,056 [model] Posterior to be computed for parameters {'Omega_m': 0.30541203767619823, 'b1': 0.5482912657438171}
2023-07-02 10:34:30,056 [prior] Evaluating prior at array([0.30541204, 0.54829127])
2023-07-02 10:34:30,056 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:30,056 [model] Got input parameters: {'Omega_m': 0.30541203767619823, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5482912657438171, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:30,056 [classy] Got parameters {'Omega_m': 0.30541203767619823, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:30,056 [classy] Computing new state
2023-07-02 10:34:30,056 [classy] Setting parameters: {'Omega_m': 0.30541203767619823, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:30,103 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.11972246776716}
2023-07-02 10:34:30,103 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:30,105 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0033241
2023-07-02 10:34:30,106 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5482912657438171, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:30,106 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:30,127 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.199584
2023-07-02 10:34:30,127 [model] Computed derived parameters: {}
2023-07-02 10:34:30,127 [mcmc] New sample, #692:
Omega_m:0.3187849, b1:0.5260916
2023-07-02 10:34:30,127 [model] Posterior to be computed for parameters {'Omega_m': 0.30541203767619823, 'b1': 0.5314879685334746}
2023-07-02 10:34:30,127 [prior] Evaluating prior at array([0.30541204, 0.53148797])
2023-07-02 10:34:30,127 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:30,127 [model] Got input parameters: {'Omega_m': 0.30541203767619823, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5314879685334746, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:30,127 [classy] Got parameters {'Omega_m': 0.30541203767619823, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:30,127 [classy] Re-using computed results
2023-07-02 10:34:30,127 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.11972246776716}
2023-07-02 10:34:30,127 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:30,127 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5314879685334746, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:30,127 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:30,148 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.85618
2023-07-02 10:34:30,148 [model] Computed derived parameters: {}
2023-07-02 10:34:30,148 [mcmc] New sample, #693:
Omega_m:0.305412, b1:0.5482913
2023-07-02 10:34:30,148 [model] Posterior to be computed for parameters {'Omega_m': 0.3134644612837745, 'b1': 0.5181205493395757}
2023-07-02 10:34:30,148 [prior] Evaluating prior at array([0.31346446, 0.51812055])
2023-07-02 10:34:30,148 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:30,149 [model] Got input parameters: {'Omega_m': 0.3134644612837745, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5181205493395757, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:30,149 [classy] Got parameters {'Omega_m': 0.3134644612837745, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:30,149 [classy] Computing new state
2023-07-02 10:34:30,149 [classy] Setting parameters: {'Omega_m': 0.3134644612837745, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:30,195 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.1423074138287}
2023-07-02 10:34:30,195 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:30,197 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000261202
2023-07-02 10:34:30,197 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5181205493395757, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:30,197 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:30,216 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.29625
2023-07-02 10:34:30,217 [model] Computed derived parameters: {}
2023-07-02 10:34:30,217 [mcmc] New sample, #694:
Omega_m:0.305412, b1:0.531488
2023-07-02 10:34:30,217 [model] Posterior to be computed for parameters {'Omega_m': 0.3134644612837745, 'b1': 0.48878169896355106}
2023-07-02 10:34:30,217 [prior] Evaluating prior at array([0.31346446, 0.4887817 ])
2023-07-02 10:34:30,217 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:30,217 [model] Got input parameters: {'Omega_m': 0.3134644612837745, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48878169896355106, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:30,217 [classy] Got parameters {'Omega_m': 0.3134644612837745, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:30,217 [classy] Re-using computed results
2023-07-02 10:34:30,217 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.1423074138287}
2023-07-02 10:34:30,217 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:30,217 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48878169896355106, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:30,217 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:30,236 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.36308
2023-07-02 10:34:30,236 [model] Computed derived parameters: {}
2023-07-02 10:34:30,236 [mcmc] New sample, #695:
Omega_m:0.3134645, b1:0.5181205
2023-07-02 10:34:30,236 [model] Posterior to be computed for parameters {'Omega_m': 0.32385166061073883, 'b1': 0.4715384372549299}
2023-07-02 10:34:30,236 [prior] Evaluating prior at array([0.32385166, 0.47153844])
2023-07-02 10:34:30,237 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:30,237 [model] Got input parameters: {'Omega_m': 0.32385166061073883, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4715384372549299, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:30,237 [classy] Got parameters {'Omega_m': 0.32385166061073883, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:30,237 [classy] Computing new state
2023-07-02 10:34:30,237 [classy] Setting parameters: {'Omega_m': 0.32385166061073883, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:30,283 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.9139791080678}
2023-07-02 10:34:30,283 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:30,285 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00790736
2023-07-02 10:34:30,285 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4715384372549299, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:30,285 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:30,305 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.08407
2023-07-02 10:34:30,305 [model] Computed derived parameters: {}
2023-07-02 10:34:30,305 [mcmc] New sample, #696:
Omega_m:0.3134645, b1:0.4887817
2023-07-02 10:34:30,305 [model] Posterior to be computed for parameters {'Omega_m': 0.32385166061073883, 'b1': 0.4869690251521813}
2023-07-02 10:34:30,305 [prior] Evaluating prior at array([0.32385166, 0.48696903])
2023-07-02 10:34:30,306 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:30,306 [model] Got input parameters: {'Omega_m': 0.32385166061073883, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4869690251521813, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:30,306 [classy] Got parameters {'Omega_m': 0.32385166061073883, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:30,306 [classy] Re-using computed results
2023-07-02 10:34:30,306 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.9139791080678}
2023-07-02 10:34:30,306 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:30,306 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4869690251521813, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:30,306 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:30,325 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.50064
2023-07-02 10:34:30,325 [model] Computed derived parameters: {}
2023-07-02 10:34:30,325 [mcmc] New sample, #697:
Omega_m:0.3238517, b1:0.4715384
2023-07-02 10:34:30,325 [model] Posterior to be computed for parameters {'Omega_m': 0.3387069686341388, 'b1': 0.46230848327303303}
2023-07-02 10:34:30,325 [prior] Evaluating prior at array([0.33870697, 0.46230848])
2023-07-02 10:34:30,325 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:30,325 [model] Got input parameters: {'Omega_m': 0.3387069686341388, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46230848327303303, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:30,325 [classy] Got parameters {'Omega_m': 0.3387069686341388, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:30,325 [classy] Computing new state
2023-07-02 10:34:30,325 [classy] Setting parameters: {'Omega_m': 0.3387069686341388, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:30,372 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.2173698211626}
2023-07-02 10:34:30,372 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:30,374 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0397677
2023-07-02 10:34:30,374 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46230848327303303, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:30,374 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:30,394 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.046335
2023-07-02 10:34:30,394 [model] Computed derived parameters: {}
2023-07-02 10:34:30,394 [model] Posterior to be computed for parameters {'Omega_m': 0.32385166061073883, 'b1': 0.48199050699630613}
2023-07-02 10:34:30,394 [prior] Evaluating prior at array([0.32385166, 0.48199051])
2023-07-02 10:34:30,394 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:30,394 [model] Got input parameters: {'Omega_m': 0.32385166061073883, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48199050699630613, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:30,394 [classy] Got parameters {'Omega_m': 0.32385166061073883, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:30,394 [classy] Re-using computed results
2023-07-02 10:34:30,394 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.9139791080678}
2023-07-02 10:34:30,394 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:30,394 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48199050699630613, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:30,394 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:30,414 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.50592
2023-07-02 10:34:30,414 [model] Computed derived parameters: {}
2023-07-02 10:34:30,414 [mcmc] New sample, #698:
Omega_m:0.3238517, b1:0.486969
2023-07-02 10:34:30,414 [model] Posterior to be computed for parameters {'Omega_m': 0.34328280323589966, 'b1': 0.44973385464600296}
2023-07-02 10:34:30,414 [prior] Evaluating prior at array([0.3432828 , 0.44973385])
2023-07-02 10:34:30,414 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:30,414 [model] Got input parameters: {'Omega_m': 0.34328280323589966, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44973385464600296, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:30,414 [classy] Got parameters {'Omega_m': 0.34328280323589966, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:30,414 [classy] Computing new state
2023-07-02 10:34:30,414 [classy] Setting parameters: {'Omega_m': 0.34328280323589966, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:30,461 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.70832803029055}
2023-07-02 10:34:30,461 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:30,463 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0541963
2023-07-02 10:34:30,463 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44973385464600296, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:30,463 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:30,482 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.01269
2023-07-02 10:34:30,482 [model] Computed derived parameters: {}
2023-07-02 10:34:30,482 [model] Posterior to be computed for parameters {'Omega_m': 0.32385166061073883, 'b1': 0.443187446490782}
2023-07-02 10:34:30,482 [prior] Evaluating prior at array([0.32385166, 0.44318745])
2023-07-02 10:34:30,482 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:30,483 [model] Got input parameters: {'Omega_m': 0.32385166061073883, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.443187446490782, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:30,483 [classy] Got parameters {'Omega_m': 0.32385166061073883, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:30,483 [classy] Re-using computed results
2023-07-02 10:34:30,483 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.9139791080678}
2023-07-02 10:34:30,483 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:30,483 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.443187446490782, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:30,483 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:30,502 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.88375
2023-07-02 10:34:30,502 [model] Computed derived parameters: {}
2023-07-02 10:34:30,503 [model] Posterior to be computed for parameters {'Omega_m': 0.3069737633938308, 'b1': 0.5100086464043815}
2023-07-02 10:34:30,503 [prior] Evaluating prior at array([0.30697376, 0.51000865])
2023-07-02 10:34:30,503 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:30,503 [model] Got input parameters: {'Omega_m': 0.3069737633938308, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5100086464043815, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:30,503 [classy] Got parameters {'Omega_m': 0.3069737633938308, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:30,503 [classy] Computing new state
2023-07-02 10:34:30,503 [classy] Setting parameters: {'Omega_m': 0.3069737633938308, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:30,549 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.92839899070088}
2023-07-02 10:34:30,549 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:30,551 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00209019
2023-07-02 10:34:30,551 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5100086464043815, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:30,551 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:30,570 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.46936
2023-07-02 10:34:30,570 [model] Computed derived parameters: {}
2023-07-02 10:34:30,570 [mcmc] New sample, #699:
Omega_m:0.3238517, b1:0.4819905
2023-07-02 10:34:30,570 [model] Posterior to be computed for parameters {'Omega_m': 0.3069737633938308, 'b1': 0.4490814472476656}
2023-07-02 10:34:30,570 [prior] Evaluating prior at array([0.30697376, 0.44908145])
2023-07-02 10:34:30,571 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:30,571 [model] Got input parameters: {'Omega_m': 0.3069737633938308, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4490814472476656, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:30,571 [classy] Got parameters {'Omega_m': 0.3069737633938308, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:30,571 [classy] Re-using computed results
2023-07-02 10:34:30,571 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.92839899070088}
2023-07-02 10:34:30,571 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:30,571 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4490814472476656, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:30,571 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:30,590 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.31653
2023-07-02 10:34:30,590 [model] Computed derived parameters: {}
2023-07-02 10:34:30,590 [model] Posterior to be computed for parameters {'Omega_m': 0.301226682593108, 'b1': 0.5195490831658292}
2023-07-02 10:34:30,590 [prior] Evaluating prior at array([0.30122668, 0.51954908])
2023-07-02 10:34:30,590 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:30,590 [model] Got input parameters: {'Omega_m': 0.301226682593108, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195490831658292, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:30,590 [classy] Got parameters {'Omega_m': 0.301226682593108, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:30,590 [classy] Computing new state
2023-07-02 10:34:30,590 [classy] Setting parameters: {'Omega_m': 0.301226682593108, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:30,636 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.63673349710393}
2023-07-02 10:34:30,636 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:30,638 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00819628
2023-07-02 10:34:30,638 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195490831658292, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:30,638 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:30,659 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.67466
2023-07-02 10:34:30,659 [model] Computed derived parameters: {}
2023-07-02 10:34:30,659 [model] Posterior to be computed for parameters {'Omega_m': 0.3069737633938308, 'b1': 0.5503702809012158}
2023-07-02 10:34:30,659 [prior] Evaluating prior at array([0.30697376, 0.55037028])
2023-07-02 10:34:30,659 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:30,659 [model] Got input parameters: {'Omega_m': 0.3069737633938308, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5503702809012158, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:30,659 [classy] Got parameters {'Omega_m': 0.3069737633938308, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:30,660 [classy] Re-using computed results
2023-07-02 10:34:30,660 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.92839899070088}
2023-07-02 10:34:30,660 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:30,660 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5503702809012158, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:30,660 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:30,679 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.947542
2023-07-02 10:34:30,679 [model] Computed derived parameters: {}
2023-07-02 10:34:30,679 [model] Posterior to be computed for parameters {'Omega_m': 0.2804158159210142, 'b1': 0.5540961452866644}
2023-07-02 10:34:30,679 [prior] Evaluating prior at array([0.28041582, 0.55409615])
2023-07-02 10:34:30,679 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:30,679 [model] Got input parameters: {'Omega_m': 0.2804158159210142, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5540961452866644, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:30,679 [classy] Got parameters {'Omega_m': 0.2804158159210142, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:30,679 [classy] Computing new state
2023-07-02 10:34:30,679 [classy] Setting parameters: {'Omega_m': 0.2804158159210142, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:30,725 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.3045795354919}
2023-07-02 10:34:30,726 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:30,728 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0686766
2023-07-02 10:34:30,728 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5540961452866644, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:30,728 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:30,747 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.14494
2023-07-02 10:34:30,747 [model] Computed derived parameters: {}
2023-07-02 10:34:30,747 [model] Posterior to be computed for parameters {'Omega_m': 0.3069737633938308, 'b1': 0.5218428830068252}
2023-07-02 10:34:30,748 [prior] Evaluating prior at array([0.30697376, 0.52184288])
2023-07-02 10:34:30,748 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:30,748 [model] Got input parameters: {'Omega_m': 0.3069737633938308, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5218428830068252, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:30,748 [classy] Got parameters {'Omega_m': 0.3069737633938308, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:30,748 [classy] Re-using computed results
2023-07-02 10:34:30,748 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.92839899070088}
2023-07-02 10:34:30,748 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:30,748 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5218428830068252, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:30,748 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:30,768 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.40471
2023-07-02 10:34:30,768 [model] Computed derived parameters: {}
2023-07-02 10:34:30,768 [mcmc] New sample, #700:
Omega_m:0.3069738, b1:0.5100086
2023-07-02 10:34:30,768 [model] Posterior to be computed for parameters {'Omega_m': 0.31082534786726057, 'b1': 0.5154490633661637}
2023-07-02 10:34:30,768 [prior] Evaluating prior at array([0.31082535, 0.51544906])
2023-07-02 10:34:30,768 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:30,768 [model] Got input parameters: {'Omega_m': 0.31082534786726057, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5154490633661637, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:30,768 [classy] Got parameters {'Omega_m': 0.31082534786726057, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:30,768 [classy] Computing new state
2023-07-02 10:34:30,768 [classy] Setting parameters: {'Omega_m': 0.31082534786726057, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:30,814 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.4601834720116}
2023-07-02 10:34:30,814 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:30,816 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000371782
2023-07-02 10:34:30,816 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5154490633661637, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:30,816 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:30,836 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.66454
2023-07-02 10:34:30,836 [model] Computed derived parameters: {}
2023-07-02 10:34:30,836 [mcmc] New sample, #701:
Omega_m:0.3069738, b1:0.5218429
2023-07-02 10:34:30,836 [model] Posterior to be computed for parameters {'Omega_m': 0.31082534786726057, 'b1': 0.5174390616925092}
2023-07-02 10:34:30,836 [prior] Evaluating prior at array([0.31082535, 0.51743906])
2023-07-02 10:34:30,836 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:30,836 [model] Got input parameters: {'Omega_m': 0.31082534786726057, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5174390616925092, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:30,836 [classy] Got parameters {'Omega_m': 0.31082534786726057, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:30,836 [classy] Re-using computed results
2023-07-02 10:34:30,836 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.4601834720116}
2023-07-02 10:34:30,836 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:30,836 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5174390616925092, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:30,836 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:30,856 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.57237
2023-07-02 10:34:30,856 [model] Computed derived parameters: {}
2023-07-02 10:34:30,856 [mcmc] New sample, #702:
Omega_m:0.3108253, b1:0.5154491
2023-07-02 10:34:30,856 [model] Posterior to be computed for parameters {'Omega_m': 0.2977809443202852, 'b1': 0.5390934130834051}
2023-07-02 10:34:30,856 [prior] Evaluating prior at array([0.29778094, 0.53909341])
2023-07-02 10:34:30,857 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:30,857 [model] Got input parameters: {'Omega_m': 0.2977809443202852, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5390934130834051, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:30,857 [classy] Got parameters {'Omega_m': 0.2977809443202852, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:30,857 [classy] Computing new state
2023-07-02 10:34:30,857 [classy] Setting parameters: {'Omega_m': 0.2977809443202852, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:30,903 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.06716352627132}
2023-07-02 10:34:30,904 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:30,906 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0139598
2023-07-02 10:34:30,906 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5390934130834051, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:30,906 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:30,925 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.943617
2023-07-02 10:34:30,925 [model] Computed derived parameters: {}
2023-07-02 10:34:30,925 [model] Posterior to be computed for parameters {'Omega_m': 0.31082534786726057, 'b1': 0.4836044424209451}
2023-07-02 10:34:30,925 [prior] Evaluating prior at array([0.31082535, 0.48360444])
2023-07-02 10:34:30,926 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:30,926 [model] Got input parameters: {'Omega_m': 0.31082534786726057, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4836044424209451, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:30,926 [classy] Got parameters {'Omega_m': 0.31082534786726057, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:30,926 [classy] Re-using computed results
2023-07-02 10:34:30,926 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.4601834720116}
2023-07-02 10:34:30,926 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:30,926 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4836044424209451, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:30,926 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:30,945 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.26721
2023-07-02 10:34:30,945 [model] Computed derived parameters: {}
2023-07-02 10:34:30,945 [model] Posterior to be computed for parameters {'Omega_m': 0.3450286171604994, 'b1': 0.46065995260361836}
2023-07-02 10:34:30,945 [prior] Evaluating prior at array([0.34502862, 0.46065995])
2023-07-02 10:34:30,945 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:30,945 [model] Got input parameters: {'Omega_m': 0.3450286171604994, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46065995260361836, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:30,945 [classy] Got parameters {'Omega_m': 0.3450286171604994, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:30,945 [classy] Computing new state
2023-07-02 10:34:30,946 [classy] Setting parameters: {'Omega_m': 0.3450286171604994, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:30,992 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.51574446370918}
2023-07-02 10:34:30,992 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:30,994 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0602451
2023-07-02 10:34:30,994 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46065995260361836, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:30,994 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:31,014 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.08448
2023-07-02 10:34:31,014 [model] Computed derived parameters: {}
2023-07-02 10:34:31,014 [model] Posterior to be computed for parameters {'Omega_m': 0.31082534786726057, 'b1': 0.5056007606352946}
2023-07-02 10:34:31,014 [prior] Evaluating prior at array([0.31082535, 0.50560076])
2023-07-02 10:34:31,014 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:31,014 [model] Got input parameters: {'Omega_m': 0.31082534786726057, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5056007606352946, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:31,014 [classy] Got parameters {'Omega_m': 0.31082534786726057, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:31,014 [classy] Re-using computed results
2023-07-02 10:34:31,014 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.4601834720116}
2023-07-02 10:34:31,014 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:31,014 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5056007606352946, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:31,014 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:31,033 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.80304
2023-07-02 10:34:31,034 [model] Computed derived parameters: {}
2023-07-02 10:34:31,034 [mcmc] New sample, #703:
Omega_m:0.3108253, b1:0.5174391
2023-07-02 10:34:31,034 [model] Posterior to be computed for parameters {'Omega_m': 0.3166007337264668, 'b1': 0.4960133360847669}
2023-07-02 10:34:31,034 [prior] Evaluating prior at array([0.31660073, 0.49601334])
2023-07-02 10:34:31,034 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:31,034 [model] Got input parameters: {'Omega_m': 0.3166007337264668, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4960133360847669, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:31,034 [classy] Got parameters {'Omega_m': 0.3166007337264668, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:31,034 [classy] Computing new state
2023-07-02 10:34:31,034 [classy] Setting parameters: {'Omega_m': 0.3166007337264668, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:31,081 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.76764731418749}
2023-07-02 10:34:31,081 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:31,082 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00123107
2023-07-02 10:34:31,083 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4960133360847669, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:31,083 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:31,102 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.91014
2023-07-02 10:34:31,102 [model] Computed derived parameters: {}
2023-07-02 10:34:31,102 [mcmc] New sample, #704:
Omega_m:0.3108253, b1:0.5056008
2023-07-02 10:34:31,102 [model] Posterior to be computed for parameters {'Omega_m': 0.3166007337264668, 'b1': 0.4852188652516624}
2023-07-02 10:34:31,102 [prior] Evaluating prior at array([0.31660073, 0.48521887])
2023-07-02 10:34:31,103 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:31,103 [model] Got input parameters: {'Omega_m': 0.3166007337264668, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4852188652516624, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:31,103 [classy] Got parameters {'Omega_m': 0.3166007337264668, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:31,103 [classy] Re-using computed results
2023-07-02 10:34:31,103 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.76764731418749}
2023-07-02 10:34:31,103 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:31,103 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4852188652516624, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:31,103 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:31,125 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.51715
2023-07-02 10:34:31,125 [model] Computed derived parameters: {}
2023-07-02 10:34:31,125 [model] Posterior to be computed for parameters {'Omega_m': 0.3081166706012419, 'b1': 0.510097298105304}
2023-07-02 10:34:31,125 [prior] Evaluating prior at array([0.30811667, 0.5100973 ])
2023-07-02 10:34:31,125 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:31,125 [model] Got input parameters: {'Omega_m': 0.3081166706012419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510097298105304, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:31,126 [classy] Got parameters {'Omega_m': 0.3081166706012419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:31,126 [classy] Computing new state
2023-07-02 10:34:31,126 [classy] Setting parameters: {'Omega_m': 0.3081166706012419, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:31,173 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.78892523797933}
2023-07-02 10:34:31,173 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:31,175 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00138491
2023-07-02 10:34:31,175 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510097298105304, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:31,175 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:31,195 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.61658
2023-07-02 10:34:31,195 [model] Computed derived parameters: {}
2023-07-02 10:34:31,195 [mcmc] New sample, #705:
Omega_m:0.3166007, b1:0.4960133
2023-07-02 10:34:31,195 [model] Posterior to be computed for parameters {'Omega_m': 0.3081166706012419, 'b1': 0.5643555912252121}
2023-07-02 10:34:31,195 [prior] Evaluating prior at array([0.30811667, 0.56435559])
2023-07-02 10:34:31,195 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:31,195 [model] Got input parameters: {'Omega_m': 0.3081166706012419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5643555912252121, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:31,195 [classy] Got parameters {'Omega_m': 0.3081166706012419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:31,195 [classy] Re-using computed results
2023-07-02 10:34:31,195 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.78892523797933}
2023-07-02 10:34:31,195 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:31,195 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5643555912252121, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:31,195 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:31,216 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.83999
2023-07-02 10:34:31,216 [model] Computed derived parameters: {}
2023-07-02 10:34:31,216 [model] Posterior to be computed for parameters {'Omega_m': 0.2967318065721468, 'b1': 0.5289967322830177}
2023-07-02 10:34:31,216 [prior] Evaluating prior at array([0.29673181, 0.52899673])
2023-07-02 10:34:31,216 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:31,216 [model] Got input parameters: {'Omega_m': 0.2967318065721468, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5289967322830177, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:31,216 [classy] Got parameters {'Omega_m': 0.2967318065721468, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:31,216 [classy] Computing new state
2023-07-02 10:34:31,216 [classy] Setting parameters: {'Omega_m': 0.2967318065721468, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:31,264 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.19908483675007}
2023-07-02 10:34:31,264 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:31,266 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0160358
2023-07-02 10:34:31,266 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5289967322830177, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:31,266 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:31,285 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.802417
2023-07-02 10:34:31,285 [model] Computed derived parameters: {}
2023-07-02 10:34:31,285 [model] Posterior to be computed for parameters {'Omega_m': 0.3081166706012419, 'b1': 0.50873016494565}
2023-07-02 10:34:31,285 [prior] Evaluating prior at array([0.30811667, 0.50873016])
2023-07-02 10:34:31,286 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:31,286 [model] Got input parameters: {'Omega_m': 0.3081166706012419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.50873016494565, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:31,286 [classy] Got parameters {'Omega_m': 0.3081166706012419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:31,286 [classy] Re-using computed results
2023-07-02 10:34:31,286 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.78892523797933}
2023-07-02 10:34:31,286 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:31,286 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.50873016494565, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:31,286 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:31,305 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.59156
2023-07-02 10:34:31,305 [model] Computed derived parameters: {}
2023-07-02 10:34:31,305 [mcmc] New sample, #706:
Omega_m:0.3081167, b1:0.5100973
2023-07-02 10:34:31,305 [model] Posterior to be computed for parameters {'Omega_m': 0.2996548351894904, 'b1': 0.5227772278686981}
2023-07-02 10:34:31,306 [prior] Evaluating prior at array([0.29965484, 0.52277723])
2023-07-02 10:34:31,306 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:31,306 [model] Got input parameters: {'Omega_m': 0.2996548351894904, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5227772278686981, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:31,306 [classy] Got parameters {'Omega_m': 0.2996548351894904, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:31,306 [classy] Computing new state
2023-07-02 10:34:31,306 [classy] Setting parameters: {'Omega_m': 0.2996548351894904, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:31,352 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.83253722101625}
2023-07-02 10:34:31,352 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:31,354 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0106261
2023-07-02 10:34:31,354 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5227772278686981, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:31,354 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:31,374 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.39989
2023-07-02 10:34:31,374 [model] Computed derived parameters: {}
2023-07-02 10:34:31,374 [model] Posterior to be computed for parameters {'Omega_m': 0.3081166706012419, 'b1': 0.48608872944192644}
2023-07-02 10:34:31,374 [prior] Evaluating prior at array([0.30811667, 0.48608873])
2023-07-02 10:34:31,374 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:31,374 [model] Got input parameters: {'Omega_m': 0.3081166706012419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48608872944192644, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:31,374 [classy] Got parameters {'Omega_m': 0.3081166706012419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:31,374 [classy] Re-using computed results
2023-07-02 10:34:31,374 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.78892523797933}
2023-07-02 10:34:31,374 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:31,374 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48608872944192644, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:31,374 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:31,394 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.77009
2023-07-02 10:34:31,394 [model] Computed derived parameters: {}
2023-07-02 10:34:31,394 [model] Posterior to be computed for parameters {'Omega_m': 0.2925140041986516, 'b1': 0.5346313584881449}
2023-07-02 10:34:31,394 [prior] Evaluating prior at array([0.292514 , 0.53463136])
2023-07-02 10:34:31,394 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:31,394 [model] Got input parameters: {'Omega_m': 0.2925140041986516, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5346313584881449, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:31,394 [classy] Got parameters {'Omega_m': 0.2925140041986516, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:31,394 [classy] Computing new state
2023-07-02 10:34:31,394 [classy] Setting parameters: {'Omega_m': 0.2925140041986516, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:31,441 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.73356701170118}
2023-07-02 10:34:31,441 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:31,443 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0259284
2023-07-02 10:34:31,443 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5346313584881449, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:31,443 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:31,464 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.365306
2023-07-02 10:34:31,464 [model] Computed derived parameters: {}
2023-07-02 10:34:31,465 [model] Posterior to be computed for parameters {'Omega_m': 0.3081166706012419, 'b1': 0.5528681085570034}
2023-07-02 10:34:31,465 [prior] Evaluating prior at array([0.30811667, 0.55286811])
2023-07-02 10:34:31,465 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:31,465 [model] Got input parameters: {'Omega_m': 0.3081166706012419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5528681085570034, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:31,465 [classy] Got parameters {'Omega_m': 0.3081166706012419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:31,465 [classy] Re-using computed results
2023-07-02 10:34:31,465 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.78892523797933}
2023-07-02 10:34:31,465 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:31,465 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5528681085570034, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:31,465 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:31,484 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.82607
2023-07-02 10:34:31,485 [model] Computed derived parameters: {}
2023-07-02 10:34:31,485 [model] Posterior to be computed for parameters {'Omega_m': 0.28117503396746524, 'b1': 0.5534546067043463}
2023-07-02 10:34:31,485 [prior] Evaluating prior at array([0.28117503, 0.55345461])
2023-07-02 10:34:31,485 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:31,485 [model] Got input parameters: {'Omega_m': 0.28117503396746524, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5534546067043463, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:31,485 [classy] Got parameters {'Omega_m': 0.28117503396746524, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:31,485 [classy] Computing new state
2023-07-02 10:34:31,485 [classy] Setting parameters: {'Omega_m': 0.28117503396746524, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:31,531 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.20429028540894}
2023-07-02 10:34:31,531 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:31,533 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0653415
2023-07-02 10:34:31,533 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5534546067043463, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:31,533 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:31,553 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.74969
2023-07-02 10:34:31,553 [model] Computed derived parameters: {}
2023-07-02 10:34:31,553 [model] Posterior to be computed for parameters {'Omega_m': 0.3081166706012419, 'b1': 0.4836574007959134}
2023-07-02 10:34:31,553 [prior] Evaluating prior at array([0.30811667, 0.4836574 ])
2023-07-02 10:34:31,553 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:31,553 [model] Got input parameters: {'Omega_m': 0.3081166706012419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4836574007959134, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:31,553 [classy] Got parameters {'Omega_m': 0.3081166706012419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:31,553 [classy] Re-using computed results
2023-07-02 10:34:31,553 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.78892523797933}
2023-07-02 10:34:31,553 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:31,553 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4836574007959134, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:31,553 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:31,574 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.420905
2023-07-02 10:34:31,574 [model] Computed derived parameters: {}
2023-07-02 10:34:31,574 [model] Posterior to be computed for parameters {'Omega_m': 0.2949364406444823, 'b1': 0.5306099948565134}
2023-07-02 10:34:31,574 [prior] Evaluating prior at array([0.29493644, 0.53060999])
2023-07-02 10:34:31,574 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:31,574 [model] Got input parameters: {'Omega_m': 0.2949364406444823, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5306099948565134, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:31,574 [classy] Got parameters {'Omega_m': 0.2949364406444823, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:31,574 [classy] Computing new state
2023-07-02 10:34:31,574 [classy] Setting parameters: {'Omega_m': 0.2949364406444823, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:31,621 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.42578366646626}
2023-07-02 10:34:31,621 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:31,623 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0199418
2023-07-02 10:34:31,623 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5306099948565134, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:31,623 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:31,642 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.31542
2023-07-02 10:34:31,642 [model] Computed derived parameters: {}
2023-07-02 10:34:31,642 [model] Posterior to be computed for parameters {'Omega_m': 0.3081166706012419, 'b1': 0.5105159297180544}
2023-07-02 10:34:31,643 [prior] Evaluating prior at array([0.30811667, 0.51051593])
2023-07-02 10:34:31,643 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:31,643 [model] Got input parameters: {'Omega_m': 0.3081166706012419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5105159297180544, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:31,643 [classy] Got parameters {'Omega_m': 0.3081166706012419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:31,643 [classy] Re-using computed results
2023-07-02 10:34:31,643 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.78892523797933}
2023-07-02 10:34:31,643 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:31,643 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5105159297180544, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:31,643 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:31,664 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.62226
2023-07-02 10:34:31,664 [model] Computed derived parameters: {}
2023-07-02 10:34:31,664 [mcmc] New sample, #707:
Omega_m:0.3081167, b1:0.5087302
2023-07-02 10:34:31,664 [model] Posterior to be computed for parameters {'Omega_m': 0.23479711361411262, 'b1': 0.63223000005531}
2023-07-02 10:34:31,664 [prior] Evaluating prior at array([0.23479711, 0.63223 ])
2023-07-02 10:34:31,665 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:31,665 [model] Got input parameters: {'Omega_m': 0.23479711361411262, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.63223000005531, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:31,665 [classy] Got parameters {'Omega_m': 0.23479711361411262, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:31,665 [classy] Computing new state
2023-07-02 10:34:31,665 [classy] Setting parameters: {'Omega_m': 0.23479711361411262, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:31,712 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 157.79696486450297}
2023-07-02 10:34:31,712 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:31,713 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.456555
2023-07-02 10:34:31,714 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.63223000005531, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:31,714 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:31,733 [fs_likelihood.fslikelihood] Computed log-likelihood = -48.1031
2023-07-02 10:34:31,733 [model] Computed derived parameters: {}
2023-07-02 10:34:31,733 [model] Posterior to be computed for parameters {'Omega_m': 0.3081166706012419, 'b1': 0.46404131797135123}
2023-07-02 10:34:31,733 [prior] Evaluating prior at array([0.30811667, 0.46404132])
2023-07-02 10:34:31,733 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:31,733 [model] Got input parameters: {'Omega_m': 0.3081166706012419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46404131797135123, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:31,733 [classy] Got parameters {'Omega_m': 0.3081166706012419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:31,733 [classy] Re-using computed results
2023-07-02 10:34:31,733 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.78892523797933}
2023-07-02 10:34:31,733 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:31,733 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46404131797135123, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:31,733 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:31,753 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.43617
2023-07-02 10:34:31,753 [model] Computed derived parameters: {}
2023-07-02 10:34:31,753 [model] Posterior to be computed for parameters {'Omega_m': 0.2368383403796161, 'b1': 0.6288414632403045}
2023-07-02 10:34:31,753 [prior] Evaluating prior at array([0.23683834, 0.62884146])
2023-07-02 10:34:31,753 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:31,753 [model] Got input parameters: {'Omega_m': 0.2368383403796161, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6288414632403045, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:31,753 [classy] Got parameters {'Omega_m': 0.2368383403796161, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:31,753 [classy] Computing new state
2023-07-02 10:34:31,753 [classy] Setting parameters: {'Omega_m': 0.2368383403796161, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:31,800 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 157.4851181864174}
2023-07-02 10:34:31,800 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:31,802 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.430314
2023-07-02 10:34:31,802 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6288414632403045, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:31,802 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:31,822 [fs_likelihood.fslikelihood] Computed log-likelihood = -45.157
2023-07-02 10:34:31,822 [model] Computed derived parameters: {}
2023-07-02 10:34:31,822 [model] Posterior to be computed for parameters {'Omega_m': 0.3081166706012419, 'b1': 0.46218718916270973}
2023-07-02 10:34:31,822 [prior] Evaluating prior at array([0.30811667, 0.46218719])
2023-07-02 10:34:31,822 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:31,822 [model] Got input parameters: {'Omega_m': 0.3081166706012419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46218718916270973, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:31,822 [classy] Got parameters {'Omega_m': 0.3081166706012419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:31,823 [classy] Re-using computed results
2023-07-02 10:34:31,823 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.78892523797933}
2023-07-02 10:34:31,823 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:31,823 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46218718916270973, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:31,823 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:31,842 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.89405
2023-07-02 10:34:31,842 [model] Computed derived parameters: {}
2023-07-02 10:34:31,842 [model] Posterior to be computed for parameters {'Omega_m': 0.27419570889761025, 'b1': 0.5668263943247615}
2023-07-02 10:34:31,842 [prior] Evaluating prior at array([0.27419571, 0.56682639])
2023-07-02 10:34:31,842 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:31,842 [model] Got input parameters: {'Omega_m': 0.27419570889761025, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5668263943247615, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:31,843 [classy] Got parameters {'Omega_m': 0.27419570889761025, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:31,843 [classy] Computing new state
2023-07-02 10:34:31,843 [classy] Setting parameters: {'Omega_m': 0.27419570889761025, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:31,890 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.13508043764273}
2023-07-02 10:34:31,890 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:31,892 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.099449
2023-07-02 10:34:31,892 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5668263943247615, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:31,892 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:31,912 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.43132
2023-07-02 10:34:31,912 [model] Computed derived parameters: {}
2023-07-02 10:34:31,912 [model] Posterior to be computed for parameters {'Omega_m': 0.3081166706012419, 'b1': 0.5067768409787212}
2023-07-02 10:34:31,912 [prior] Evaluating prior at array([0.30811667, 0.50677684])
2023-07-02 10:34:31,912 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:31,912 [model] Got input parameters: {'Omega_m': 0.3081166706012419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5067768409787212, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:31,912 [classy] Got parameters {'Omega_m': 0.3081166706012419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:31,912 [classy] Re-using computed results
2023-07-02 10:34:31,912 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.78892523797933}
2023-07-02 10:34:31,912 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:31,912 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5067768409787212, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:31,912 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:31,932 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.53868
2023-07-02 10:34:31,932 [model] Computed derived parameters: {}
2023-07-02 10:34:31,932 [mcmc] New sample, #708:
Omega_m:0.3081167, b1:0.5105159
2023-07-02 10:34:31,932 [model] Posterior to be computed for parameters {'Omega_m': 0.2904005307311574, 'b1': 0.5361865044145034}
2023-07-02 10:34:31,932 [prior] Evaluating prior at array([0.29040053, 0.5361865 ])
2023-07-02 10:34:31,932 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:31,933 [model] Got input parameters: {'Omega_m': 0.2904005307311574, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5361865044145034, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:31,933 [classy] Got parameters {'Omega_m': 0.2904005307311574, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:31,933 [classy] Computing new state
2023-07-02 10:34:31,933 [classy] Setting parameters: {'Omega_m': 0.2904005307311574, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:31,979 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.00390611815547}
2023-07-02 10:34:31,979 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:31,981 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0318344
2023-07-02 10:34:31,981 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5361865044145034, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:31,981 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:32,000 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.10971
2023-07-02 10:34:32,001 [model] Computed derived parameters: {}
2023-07-02 10:34:32,001 [model] Posterior to be computed for parameters {'Omega_m': 0.3081166706012419, 'b1': 0.5015402797432746}
2023-07-02 10:34:32,001 [prior] Evaluating prior at array([0.30811667, 0.50154028])
2023-07-02 10:34:32,001 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:32,001 [model] Got input parameters: {'Omega_m': 0.3081166706012419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5015402797432746, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:32,001 [classy] Got parameters {'Omega_m': 0.3081166706012419, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:32,001 [classy] Re-using computed results
2023-07-02 10:34:32,001 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.78892523797933}
2023-07-02 10:34:32,001 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:32,001 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5015402797432746, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:32,001 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:32,031 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.29824
2023-07-02 10:34:32,031 [model] Computed derived parameters: {}
2023-07-02 10:34:32,031 [mcmc] New sample, #709:
Omega_m:0.3081167, b1:0.5067768
2023-07-02 10:34:32,031 [model] Posterior to be computed for parameters {'Omega_m': 0.31176324941122624, 'b1': 0.49548677958578335}
2023-07-02 10:34:32,031 [prior] Evaluating prior at array([0.31176325, 0.49548678])
2023-07-02 10:34:32,031 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:32,031 [model] Got input parameters: {'Omega_m': 0.31176324941122624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49548677958578335, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:32,031 [classy] Got parameters {'Omega_m': 0.31176324941122624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:32,031 [classy] Computing new state
2023-07-02 10:34:32,031 [classy] Setting parameters: {'Omega_m': 0.31176324941122624, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:32,078 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.34693951648617}
2023-07-02 10:34:32,078 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:32,080 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000234284
2023-07-02 10:34:32,080 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49548677958578335, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:32,080 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:32,099 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.55308
2023-07-02 10:34:32,100 [model] Computed derived parameters: {}
2023-07-02 10:34:32,100 [mcmc] New sample, #710:
Omega_m:0.3081167, b1:0.5015403
2023-07-02 10:34:32,100 [model] Posterior to be computed for parameters {'Omega_m': 0.31176324941122624, 'b1': 0.5101236677176169}
2023-07-02 10:34:32,100 [prior] Evaluating prior at array([0.31176325, 0.51012367])
2023-07-02 10:34:32,100 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:32,100 [model] Got input parameters: {'Omega_m': 0.31176324941122624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5101236677176169, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:32,100 [classy] Got parameters {'Omega_m': 0.31176324941122624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:32,100 [classy] Re-using computed results
2023-07-02 10:34:32,100 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.34693951648617}
2023-07-02 10:34:32,100 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:32,100 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5101236677176169, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:32,100 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:32,120 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.81868
2023-07-02 10:34:32,120 [model] Computed derived parameters: {}
2023-07-02 10:34:32,120 [mcmc] New sample, #711:
Omega_m:0.3117632, b1:0.4954868
2023-07-02 10:34:32,120 [model] Posterior to be computed for parameters {'Omega_m': 0.32828814355318114, 'b1': 0.4826915307740906}
2023-07-02 10:34:32,120 [prior] Evaluating prior at array([0.32828814, 0.48269153])
2023-07-02 10:34:32,120 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:32,120 [model] Got input parameters: {'Omega_m': 0.32828814355318114, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4826915307740906, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:32,121 [classy] Got parameters {'Omega_m': 0.32828814355318114, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:32,121 [classy] Computing new state
2023-07-02 10:34:32,121 [classy] Setting parameters: {'Omega_m': 0.32828814355318114, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:32,169 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.4000417051186}
2023-07-02 10:34:32,169 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:32,171 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0149366
2023-07-02 10:34:32,171 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4826915307740906, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:32,171 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:32,191 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.90039
2023-07-02 10:34:32,191 [model] Computed derived parameters: {}
2023-07-02 10:34:32,191 [model] Posterior to be computed for parameters {'Omega_m': 0.31176324941122624, 'b1': 0.5410847544256415}
2023-07-02 10:34:32,191 [prior] Evaluating prior at array([0.31176325, 0.54108475])
2023-07-02 10:34:32,191 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:32,191 [model] Got input parameters: {'Omega_m': 0.31176324941122624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5410847544256415, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:32,191 [classy] Got parameters {'Omega_m': 0.31176324941122624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:32,191 [classy] Re-using computed results
2023-07-02 10:34:32,191 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.34693951648617}
2023-07-02 10:34:32,191 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:32,191 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5410847544256415, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:32,191 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:32,211 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.521664
2023-07-02 10:34:32,211 [model] Computed derived parameters: {}
2023-07-02 10:34:32,211 [model] Posterior to be computed for parameters {'Omega_m': 0.2982962487810565, 'b1': 0.5324795510492645}
2023-07-02 10:34:32,211 [prior] Evaluating prior at array([0.29829625, 0.53247955])
2023-07-02 10:34:32,211 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:32,211 [model] Got input parameters: {'Omega_m': 0.2982962487810565, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5324795510492645, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:32,211 [classy] Got parameters {'Omega_m': 0.2982962487810565, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:32,211 [classy] Computing new state
2023-07-02 10:34:32,211 [classy] Setting parameters: {'Omega_m': 0.2982962487810565, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:32,258 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.0025145746044}
2023-07-02 10:34:32,258 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:32,260 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0129954
2023-07-02 10:34:32,260 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5324795510492645, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:32,260 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:32,280 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.195
2023-07-02 10:34:32,280 [model] Computed derived parameters: {}
2023-07-02 10:34:32,281 [model] Posterior to be computed for parameters {'Omega_m': 0.31176324941122624, 'b1': 0.5059570422716518}
2023-07-02 10:34:32,281 [prior] Evaluating prior at array([0.31176325, 0.50595704])
2023-07-02 10:34:32,281 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:32,281 [model] Got input parameters: {'Omega_m': 0.31176324941122624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5059570422716518, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:32,281 [classy] Got parameters {'Omega_m': 0.31176324941122624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:32,281 [classy] Re-using computed results
2023-07-02 10:34:32,281 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.34693951648617}
2023-07-02 10:34:32,281 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:32,281 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5059570422716518, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:32,281 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:32,300 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.85949
2023-07-02 10:34:32,300 [model] Computed derived parameters: {}
2023-07-02 10:34:32,300 [mcmc] New sample, #712:
Omega_m:0.3117632, b1:0.5101237
2023-07-02 10:34:32,300 [model] Posterior to be computed for parameters {'Omega_m': 0.34717089550883595, 'b1': 0.4471786084581791}
2023-07-02 10:34:32,300 [prior] Evaluating prior at array([0.3471709 , 0.44717861])
2023-07-02 10:34:32,301 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:32,301 [model] Got input parameters: {'Omega_m': 0.34717089550883595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4471786084581791, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:32,301 [classy] Got parameters {'Omega_m': 0.34717089550883595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:32,301 [classy] Computing new state
2023-07-02 10:34:32,301 [classy] Setting parameters: {'Omega_m': 0.34717089550883595, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:32,347 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.2806612747171}
2023-07-02 10:34:32,347 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:32,349 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0680683
2023-07-02 10:34:32,349 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4471786084581791, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:32,349 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:32,368 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.16323
2023-07-02 10:34:32,369 [model] Computed derived parameters: {}
2023-07-02 10:34:32,369 [model] Posterior to be computed for parameters {'Omega_m': 0.31176324941122624, 'b1': 0.4982521990034722}
2023-07-02 10:34:32,369 [prior] Evaluating prior at array([0.31176325, 0.4982522 ])
2023-07-02 10:34:32,369 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:32,369 [model] Got input parameters: {'Omega_m': 0.31176324941122624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4982521990034722, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:32,369 [classy] Got parameters {'Omega_m': 0.31176324941122624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:32,369 [classy] Re-using computed results
2023-07-02 10:34:32,369 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.34693951648617}
2023-07-02 10:34:32,369 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:32,369 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4982521990034722, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:32,369 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:32,389 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.69019
2023-07-02 10:34:32,389 [model] Computed derived parameters: {}
2023-07-02 10:34:32,389 [mcmc] New sample, #713:
Omega_m:0.3117632, b1:0.505957
2023-07-02 10:34:32,389 [model] Posterior to be computed for parameters {'Omega_m': 0.38789090490987443, 'b1': 0.37187654703929873}
2023-07-02 10:34:32,389 [prior] Evaluating prior at array([0.3878909 , 0.37187655])
2023-07-02 10:34:32,389 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:32,390 [model] Got input parameters: {'Omega_m': 0.38789090490987443, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.37187654703929873, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:32,390 [classy] Got parameters {'Omega_m': 0.38789090490987443, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:32,390 [classy] Computing new state
2023-07-02 10:34:32,390 [classy] Setting parameters: {'Omega_m': 0.38789090490987443, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:32,436 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 139.0496529909523}
2023-07-02 10:34:32,436 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:32,438 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.292836
2023-07-02 10:34:32,438 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.37187654703929873, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:32,438 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:32,457 [fs_likelihood.fslikelihood] Computed log-likelihood = -18.8613
2023-07-02 10:34:32,457 [model] Computed derived parameters: {}
2023-07-02 10:34:32,457 [model] Posterior to be computed for parameters {'Omega_m': 0.31176324941122624, 'b1': 0.4685827753252232}
2023-07-02 10:34:32,457 [prior] Evaluating prior at array([0.31176325, 0.46858278])
2023-07-02 10:34:32,458 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:32,458 [model] Got input parameters: {'Omega_m': 0.31176324941122624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4685827753252232, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:32,458 [classy] Got parameters {'Omega_m': 0.31176324941122624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:32,458 [classy] Re-using computed results
2023-07-02 10:34:32,458 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.34693951648617}
2023-07-02 10:34:32,458 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:32,458 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4685827753252232, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:32,458 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:32,478 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.80685
2023-07-02 10:34:32,478 [model] Computed derived parameters: {}
2023-07-02 10:34:32,479 [model] Posterior to be computed for parameters {'Omega_m': 0.3384639431268244, 'b1': 0.4539277343381398}
2023-07-02 10:34:32,479 [prior] Evaluating prior at array([0.33846394, 0.45392773])
2023-07-02 10:34:32,479 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:32,479 [model] Got input parameters: {'Omega_m': 0.3384639431268244, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4539277343381398, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:32,479 [classy] Got parameters {'Omega_m': 0.3384639431268244, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:32,479 [classy] Computing new state
2023-07-02 10:34:32,479 [classy] Setting parameters: {'Omega_m': 0.3384639431268244, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:32,525 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.24457964941573}
2023-07-02 10:34:32,525 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:32,527 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0390601
2023-07-02 10:34:32,527 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4539277343381398, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:32,527 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:32,546 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.125242
2023-07-02 10:34:32,546 [model] Computed derived parameters: {}
2023-07-02 10:34:32,546 [model] Posterior to be computed for parameters {'Omega_m': 0.31176324941122624, 'b1': 0.45529118162470056}
2023-07-02 10:34:32,546 [prior] Evaluating prior at array([0.31176325, 0.45529118])
2023-07-02 10:34:32,546 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:32,546 [model] Got input parameters: {'Omega_m': 0.31176324941122624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45529118162470056, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:32,547 [classy] Got parameters {'Omega_m': 0.31176324941122624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:32,547 [classy] Re-using computed results
2023-07-02 10:34:32,547 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.34693951648617}
2023-07-02 10:34:32,547 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:32,547 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45529118162470056, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:32,547 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:32,566 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.76332
2023-07-02 10:34:32,566 [model] Computed derived parameters: {}
2023-07-02 10:34:32,566 [model] Posterior to be computed for parameters {'Omega_m': 0.26343683428272374, 'b1': 0.578476424732639}
2023-07-02 10:34:32,566 [prior] Evaluating prior at array([0.26343683, 0.57847642])
2023-07-02 10:34:32,566 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:32,566 [model] Got input parameters: {'Omega_m': 0.26343683428272374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.578476424732639, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:32,566 [classy] Got parameters {'Omega_m': 0.26343683428272374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:32,566 [classy] Computing new state
2023-07-02 10:34:32,566 [classy] Setting parameters: {'Omega_m': 0.26343683428272374, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:32,612 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.61020467698955}
2023-07-02 10:34:32,612 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:32,614 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.167897
2023-07-02 10:34:32,614 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.578476424732639, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:32,614 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:32,634 [fs_likelihood.fslikelihood] Computed log-likelihood = -16.327
2023-07-02 10:34:32,634 [model] Computed derived parameters: {}
2023-07-02 10:34:32,635 [model] Posterior to be computed for parameters {'Omega_m': 0.31176324941122624, 'b1': 0.5002750289201412}
2023-07-02 10:34:32,635 [prior] Evaluating prior at array([0.31176325, 0.50027503])
2023-07-02 10:34:32,635 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:32,635 [model] Got input parameters: {'Omega_m': 0.31176324941122624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5002750289201412, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:32,635 [classy] Got parameters {'Omega_m': 0.31176324941122624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:32,635 [classy] Re-using computed results
2023-07-02 10:34:32,635 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.34693951648617}
2023-07-02 10:34:32,635 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:32,635 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5002750289201412, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:32,635 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:32,654 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.76509
2023-07-02 10:34:32,654 [model] Computed derived parameters: {}
2023-07-02 10:34:32,654 [mcmc] New sample, #714:
Omega_m:0.3117632, b1:0.4982522
2023-07-02 10:34:32,654 [model] Posterior to be computed for parameters {'Omega_m': 0.3230832833558424, 'b1': 0.48148321587090254}
2023-07-02 10:34:32,654 [prior] Evaluating prior at array([0.32308328, 0.48148322])
2023-07-02 10:34:32,655 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:32,655 [model] Got input parameters: {'Omega_m': 0.3230832833558424, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48148321587090254, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:32,655 [classy] Got parameters {'Omega_m': 0.3230832833558424, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:32,655 [classy] Computing new state
2023-07-02 10:34:32,655 [classy] Setting parameters: {'Omega_m': 0.3230832833558424, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:32,701 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.00363016026483}
2023-07-02 10:34:32,701 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:32,703 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00691345
2023-07-02 10:34:32,703 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48148321587090254, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:32,703 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:32,723 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.54041
2023-07-02 10:34:32,723 [model] Computed derived parameters: {}
2023-07-02 10:34:32,723 [model] Posterior to be computed for parameters {'Omega_m': 0.31176324941122624, 'b1': 0.5068111191219317}
2023-07-02 10:34:32,723 [prior] Evaluating prior at array([0.31176325, 0.50681112])
2023-07-02 10:34:32,723 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:32,723 [model] Got input parameters: {'Omega_m': 0.31176324941122624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5068111191219317, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:32,724 [classy] Got parameters {'Omega_m': 0.31176324941122624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:32,724 [classy] Re-using computed results
2023-07-02 10:34:32,724 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.34693951648617}
2023-07-02 10:34:32,724 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:32,724 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5068111191219317, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:32,724 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:32,744 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.85876
2023-07-02 10:34:32,744 [model] Computed derived parameters: {}
2023-07-02 10:34:32,744 [mcmc] New sample, #715:
Omega_m:0.3117632, b1:0.500275
2023-07-02 10:34:32,744 [model] Posterior to be computed for parameters {'Omega_m': 0.3273167556003784, 'b1': 0.48099153395136496}
2023-07-02 10:34:32,744 [prior] Evaluating prior at array([0.32731676, 0.48099153])
2023-07-02 10:34:32,744 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:32,744 [model] Got input parameters: {'Omega_m': 0.3273167556003784, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48099153395136496, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:32,744 [classy] Got parameters {'Omega_m': 0.3273167556003784, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:32,744 [classy] Computing new state
2023-07-02 10:34:32,744 [classy] Setting parameters: {'Omega_m': 0.3273167556003784, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:32,790 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.51203535192877}
2023-07-02 10:34:32,791 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:32,792 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0132114
2023-07-02 10:34:32,792 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48099153395136496, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:32,792 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:32,812 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.11713
2023-07-02 10:34:32,812 [model] Computed derived parameters: {}
2023-07-02 10:34:32,812 [model] Posterior to be computed for parameters {'Omega_m': 0.31176324941122624, 'b1': 0.5308182268463638}
2023-07-02 10:34:32,812 [prior] Evaluating prior at array([0.31176325, 0.53081823])
2023-07-02 10:34:32,812 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:32,812 [model] Got input parameters: {'Omega_m': 0.31176324941122624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5308182268463638, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:32,812 [classy] Got parameters {'Omega_m': 0.31176324941122624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:32,812 [classy] Re-using computed results
2023-07-02 10:34:32,812 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.34693951648617}
2023-07-02 10:34:32,812 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:32,812 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5308182268463638, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:32,812 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:32,832 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.19381
2023-07-02 10:34:32,832 [model] Computed derived parameters: {}
2023-07-02 10:34:32,832 [model] Posterior to be computed for parameters {'Omega_m': 0.28258260765916193, 'b1': 0.5552524194876783}
2023-07-02 10:34:32,832 [prior] Evaluating prior at array([0.28258261, 0.55525242])
2023-07-02 10:34:32,833 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:32,833 [model] Got input parameters: {'Omega_m': 0.28258260765916193, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5552524194876783, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:32,833 [classy] Got parameters {'Omega_m': 0.28258260765916193, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:32,833 [classy] Computing new state
2023-07-02 10:34:32,833 [classy] Setting parameters: {'Omega_m': 0.28258260765916193, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:32,879 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.01896385615075}
2023-07-02 10:34:32,879 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:32,881 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0593951
2023-07-02 10:34:32,881 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5552524194876783, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:32,881 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:32,901 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.96658
2023-07-02 10:34:32,901 [model] Computed derived parameters: {}
2023-07-02 10:34:32,901 [model] Posterior to be computed for parameters {'Omega_m': 0.31176324941122624, 'b1': 0.5219705513883467}
2023-07-02 10:34:32,901 [prior] Evaluating prior at array([0.31176325, 0.52197055])
2023-07-02 10:34:32,901 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:32,901 [model] Got input parameters: {'Omega_m': 0.31176324941122624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5219705513883467, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:32,901 [classy] Got parameters {'Omega_m': 0.31176324941122624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:32,901 [classy] Re-using computed results
2023-07-02 10:34:32,901 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.34693951648617}
2023-07-02 10:34:32,901 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:32,901 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5219705513883467, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:32,901 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:32,920 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.18283
2023-07-02 10:34:32,920 [model] Computed derived parameters: {}
2023-07-02 10:34:32,920 [mcmc] New sample, #716:
Omega_m:0.3117632, b1:0.5068111
2023-07-02 10:34:32,920 [model] Posterior to be computed for parameters {'Omega_m': 0.3139702786750449, 'b1': 0.5183067742722361}
2023-07-02 10:34:32,920 [prior] Evaluating prior at array([0.31397028, 0.51830677])
2023-07-02 10:34:32,921 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:32,921 [model] Got input parameters: {'Omega_m': 0.3139702786750449, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5183067742722361, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:32,921 [classy] Got parameters {'Omega_m': 0.3139702786750449, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:32,921 [classy] Computing new state
2023-07-02 10:34:32,921 [classy] Setting parameters: {'Omega_m': 0.3139702786750449, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:32,967 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.08165482317673}
2023-07-02 10:34:32,967 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:32,969 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000337375
2023-07-02 10:34:32,969 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5183067742722361, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:32,969 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:32,989 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.20979
2023-07-02 10:34:32,989 [model] Computed derived parameters: {}
2023-07-02 10:34:32,989 [mcmc] New sample, #717:
Omega_m:0.3117632, b1:0.5219706
2023-07-02 10:34:32,989 [model] Posterior to be computed for parameters {'Omega_m': 0.3139702786750449, 'b1': 0.5299038224053864}
2023-07-02 10:34:32,989 [prior] Evaluating prior at array([0.31397028, 0.52990382])
2023-07-02 10:34:32,989 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:32,989 [model] Got input parameters: {'Omega_m': 0.3139702786750449, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5299038224053864, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:32,989 [classy] Got parameters {'Omega_m': 0.3139702786750449, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:32,990 [classy] Re-using computed results
2023-07-02 10:34:32,990 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.08165482317673}
2023-07-02 10:34:32,990 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:32,990 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5299038224053864, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:32,990 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:33,009 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.795885
2023-07-02 10:34:33,009 [model] Computed derived parameters: {}
2023-07-02 10:34:33,009 [model] Posterior to be computed for parameters {'Omega_m': 0.3074855928282414, 'b1': 0.529071671684415}
2023-07-02 10:34:33,009 [prior] Evaluating prior at array([0.30748559, 0.52907167])
2023-07-02 10:34:33,009 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:33,009 [model] Got input parameters: {'Omega_m': 0.3074855928282414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.529071671684415, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:33,009 [classy] Got parameters {'Omega_m': 0.3074855928282414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:33,009 [classy] Computing new state
2023-07-02 10:34:33,009 [classy] Setting parameters: {'Omega_m': 0.3074855928282414, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:33,056 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.8658817262105}
2023-07-02 10:34:33,056 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:33,058 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00175379
2023-07-02 10:34:33,058 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.529071671684415, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:33,058 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:33,078 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.96424
2023-07-02 10:34:33,078 [model] Computed derived parameters: {}
2023-07-02 10:34:33,078 [mcmc] New sample, #718:
Omega_m:0.3139703, b1:0.5183068
2023-07-02 10:34:33,078 [model] Posterior to be computed for parameters {'Omega_m': 0.3074855928282414, 'b1': 0.5174440260227556}
2023-07-02 10:34:33,078 [prior] Evaluating prior at array([0.30748559, 0.51744403])
2023-07-02 10:34:33,078 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:33,078 [model] Got input parameters: {'Omega_m': 0.3074855928282414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5174440260227556, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:33,078 [classy] Got parameters {'Omega_m': 0.3074855928282414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:33,079 [classy] Re-using computed results
2023-07-02 10:34:33,079 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.8658817262105}
2023-07-02 10:34:33,079 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:33,079 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5174440260227556, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:33,079 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:33,098 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.54988
2023-07-02 10:34:33,099 [model] Computed derived parameters: {}
2023-07-02 10:34:33,099 [mcmc] New sample, #719:
Omega_m:0.3074856, b1:0.5290717
2023-07-02 10:34:33,099 [model] Posterior to be computed for parameters {'Omega_m': 0.3398000390052746, 'b1': 0.46380045619606786}
2023-07-02 10:34:33,099 [prior] Evaluating prior at array([0.33980004, 0.46380046])
2023-07-02 10:34:33,099 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:33,099 [model] Got input parameters: {'Omega_m': 0.3398000390052746, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46380045619606786, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:33,099 [classy] Got parameters {'Omega_m': 0.3398000390052746, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:33,099 [classy] Computing new state
2023-07-02 10:34:33,099 [classy] Setting parameters: {'Omega_m': 0.3398000390052746, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:33,148 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.09520645961544}
2023-07-02 10:34:33,148 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:33,150 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0430242
2023-07-02 10:34:33,150 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46380045619606786, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:33,150 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:33,169 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.334803
2023-07-02 10:34:33,169 [model] Computed derived parameters: {}
2023-07-02 10:34:33,169 [model] Posterior to be computed for parameters {'Omega_m': 0.3074855928282414, 'b1': 0.512666647486877}
2023-07-02 10:34:33,169 [prior] Evaluating prior at array([0.30748559, 0.51266665])
2023-07-02 10:34:33,170 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:33,170 [model] Got input parameters: {'Omega_m': 0.3074855928282414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.512666647486877, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:33,170 [classy] Got parameters {'Omega_m': 0.3074855928282414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:33,170 [classy] Re-using computed results
2023-07-02 10:34:33,170 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.8658817262105}
2023-07-02 10:34:33,170 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:33,170 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.512666647486877, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:33,170 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:33,190 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.57713
2023-07-02 10:34:33,190 [model] Computed derived parameters: {}
2023-07-02 10:34:33,190 [mcmc] New sample, #720:
Omega_m:0.3074856, b1:0.517444
2023-07-02 10:34:33,190 [mcmc] Learn + convergence test @ 720 samples accepted.
2023-07-02 10:34:33,190 [mcmc] Ready to check convergence and learn a new proposal covmat
2023-07-02 10:34:33,195 [mcmc] - Acceptance rate: 0.478
2023-07-02 10:34:33,196 [mcmc] - Condition number = 14.3905
2023-07-02 10:34:33,196 [mcmc] - Eigenvalues = array([0.00280571, 0.04037571])
2023-07-02 10:34:33,196 [mcmc] - Convergence of means: R-1 = 0.040376 after 576 accepted steps
2023-07-02 10:34:33,196 [mcmc] - Updated covariance matrix of proposal pdf.
2023-07-02 10:34:33,196 [mcmc] array([[ 0.00010025, -0.00017427],
[-0.00017427, 0.0004754 ]])
2023-07-02 10:34:33,206 [mcmc] Dumped checkpoint and progress info, and current covmat.
2023-07-02 10:34:33,206 [model] Posterior to be computed for parameters {'Omega_m': 0.3226206442669289, 'b1': 0.48635618190946245}
2023-07-02 10:34:33,206 [prior] Evaluating prior at array([0.32262064, 0.48635618])
2023-07-02 10:34:33,206 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:33,206 [model] Got input parameters: {'Omega_m': 0.3226206442669289, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48635618190946245, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:33,206 [classy] Got parameters {'Omega_m': 0.3226206442669289, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:33,206 [classy] Computing new state
2023-07-02 10:34:33,207 [classy] Setting parameters: {'Omega_m': 0.3226206442669289, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:33,254 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.05770076482432}
2023-07-02 10:34:33,254 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:33,256 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00634728
2023-07-02 10:34:33,256 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48635618190946245, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:33,256 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:33,276 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.62595
2023-07-02 10:34:33,276 [model] Computed derived parameters: {}
2023-07-02 10:34:33,276 [mcmc] New sample, #721:
Omega_m:0.3074856, b1:0.5126666
2023-07-02 10:34:33,276 [model] Posterior to be computed for parameters {'Omega_m': 0.3226206442669289, 'b1': 0.4580917743938249}
2023-07-02 10:34:33,276 [prior] Evaluating prior at array([0.32262064, 0.45809177])
2023-07-02 10:34:33,276 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:33,277 [model] Got input parameters: {'Omega_m': 0.3226206442669289, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4580917743938249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:33,277 [classy] Got parameters {'Omega_m': 0.3226206442669289, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:33,277 [classy] Re-using computed results
2023-07-02 10:34:33,277 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.05770076482432}
2023-07-02 10:34:33,277 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:33,277 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4580917743938249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:33,277 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:33,297 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.494035
2023-07-02 10:34:33,297 [model] Computed derived parameters: {}
2023-07-02 10:34:33,297 [model] Posterior to be computed for parameters {'Omega_m': 0.3005717615089583, 'b1': 0.5246855112265184}
2023-07-02 10:34:33,297 [prior] Evaluating prior at array([0.30057176, 0.52468551])
2023-07-02 10:34:33,298 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:33,298 [model] Got input parameters: {'Omega_m': 0.3005717615089583, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5246855112265184, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:33,298 [classy] Got parameters {'Omega_m': 0.3005717615089583, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:33,298 [classy] Computing new state
2023-07-02 10:34:33,298 [classy] Setting parameters: {'Omega_m': 0.3005717615089583, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:33,345 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.71819880596033}
2023-07-02 10:34:33,345 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:33,347 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00916818
2023-07-02 10:34:33,347 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5246855112265184, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:33,347 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:33,366 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.63956
2023-07-02 10:34:33,366 [model] Computed derived parameters: {}
2023-07-02 10:34:33,366 [mcmc] New sample, #722:
Omega_m:0.3226206, b1:0.4863562
2023-07-02 10:34:33,366 [model] Posterior to be computed for parameters {'Omega_m': 0.3005717615089583, 'b1': 0.5133629000237084}
2023-07-02 10:34:33,366 [prior] Evaluating prior at array([0.30057176, 0.5133629 ])
2023-07-02 10:34:33,366 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:33,366 [model] Got input parameters: {'Omega_m': 0.3005717615089583, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5133629000237084, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:33,366 [classy] Got parameters {'Omega_m': 0.3005717615089583, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:33,366 [classy] Re-using computed results
2023-07-02 10:34:33,367 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.71819880596033}
2023-07-02 10:34:33,367 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:33,367 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5133629000237084, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:33,367 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:33,386 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.1929
2023-07-02 10:34:33,386 [model] Computed derived parameters: {}
2023-07-02 10:34:33,387 [mcmc] New sample, #723:
Omega_m:0.3005718, b1:0.5246855
2023-07-02 10:34:33,387 [model] Posterior to be computed for parameters {'Omega_m': 0.286652445967754, 'b1': 0.5375599550447375}
2023-07-02 10:34:33,387 [prior] Evaluating prior at array([0.28665245, 0.53755996])
2023-07-02 10:34:33,387 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:33,387 [model] Got input parameters: {'Omega_m': 0.286652445967754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5375599550447375, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:33,387 [classy] Got parameters {'Omega_m': 0.286652445967754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:33,387 [classy] Computing new state
2023-07-02 10:34:33,387 [classy] Setting parameters: {'Omega_m': 0.286652445967754, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:33,433 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.48753642130387}
2023-07-02 10:34:33,433 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:33,434 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0439068
2023-07-02 10:34:33,435 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5375599550447375, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:33,435 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:33,454 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.756
2023-07-02 10:34:33,454 [model] Computed derived parameters: {}
2023-07-02 10:34:33,455 [model] Posterior to be computed for parameters {'Omega_m': 0.3005717615089583, 'b1': 0.5382970998964345}
2023-07-02 10:34:33,455 [prior] Evaluating prior at array([0.30057176, 0.5382971 ])
2023-07-02 10:34:33,455 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:33,455 [model] Got input parameters: {'Omega_m': 0.3005717615089583, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5382970998964345, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:33,455 [classy] Got parameters {'Omega_m': 0.3005717615089583, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:33,455 [classy] Re-using computed results
2023-07-02 10:34:33,455 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.71819880596033}
2023-07-02 10:34:33,455 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:33,455 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5382970998964345, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:33,455 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:33,474 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.2777
2023-07-02 10:34:33,475 [model] Computed derived parameters: {}
2023-07-02 10:34:33,475 [mcmc] New sample, #724:
Omega_m:0.3005718, b1:0.5133629
2023-07-02 10:34:33,475 [model] Posterior to be computed for parameters {'Omega_m': 0.2605877872821915, 'b1': 0.6078044274270509}
2023-07-02 10:34:33,475 [prior] Evaluating prior at array([0.26058779, 0.60780443])
2023-07-02 10:34:33,475 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:33,475 [model] Got input parameters: {'Omega_m': 0.2605877872821915, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6078044274270509, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:33,475 [classy] Got parameters {'Omega_m': 0.2605877872821915, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:33,475 [classy] Computing new state
2023-07-02 10:34:33,475 [classy] Setting parameters: {'Omega_m': 0.2605877872821915, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:33,522 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 154.00930431794265}
2023-07-02 10:34:33,522 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:33,524 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.189424
2023-07-02 10:34:33,524 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6078044274270509, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:33,524 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:33,544 [fs_likelihood.fslikelihood] Computed log-likelihood = -18.3492
2023-07-02 10:34:33,544 [model] Computed derived parameters: {}
2023-07-02 10:34:33,544 [model] Posterior to be computed for parameters {'Omega_m': 0.3005717615089583, 'b1': 0.5531083626864187}
2023-07-02 10:34:33,544 [prior] Evaluating prior at array([0.30057176, 0.55310836])
2023-07-02 10:34:33,544 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:33,544 [model] Got input parameters: {'Omega_m': 0.3005717615089583, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5531083626864187, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:33,544 [classy] Got parameters {'Omega_m': 0.3005717615089583, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:33,544 [classy] Re-using computed results
2023-07-02 10:34:33,544 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.71819880596033}
2023-07-02 10:34:33,544 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:33,544 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5531083626864187, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:33,544 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:33,564 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.275504
2023-07-02 10:34:33,564 [model] Computed derived parameters: {}
2023-07-02 10:34:33,564 [model] Posterior to be computed for parameters {'Omega_m': 0.31768967802768583, 'b1': 0.5085396619949156}
2023-07-02 10:34:33,564 [prior] Evaluating prior at array([0.31768968, 0.50853966])
2023-07-02 10:34:33,564 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:33,564 [model] Got input parameters: {'Omega_m': 0.31768967802768583, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5085396619949156, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:33,564 [classy] Got parameters {'Omega_m': 0.31768967802768583, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:33,564 [classy] Computing new state
2023-07-02 10:34:33,564 [classy] Setting parameters: {'Omega_m': 0.31768967802768583, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:33,611 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.6383380396427}
2023-07-02 10:34:33,611 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:33,613 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00184278
2023-07-02 10:34:33,613 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5085396619949156, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:33,613 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:33,632 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.42392
2023-07-02 10:34:33,632 [model] Computed derived parameters: {}
2023-07-02 10:34:33,632 [mcmc] New sample, #725:
Omega_m:0.3005718, b1:0.5382971
2023-07-02 10:34:33,632 [model] Posterior to be computed for parameters {'Omega_m': 0.31768967802768583, 'b1': 0.5052693608425649}
2023-07-02 10:34:33,632 [prior] Evaluating prior at array([0.31768968, 0.50526936])
2023-07-02 10:34:33,632 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:33,632 [model] Got input parameters: {'Omega_m': 0.31768967802768583, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5052693608425649, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:33,633 [classy] Got parameters {'Omega_m': 0.31768967802768583, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:33,633 [classy] Re-using computed results
2023-07-02 10:34:33,633 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.6383380396427}
2023-07-02 10:34:33,633 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:33,633 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5052693608425649, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:33,633 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:33,653 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.62967
2023-07-02 10:34:33,653 [model] Computed derived parameters: {}
2023-07-02 10:34:33,653 [mcmc] New sample, #726:
Omega_m:0.3176897, b1:0.5085397
2023-07-02 10:34:33,653 [model] Posterior to be computed for parameters {'Omega_m': 0.3349306489081108, 'b1': 0.4752980077415698}
2023-07-02 10:34:33,653 [prior] Evaluating prior at array([0.33493065, 0.47529801])
2023-07-02 10:34:33,653 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:33,653 [model] Got input parameters: {'Omega_m': 0.3349306489081108, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4752980077415698, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:33,653 [classy] Got parameters {'Omega_m': 0.3349306489081108, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:33,653 [classy] Computing new state
2023-07-02 10:34:33,653 [classy] Setting parameters: {'Omega_m': 0.3349306489081108, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:33,700 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.64218396451753}
2023-07-02 10:34:33,700 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:33,702 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.029454
2023-07-02 10:34:33,702 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4752980077415698, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:33,702 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:33,721 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.572115
2023-07-02 10:34:33,721 [model] Computed derived parameters: {}
2023-07-02 10:34:33,721 [model] Posterior to be computed for parameters {'Omega_m': 0.31768967802768583, 'b1': 0.4978938737703222}
2023-07-02 10:34:33,721 [prior] Evaluating prior at array([0.31768968, 0.49789387])
2023-07-02 10:34:33,722 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:33,722 [model] Got input parameters: {'Omega_m': 0.31768967802768583, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4978938737703222, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:33,722 [classy] Got parameters {'Omega_m': 0.31768967802768583, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:33,722 [classy] Re-using computed results
2023-07-02 10:34:33,722 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.6383380396427}
2023-07-02 10:34:33,722 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:33,722 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4978938737703222, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:33,722 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:33,741 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.87604
2023-07-02 10:34:33,741 [model] Computed derived parameters: {}
2023-07-02 10:34:33,742 [mcmc] New sample, #727:
Omega_m:0.3176897, b1:0.5052694
2023-07-02 10:34:33,742 [model] Posterior to be computed for parameters {'Omega_m': 0.3200906788906161, 'b1': 0.49372002270603094}
2023-07-02 10:34:33,742 [prior] Evaluating prior at array([0.32009068, 0.49372002])
2023-07-02 10:34:33,742 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:33,742 [model] Got input parameters: {'Omega_m': 0.3200906788906161, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49372002270603094, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:33,742 [classy] Got parameters {'Omega_m': 0.3200906788906161, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:33,742 [classy] Computing new state
2023-07-02 10:34:33,742 [classy] Setting parameters: {'Omega_m': 0.3200906788906161, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:33,788 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.3546186370542}
2023-07-02 10:34:33,788 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:33,790 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00368414
2023-07-02 10:34:33,790 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49372002270603094, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:33,790 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:33,810 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.77604
2023-07-02 10:34:33,810 [model] Computed derived parameters: {}
2023-07-02 10:34:33,810 [mcmc] New sample, #728:
Omega_m:0.3176897, b1:0.4978939
2023-07-02 10:34:33,810 [model] Posterior to be computed for parameters {'Omega_m': 0.3200906788906161, 'b1': 0.5292142793968342}
2023-07-02 10:34:33,810 [prior] Evaluating prior at array([0.32009068, 0.52921428])
2023-07-02 10:34:33,810 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:33,810 [model] Got input parameters: {'Omega_m': 0.3200906788906161, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5292142793968342, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:33,810 [classy] Got parameters {'Omega_m': 0.3200906788906161, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:33,810 [classy] Re-using computed results
2023-07-02 10:34:33,810 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.3546186370542}
2023-07-02 10:34:33,810 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:33,810 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5292142793968342, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:33,810 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:33,829 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.2917
2023-07-02 10:34:33,830 [model] Computed derived parameters: {}
2023-07-02 10:34:33,830 [model] Posterior to be computed for parameters {'Omega_m': 0.3451827299049178, 'b1': 0.45010051158953845}
2023-07-02 10:34:33,830 [prior] Evaluating prior at array([0.34518273, 0.45010051])
2023-07-02 10:34:33,830 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:33,830 [model] Got input parameters: {'Omega_m': 0.3451827299049178, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45010051158953845, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:33,830 [classy] Got parameters {'Omega_m': 0.3451827299049178, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:33,830 [classy] Computing new state
2023-07-02 10:34:33,830 [classy] Setting parameters: {'Omega_m': 0.3451827299049178, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:33,876 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.49878836173818}
2023-07-02 10:34:33,877 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:33,878 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0607932
2023-07-02 10:34:33,878 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45010051158953845, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:33,878 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:33,898 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.57891
2023-07-02 10:34:33,898 [model] Computed derived parameters: {}
2023-07-02 10:34:33,898 [model] Posterior to be computed for parameters {'Omega_m': 0.3200906788906161, 'b1': 0.5676139708129573}
2023-07-02 10:34:33,899 [prior] Evaluating prior at array([0.32009068, 0.56761397])
2023-07-02 10:34:33,899 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:33,899 [model] Got input parameters: {'Omega_m': 0.3200906788906161, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5676139708129573, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:33,899 [classy] Got parameters {'Omega_m': 0.3200906788906161, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:33,899 [classy] Re-using computed results
2023-07-02 10:34:33,899 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.3546186370542}
2023-07-02 10:34:33,899 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:33,899 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5676139708129573, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:33,899 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:33,918 [fs_likelihood.fslikelihood] Computed log-likelihood = -14.3145
2023-07-02 10:34:33,918 [model] Computed derived parameters: {}
2023-07-02 10:34:33,918 [model] Posterior to be computed for parameters {'Omega_m': 0.3483233719210537, 'b1': 0.44464088338865193}
2023-07-02 10:34:33,918 [prior] Evaluating prior at array([0.34832337, 0.44464088])
2023-07-02 10:34:33,919 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:33,919 [model] Got input parameters: {'Omega_m': 0.3483233719210537, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44464088338865193, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:33,919 [classy] Got parameters {'Omega_m': 0.3483233719210537, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:33,919 [classy] Computing new state
2023-07-02 10:34:33,919 [classy] Setting parameters: {'Omega_m': 0.3483233719210537, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:33,965 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.15474376189673}
2023-07-02 10:34:33,965 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:33,967 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0724579
2023-07-02 10:34:33,967 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44464088338865193, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:33,967 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:33,987 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.49276
2023-07-02 10:34:33,987 [model] Computed derived parameters: {}
2023-07-02 10:34:33,987 [model] Posterior to be computed for parameters {'Omega_m': 0.3200906788906161, 'b1': 0.5134282294216049}
2023-07-02 10:34:33,987 [prior] Evaluating prior at array([0.32009068, 0.51342823])
2023-07-02 10:34:33,987 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:33,987 [model] Got input parameters: {'Omega_m': 0.3200906788906161, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5134282294216049, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:33,987 [classy] Got parameters {'Omega_m': 0.3200906788906161, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:33,988 [classy] Re-using computed results
2023-07-02 10:34:33,988 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.3546186370542}
2023-07-02 10:34:33,988 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:33,988 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5134282294216049, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:33,988 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:34,007 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.41455
2023-07-02 10:34:34,008 [model] Computed derived parameters: {}
2023-07-02 10:34:34,008 [model] Posterior to be computed for parameters {'Omega_m': 0.3419989952203588, 'b1': 0.4556350512087163}
2023-07-02 10:34:34,008 [prior] Evaluating prior at array([0.341999 , 0.45563505])
2023-07-02 10:34:34,008 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:34,008 [model] Got input parameters: {'Omega_m': 0.3419989952203588, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4556350512087163, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:34,008 [classy] Got parameters {'Omega_m': 0.3419989952203588, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:34,008 [classy] Computing new state
2023-07-02 10:34:34,008 [classy] Setting parameters: {'Omega_m': 0.3419989952203588, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:34,055 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.85052036542538}
2023-07-02 10:34:34,055 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:34,057 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0499382
2023-07-02 10:34:34,057 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4556350512087163, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:34,057 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:34,078 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.727489
2023-07-02 10:34:34,078 [model] Computed derived parameters: {}
2023-07-02 10:34:34,079 [model] Posterior to be computed for parameters {'Omega_m': 0.3200906788906161, 'b1': 0.54611710067799}
2023-07-02 10:34:34,079 [prior] Evaluating prior at array([0.32009068, 0.5461171 ])
2023-07-02 10:34:34,079 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:34,079 [model] Got input parameters: {'Omega_m': 0.3200906788906161, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.54611710067799, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:34,079 [classy] Got parameters {'Omega_m': 0.3200906788906161, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:34,079 [classy] Re-using computed results
2023-07-02 10:34:34,079 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.3546186370542}
2023-07-02 10:34:34,079 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:34,079 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.54611710067799, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:34,079 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:34,099 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.86491
2023-07-02 10:34:34,099 [model] Computed derived parameters: {}
2023-07-02 10:34:34,099 [model] Posterior to be computed for parameters {'Omega_m': 0.307821221076077, 'b1': 0.5150489986127667}
2023-07-02 10:34:34,099 [prior] Evaluating prior at array([0.30782122, 0.515049 ])
2023-07-02 10:34:34,099 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:34,099 [model] Got input parameters: {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5150489986127667, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:34,099 [classy] Got parameters {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:34,099 [classy] Computing new state
2023-07-02 10:34:34,100 [classy] Setting parameters: {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:34,150 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.82493684400143}
2023-07-02 10:34:34,150 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:34,152 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00155131
2023-07-02 10:34:34,152 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5150489986127667, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:34,153 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:34,173 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.60424
2023-07-02 10:34:34,173 [model] Computed derived parameters: {}
2023-07-02 10:34:34,174 [mcmc] New sample, #729:
Omega_m:0.3200907, b1:0.49372
2023-07-02 10:34:34,174 [model] Posterior to be computed for parameters {'Omega_m': 0.307821221076077, 'b1': 0.4158374720263018}
2023-07-02 10:34:34,174 [prior] Evaluating prior at array([0.30782122, 0.41583747])
2023-07-02 10:34:34,174 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:34,174 [model] Got input parameters: {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4158374720263018, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:34,174 [classy] Got parameters {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:34,174 [classy] Re-using computed results
2023-07-02 10:34:34,174 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.82493684400143}
2023-07-02 10:34:34,174 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:34,174 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4158374720263018, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:34,174 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:34,194 [fs_likelihood.fslikelihood] Computed log-likelihood = -20.4616
2023-07-02 10:34:34,194 [model] Computed derived parameters: {}
2023-07-02 10:34:34,194 [model] Posterior to be computed for parameters {'Omega_m': 0.29658447493405954, 'b1': 0.5345827295531178}
2023-07-02 10:34:34,195 [prior] Evaluating prior at array([0.29658447, 0.53458273])
2023-07-02 10:34:34,195 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:34,195 [model] Got input parameters: {'Omega_m': 0.29658447493405954, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5345827295531178, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:34,195 [classy] Got parameters {'Omega_m': 0.29658447493405954, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:34,195 [classy] Computing new state
2023-07-02 10:34:34,195 [classy] Setting parameters: {'Omega_m': 0.29658447493405954, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:34,251 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.21764210412306}
2023-07-02 10:34:34,251 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:34,253 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0163395
2023-07-02 10:34:34,253 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5345827295531178, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:34,253 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:34,282 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.820035
2023-07-02 10:34:34,282 [model] Computed derived parameters: {}
2023-07-02 10:34:34,282 [model] Posterior to be computed for parameters {'Omega_m': 0.307821221076077, 'b1': 0.5552682468125634}
2023-07-02 10:34:34,282 [prior] Evaluating prior at array([0.30782122, 0.55526825])
2023-07-02 10:34:34,283 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:34,283 [model] Got input parameters: {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5552682468125634, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:34,283 [classy] Got parameters {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:34,283 [classy] Re-using computed results
2023-07-02 10:34:34,283 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.82493684400143}
2023-07-02 10:34:34,283 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:34,283 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5552682468125634, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:34,283 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:34,309 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.28399
2023-07-02 10:34:34,309 [model] Computed derived parameters: {}
2023-07-02 10:34:34,309 [model] Posterior to be computed for parameters {'Omega_m': 0.34179027717776245, 'b1': 0.45599788240868705}
2023-07-02 10:34:34,309 [prior] Evaluating prior at array([0.34179028, 0.45599788])
2023-07-02 10:34:34,310 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:34,310 [model] Got input parameters: {'Omega_m': 0.34179027717776245, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45599788240868705, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:34,310 [classy] Got parameters {'Omega_m': 0.34179027717776245, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:34,310 [classy] Computing new state
2023-07-02 10:34:34,310 [classy] Setting parameters: {'Omega_m': 0.34179027717776245, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:34,357 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.8736851165023}
2023-07-02 10:34:34,357 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:34,359 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0492612
2023-07-02 10:34:34,359 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45599788240868705, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:34,359 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:34,379 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.674396
2023-07-02 10:34:34,379 [model] Computed derived parameters: {}
2023-07-02 10:34:34,379 [model] Posterior to be computed for parameters {'Omega_m': 0.307821221076077, 'b1': 0.5483848172324856}
2023-07-02 10:34:34,379 [prior] Evaluating prior at array([0.30782122, 0.54838482])
2023-07-02 10:34:34,379 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:34,379 [model] Got input parameters: {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5483848172324856, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:34,379 [classy] Got parameters {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:34,379 [classy] Re-using computed results
2023-07-02 10:34:34,379 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.82493684400143}
2023-07-02 10:34:34,379 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:34,379 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5483848172324856, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:34,379 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:34,399 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.783893
2023-07-02 10:34:34,399 [model] Computed derived parameters: {}
2023-07-02 10:34:34,399 [model] Posterior to be computed for parameters {'Omega_m': 0.33768869219887154, 'b1': 0.4631279943106593}
2023-07-02 10:34:34,399 [prior] Evaluating prior at array([0.33768869, 0.46312799])
2023-07-02 10:34:34,399 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:34,399 [model] Got input parameters: {'Omega_m': 0.33768869219887154, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4631279943106593, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:34,399 [classy] Got parameters {'Omega_m': 0.33768869219887154, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:34,399 [classy] Computing new state
2023-07-02 10:34:34,399 [classy] Setting parameters: {'Omega_m': 0.33768869219887154, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:34,450 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.3314978558565}
2023-07-02 10:34:34,450 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:34,452 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0368428
2023-07-02 10:34:34,452 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4631279943106593, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:34,452 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:34,472 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.298356
2023-07-02 10:34:34,472 [model] Computed derived parameters: {}
2023-07-02 10:34:34,472 [model] Posterior to be computed for parameters {'Omega_m': 0.307821221076077, 'b1': 0.5538579541844277}
2023-07-02 10:34:34,472 [prior] Evaluating prior at array([0.30782122, 0.55385795])
2023-07-02 10:34:34,472 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:34,472 [model] Got input parameters: {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5538579541844277, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:34,472 [classy] Got parameters {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:34,472 [classy] Re-using computed results
2023-07-02 10:34:34,472 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.82493684400143}
2023-07-02 10:34:34,472 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:34,472 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5538579541844277, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:34,472 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:34,492 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.95349
2023-07-02 10:34:34,492 [model] Computed derived parameters: {}
2023-07-02 10:34:34,492 [model] Posterior to be computed for parameters {'Omega_m': 0.3279371187006351, 'b1': 0.4800799313351448}
2023-07-02 10:34:34,493 [prior] Evaluating prior at array([0.32793712, 0.48007993])
2023-07-02 10:34:34,493 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:34,493 [model] Got input parameters: {'Omega_m': 0.3279371187006351, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4800799313351448, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:34,493 [classy] Got parameters {'Omega_m': 0.3279371187006351, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:34,493 [classy] Computing new state
2023-07-02 10:34:34,493 [classy] Setting parameters: {'Omega_m': 0.3279371187006351, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:34,539 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.44047976212397}
2023-07-02 10:34:34,539 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:34,541 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0143012
2023-07-02 10:34:34,541 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4800799313351448, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:34,541 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:34,561 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.03339
2023-07-02 10:34:34,561 [model] Computed derived parameters: {}
2023-07-02 10:34:34,561 [model] Posterior to be computed for parameters {'Omega_m': 0.307821221076077, 'b1': 0.6231285020999274}
2023-07-02 10:34:34,561 [prior] Evaluating prior at array([0.30782122, 0.6231285 ])
2023-07-02 10:34:34,562 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:34,562 [model] Got input parameters: {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6231285020999274, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:34,562 [classy] Got parameters {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:34,562 [classy] Re-using computed results
2023-07-02 10:34:34,562 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.82493684400143}
2023-07-02 10:34:34,562 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:34,562 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6231285020999274, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:34,562 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:34,581 [fs_likelihood.fslikelihood] Computed log-likelihood = -33.3001
2023-07-02 10:34:34,581 [model] Computed derived parameters: {}
2023-07-02 10:34:34,582 [model] Posterior to be computed for parameters {'Omega_m': 0.26332381457083465, 'b1': 0.5924023850140703}
2023-07-02 10:34:34,582 [prior] Evaluating prior at array([0.26332381, 0.59240239])
2023-07-02 10:34:34,582 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:34,582 [model] Got input parameters: {'Omega_m': 0.26332381457083465, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5924023850140703, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:34,582 [classy] Got parameters {'Omega_m': 0.26332381457083465, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:34,582 [classy] Computing new state
2023-07-02 10:34:34,582 [classy] Setting parameters: {'Omega_m': 0.26332381457083465, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:34,628 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.62596951588094}
2023-07-02 10:34:34,628 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:34,630 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.168723
2023-07-02 10:34:34,630 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5924023850140703, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:34,630 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:34,649 [fs_likelihood.fslikelihood] Computed log-likelihood = -15.862
2023-07-02 10:34:34,649 [model] Computed derived parameters: {}
2023-07-02 10:34:34,650 [model] Posterior to be computed for parameters {'Omega_m': 0.307821221076077, 'b1': 0.5351445489868382}
2023-07-02 10:34:34,650 [prior] Evaluating prior at array([0.30782122, 0.53514455])
2023-07-02 10:34:34,650 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:34,650 [model] Got input parameters: {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5351445489868382, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:34,650 [classy] Got parameters {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:34,650 [classy] Re-using computed results
2023-07-02 10:34:34,650 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.82493684400143}
2023-07-02 10:34:34,650 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:34,650 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5351445489868382, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:34,650 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:34,670 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.31631
2023-07-02 10:34:34,670 [model] Computed derived parameters: {}
2023-07-02 10:34:34,670 [model] Posterior to be computed for parameters {'Omega_m': 0.2867833487250209, 'b1': 0.5516208080021705}
2023-07-02 10:34:34,670 [prior] Evaluating prior at array([0.28678335, 0.55162081])
2023-07-02 10:34:34,670 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:34,670 [model] Got input parameters: {'Omega_m': 0.2867833487250209, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5516208080021705, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:34,670 [classy] Got parameters {'Omega_m': 0.2867833487250209, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:34,670 [classy] Computing new state
2023-07-02 10:34:34,670 [classy] Setting parameters: {'Omega_m': 0.2867833487250209, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:34,718 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.47055417026638}
2023-07-02 10:34:34,718 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:34,720 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0434502
2023-07-02 10:34:34,720 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5516208080021705, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:34,720 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:34,739 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.18516
2023-07-02 10:34:34,739 [model] Computed derived parameters: {}
2023-07-02 10:34:34,739 [model] Posterior to be computed for parameters {'Omega_m': 0.307821221076077, 'b1': 0.5166446013770936}
2023-07-02 10:34:34,739 [prior] Evaluating prior at array([0.30782122, 0.5166446 ])
2023-07-02 10:34:34,739 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:34,739 [model] Got input parameters: {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5166446013770936, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:34,739 [classy] Got parameters {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:34,739 [classy] Re-using computed results
2023-07-02 10:34:34,739 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.82493684400143}
2023-07-02 10:34:34,740 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:34,740 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5166446013770936, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:34,740 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:34,759 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.58313
2023-07-02 10:34:34,759 [model] Computed derived parameters: {}
2023-07-02 10:34:34,760 [mcmc] New sample, #730:
Omega_m:0.3078212, b1:0.515049
2023-07-02 10:34:34,760 [model] Posterior to be computed for parameters {'Omega_m': 0.25137402758935745, 'b1': 0.6147712544109722}
2023-07-02 10:34:34,760 [prior] Evaluating prior at array([0.25137403, 0.61477125])
2023-07-02 10:34:34,760 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:34,760 [model] Got input parameters: {'Omega_m': 0.25137402758935745, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6147712544109722, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:34,760 [classy] Got parameters {'Omega_m': 0.25137402758935745, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:34,760 [classy] Computing new state
2023-07-02 10:34:34,760 [classy] Setting parameters: {'Omega_m': 0.25137402758935745, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:34,806 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 155.32549280324454}
2023-07-02 10:34:34,806 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:34,808 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.269427
2023-07-02 10:34:34,808 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6147712544109722, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:34,808 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:34,828 [fs_likelihood.fslikelihood] Computed log-likelihood = -26.9467
2023-07-02 10:34:34,828 [model] Computed derived parameters: {}
2023-07-02 10:34:34,828 [model] Posterior to be computed for parameters {'Omega_m': 0.307821221076077, 'b1': 0.5582116231789337}
2023-07-02 10:34:34,828 [prior] Evaluating prior at array([0.30782122, 0.55821162])
2023-07-02 10:34:34,828 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:34,828 [model] Got input parameters: {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5582116231789337, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:34,828 [classy] Got parameters {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:34,828 [classy] Re-using computed results
2023-07-02 10:34:34,828 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.82493684400143}
2023-07-02 10:34:34,828 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:34,828 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5582116231789337, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:34,828 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:34,847 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.01255
2023-07-02 10:34:34,847 [model] Computed derived parameters: {}
2023-07-02 10:34:34,847 [model] Posterior to be computed for parameters {'Omega_m': 0.3034111739944942, 'b1': 0.5243109375243346}
2023-07-02 10:34:34,848 [prior] Evaluating prior at array([0.30341117, 0.52431094])
2023-07-02 10:34:34,848 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:34,848 [model] Got input parameters: {'Omega_m': 0.3034111739944942, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5243109375243346, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:34,848 [classy] Got parameters {'Omega_m': 0.3034111739944942, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:34,848 [classy] Computing new state
2023-07-02 10:34:34,848 [classy] Setting parameters: {'Omega_m': 0.3034111739944942, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:34,894 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.36610639144422}
2023-07-02 10:34:34,894 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:34,896 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00536633
2023-07-02 10:34:34,896 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5243109375243346, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:34,896 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:34,917 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.08404
2023-07-02 10:34:34,917 [model] Computed derived parameters: {}
2023-07-02 10:34:34,917 [model] Posterior to be computed for parameters {'Omega_m': 0.307821221076077, 'b1': 0.5277396481046734}
2023-07-02 10:34:34,917 [prior] Evaluating prior at array([0.30782122, 0.52773965])
2023-07-02 10:34:34,917 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:34,917 [model] Got input parameters: {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5277396481046734, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:34,917 [classy] Got parameters {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:34,917 [classy] Re-using computed results
2023-07-02 10:34:34,917 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.82493684400143}
2023-07-02 10:34:34,917 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:34,917 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5277396481046734, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:34,917 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:34,937 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.05206
2023-07-02 10:34:34,937 [model] Computed derived parameters: {}
2023-07-02 10:34:34,937 [mcmc] New sample, #731:
Omega_m:0.3078212, b1:0.5166446
2023-07-02 10:34:34,937 [model] Posterior to be computed for parameters {'Omega_m': 0.30366365165102466, 'b1': 0.5349670822291416}
2023-07-02 10:34:34,937 [prior] Evaluating prior at array([0.30366365, 0.53496708])
2023-07-02 10:34:34,937 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:34,937 [model] Got input parameters: {'Omega_m': 0.30366365165102466, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5349670822291416, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:34,937 [classy] Got parameters {'Omega_m': 0.30366365165102466, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:34,937 [classy] Computing new state
2023-07-02 10:34:34,937 [classy] Setting parameters: {'Omega_m': 0.30366365165102466, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:34,984 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.334937745333}
2023-07-02 10:34:34,984 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:34,986 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00507982
2023-07-02 10:34:34,986 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5349670822291416, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:34,986 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:35,005 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.61014
2023-07-02 10:34:35,005 [model] Computed derived parameters: {}
2023-07-02 10:34:35,005 [model] Posterior to be computed for parameters {'Omega_m': 0.307821221076077, 'b1': 0.5654594376991975}
2023-07-02 10:34:35,005 [prior] Evaluating prior at array([0.30782122, 0.56545944])
2023-07-02 10:34:35,005 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:35,005 [model] Got input parameters: {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5654594376991975, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:35,005 [classy] Got parameters {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:35,005 [classy] Re-using computed results
2023-07-02 10:34:35,005 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.82493684400143}
2023-07-02 10:34:35,005 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:35,005 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5654594376991975, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:35,005 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:35,026 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.0326
2023-07-02 10:34:35,026 [model] Computed derived parameters: {}
2023-07-02 10:34:35,026 [model] Posterior to be computed for parameters {'Omega_m': 0.3340034526797648, 'b1': 0.48222498922562435}
2023-07-02 10:34:35,026 [prior] Evaluating prior at array([0.33400345, 0.48222499])
2023-07-02 10:34:35,026 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:35,026 [model] Got input parameters: {'Omega_m': 0.3340034526797648, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48222498922562435, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:35,026 [classy] Got parameters {'Omega_m': 0.3340034526797648, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:35,026 [classy] Computing new state
2023-07-02 10:34:35,026 [classy] Setting parameters: {'Omega_m': 0.3340034526797648, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:35,073 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.74714886034815}
2023-07-02 10:34:35,073 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:35,075 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0271471
2023-07-02 10:34:35,075 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48222498922562435, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:35,075 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:35,095 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.347465
2023-07-02 10:34:35,095 [model] Computed derived parameters: {}
2023-07-02 10:34:35,095 [model] Posterior to be computed for parameters {'Omega_m': 0.307821221076077, 'b1': 0.5484608684177067}
2023-07-02 10:34:35,095 [prior] Evaluating prior at array([0.30782122, 0.54846087])
2023-07-02 10:34:35,095 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:35,095 [model] Got input parameters: {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5484608684177067, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:35,095 [classy] Got parameters {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:35,095 [classy] Re-using computed results
2023-07-02 10:34:35,095 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.82493684400143}
2023-07-02 10:34:35,095 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:35,095 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5484608684177067, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:35,095 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:35,115 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.798922
2023-07-02 10:34:35,115 [model] Computed derived parameters: {}
2023-07-02 10:34:35,116 [model] Posterior to be computed for parameters {'Omega_m': 0.2602533506523905, 'b1': 0.6104306665292432}
2023-07-02 10:34:35,116 [prior] Evaluating prior at array([0.26025335, 0.61043067])
2023-07-02 10:34:35,116 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:35,116 [model] Got input parameters: {'Omega_m': 0.2602533506523905, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6104306665292432, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:35,116 [classy] Got parameters {'Omega_m': 0.2602533506523905, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:35,116 [classy] Computing new state
2023-07-02 10:34:35,116 [classy] Setting parameters: {'Omega_m': 0.2602533506523905, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:35,164 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 154.05638878019178}
2023-07-02 10:34:35,164 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:35,166 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.192048
2023-07-02 10:34:35,166 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6104306665292432, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:35,166 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:35,185 [fs_likelihood.fslikelihood] Computed log-likelihood = -18.7447
2023-07-02 10:34:35,185 [model] Computed derived parameters: {}
2023-07-02 10:34:35,186 [model] Posterior to be computed for parameters {'Omega_m': 0.307821221076077, 'b1': 0.5768476062596689}
2023-07-02 10:34:35,186 [prior] Evaluating prior at array([0.30782122, 0.57684761])
2023-07-02 10:34:35,186 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:35,186 [model] Got input parameters: {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5768476062596689, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:35,186 [classy] Got parameters {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:35,186 [classy] Re-using computed results
2023-07-02 10:34:35,186 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.82493684400143}
2023-07-02 10:34:35,186 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:35,186 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5768476062596689, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:35,186 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:35,205 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.86921
2023-07-02 10:34:35,205 [model] Computed derived parameters: {}
2023-07-02 10:34:35,206 [model] Posterior to be computed for parameters {'Omega_m': 0.28793212553530145, 'b1': 0.562314447252952}
2023-07-02 10:34:35,206 [prior] Evaluating prior at array([0.28793213, 0.56231445])
2023-07-02 10:34:35,206 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:35,206 [model] Got input parameters: {'Omega_m': 0.28793212553530145, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.562314447252952, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:35,206 [classy] Got parameters {'Omega_m': 0.28793212553530145, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:35,206 [classy] Computing new state
2023-07-02 10:34:35,206 [classy] Setting parameters: {'Omega_m': 0.28793212553530145, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:35,253 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.32180444893572}
2023-07-02 10:34:35,253 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:35,255 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0395525
2023-07-02 10:34:35,255 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.562314447252952, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:35,255 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:35,275 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.1959
2023-07-02 10:34:35,275 [model] Computed derived parameters: {}
2023-07-02 10:34:35,275 [model] Posterior to be computed for parameters {'Omega_m': 0.307821221076077, 'b1': 0.486805209231203}
2023-07-02 10:34:35,275 [prior] Evaluating prior at array([0.30782122, 0.48680521])
2023-07-02 10:34:35,276 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:35,276 [model] Got input parameters: {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.486805209231203, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:35,276 [classy] Got parameters {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:35,276 [classy] Re-using computed results
2023-07-02 10:34:35,276 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.82493684400143}
2023-07-02 10:34:35,276 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:35,276 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.486805209231203, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:35,276 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:35,296 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.7702
2023-07-02 10:34:35,296 [model] Computed derived parameters: {}
2023-07-02 10:34:35,296 [model] Posterior to be computed for parameters {'Omega_m': 0.26251651366528567, 'b1': 0.6064964299798615}
2023-07-02 10:34:35,296 [prior] Evaluating prior at array([0.26251651, 0.60649643])
2023-07-02 10:34:35,296 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:35,296 [model] Got input parameters: {'Omega_m': 0.26251651366528567, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6064964299798615, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:35,296 [classy] Got parameters {'Omega_m': 0.26251651366528567, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:35,296 [classy] Computing new state
2023-07-02 10:34:35,296 [classy] Setting parameters: {'Omega_m': 0.26251651366528567, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:35,343 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.738728640241}
2023-07-02 10:34:35,343 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:35,345 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.17469
2023-07-02 10:34:35,345 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6064964299798615, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:35,345 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:35,365 [fs_likelihood.fslikelihood] Computed log-likelihood = -16.8456
2023-07-02 10:34:35,365 [model] Computed derived parameters: {}
2023-07-02 10:34:35,365 [model] Posterior to be computed for parameters {'Omega_m': 0.307821221076077, 'b1': 0.5851839027485815}
2023-07-02 10:34:35,365 [prior] Evaluating prior at array([0.30782122, 0.5851839 ])
2023-07-02 10:34:35,365 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:35,365 [model] Got input parameters: {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5851839027485815, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:35,365 [classy] Got parameters {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:35,365 [classy] Re-using computed results
2023-07-02 10:34:35,365 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.82493684400143}
2023-07-02 10:34:35,365 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:35,365 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5851839027485815, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:35,365 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:35,385 [fs_likelihood.fslikelihood] Computed log-likelihood = -12.2038
2023-07-02 10:34:35,385 [model] Computed derived parameters: {}
2023-07-02 10:34:35,385 [model] Posterior to be computed for parameters {'Omega_m': 0.3396853863429277, 'b1': 0.4723476313148563}
2023-07-02 10:34:35,385 [prior] Evaluating prior at array([0.33968539, 0.47234763])
2023-07-02 10:34:35,385 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:35,385 [model] Got input parameters: {'Omega_m': 0.3396853863429277, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4723476313148563, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:35,385 [classy] Got parameters {'Omega_m': 0.3396853863429277, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:35,385 [classy] Computing new state
2023-07-02 10:34:35,385 [classy] Setting parameters: {'Omega_m': 0.3396853863429277, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:35,436 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.10800296388737}
2023-07-02 10:34:35,436 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:35,438 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.042677
2023-07-02 10:34:35,439 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4723476313148563, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:35,439 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:35,459 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.894634
2023-07-02 10:34:35,459 [model] Computed derived parameters: {}
2023-07-02 10:34:35,460 [model] Posterior to be computed for parameters {'Omega_m': 0.307821221076077, 'b1': 0.5019667928152267}
2023-07-02 10:34:35,460 [prior] Evaluating prior at array([0.30782122, 0.50196679])
2023-07-02 10:34:35,460 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:35,460 [model] Got input parameters: {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5019667928152267, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:35,460 [classy] Got parameters {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:35,460 [classy] Re-using computed results
2023-07-02 10:34:35,460 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.82493684400143}
2023-07-02 10:34:35,460 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:35,460 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5019667928152267, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:35,460 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:35,480 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.26664
2023-07-02 10:34:35,480 [model] Computed derived parameters: {}
2023-07-02 10:34:35,480 [mcmc] New sample, #732:
Omega_m:0.3078212, b1:0.5277396
2023-07-02 10:34:35,480 [model] Posterior to be computed for parameters {'Omega_m': 0.2899500680203179, 'b1': 0.5330336417920566}
2023-07-02 10:34:35,481 [prior] Evaluating prior at array([0.28995007, 0.53303364])
2023-07-02 10:34:35,481 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:35,481 [model] Got input parameters: {'Omega_m': 0.2899500680203179, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5330336417920566, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:35,481 [classy] Got parameters {'Omega_m': 0.2899500680203179, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:35,481 [classy] Computing new state
2023-07-02 10:34:35,481 [classy] Setting parameters: {'Omega_m': 0.2899500680203179, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:35,528 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.06174566377476}
2023-07-02 10:34:35,528 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:35,530 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0331765
2023-07-02 10:34:35,530 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5330336417920566, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:35,530 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:35,549 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.47888
2023-07-02 10:34:35,549 [model] Computed derived parameters: {}
2023-07-02 10:34:35,549 [model] Posterior to be computed for parameters {'Omega_m': 0.307821221076077, 'b1': 0.4999325702979241}
2023-07-02 10:34:35,549 [prior] Evaluating prior at array([0.30782122, 0.49993257])
2023-07-02 10:34:35,549 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:35,549 [model] Got input parameters: {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4999325702979241, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:35,549 [classy] Got parameters {'Omega_m': 0.307821221076077, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:35,549 [classy] Re-using computed results
2023-07-02 10:34:35,549 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.82493684400143}
2023-07-02 10:34:35,549 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:35,549 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4999325702979241, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:35,550 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:35,569 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.13372
2023-07-02 10:34:35,569 [model] Computed derived parameters: {}
2023-07-02 10:34:35,569 [mcmc] New sample, #733:
Omega_m:0.3078212, b1:0.5019668
2023-07-02 10:34:35,569 [model] Posterior to be computed for parameters {'Omega_m': 0.30106300269950487, 'b1': 0.5116809196630896}
2023-07-02 10:34:35,570 [prior] Evaluating prior at array([0.301063 , 0.51168092])
2023-07-02 10:34:35,570 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:35,570 [model] Got input parameters: {'Omega_m': 0.30106300269950487, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5116809196630896, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:35,570 [classy] Got parameters {'Omega_m': 0.30106300269950487, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:35,570 [classy] Computing new state
2023-07-02 10:34:35,570 [classy] Setting parameters: {'Omega_m': 0.30106300269950487, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:35,616 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.6570763618066}
2023-07-02 10:34:35,616 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:35,618 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00843375
2023-07-02 10:34:35,618 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5116809196630896, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:35,618 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:35,638 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.22365
2023-07-02 10:34:35,638 [model] Computed derived parameters: {}
2023-07-02 10:34:35,638 [mcmc] New sample, #734:
Omega_m:0.3078212, b1:0.4999326
2023-07-02 10:34:35,638 [model] Posterior to be computed for parameters {'Omega_m': 0.30106300269950487, 'b1': 0.5255361549856249}
2023-07-02 10:34:35,638 [prior] Evaluating prior at array([0.301063 , 0.52553615])
2023-07-02 10:34:35,638 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:35,638 [model] Got input parameters: {'Omega_m': 0.30106300269950487, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5255361549856249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:35,638 [classy] Got parameters {'Omega_m': 0.30106300269950487, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:35,638 [classy] Re-using computed results
2023-07-02 10:34:35,638 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.6570763618066}
2023-07-02 10:34:35,638 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:35,638 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5255361549856249, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:35,638 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:35,657 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.73562
2023-07-02 10:34:35,657 [model] Computed derived parameters: {}
2023-07-02 10:34:35,657 [mcmc] New sample, #735:
Omega_m:0.301063, b1:0.5116809
2023-07-02 10:34:35,657 [model] Posterior to be computed for parameters {'Omega_m': 0.3357509743678803, 'b1': 0.46523529058299495}
2023-07-02 10:34:35,657 [prior] Evaluating prior at array([0.33575097, 0.46523529])
2023-07-02 10:34:35,658 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:35,658 [model] Got input parameters: {'Omega_m': 0.3357509743678803, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46523529058299495, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:35,658 [classy] Got parameters {'Omega_m': 0.3357509743678803, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:35,658 [classy] Computing new state
2023-07-02 10:34:35,658 [classy] Setting parameters: {'Omega_m': 0.3357509743678803, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:35,704 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.54953384713232}
2023-07-02 10:34:35,705 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:35,706 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0315698
2023-07-02 10:34:35,707 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46523529058299495, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:35,707 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:35,727 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.731395
2023-07-02 10:34:35,727 [model] Computed derived parameters: {}
2023-07-02 10:34:35,727 [model] Posterior to be computed for parameters {'Omega_m': 0.30106300269950487, 'b1': 0.5737459942729837}
2023-07-02 10:34:35,727 [prior] Evaluating prior at array([0.301063 , 0.57374599])
2023-07-02 10:34:35,728 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:35,728 [model] Got input parameters: {'Omega_m': 0.30106300269950487, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5737459942729837, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:35,728 [classy] Got parameters {'Omega_m': 0.30106300269950487, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:35,728 [classy] Re-using computed results
2023-07-02 10:34:35,728 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.6570763618066}
2023-07-02 10:34:35,728 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:35,728 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5737459942729837, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:35,728 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:35,747 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.71096
2023-07-02 10:34:35,747 [model] Computed derived parameters: {}
2023-07-02 10:34:35,747 [model] Posterior to be computed for parameters {'Omega_m': 0.2737227705773714, 'b1': 0.5730638584124655}
2023-07-02 10:34:35,747 [prior] Evaluating prior at array([0.27372277, 0.57306386])
2023-07-02 10:34:35,747 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:35,747 [model] Got input parameters: {'Omega_m': 0.2737227705773714, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5730638584124655, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:35,748 [classy] Got parameters {'Omega_m': 0.2737227705773714, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:35,748 [classy] Computing new state
2023-07-02 10:34:35,748 [classy] Setting parameters: {'Omega_m': 0.2737227705773714, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:35,794 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.19888024071236}
2023-07-02 10:34:35,794 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:35,796 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.102045
2023-07-02 10:34:35,796 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5730638584124655, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:35,796 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:35,815 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.58485
2023-07-02 10:34:35,815 [model] Computed derived parameters: {}
2023-07-02 10:34:35,815 [model] Posterior to be computed for parameters {'Omega_m': 0.30106300269950487, 'b1': 0.5635160162531283}
2023-07-02 10:34:35,815 [prior] Evaluating prior at array([0.301063 , 0.56351602])
2023-07-02 10:34:35,816 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:35,816 [model] Got input parameters: {'Omega_m': 0.30106300269950487, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5635160162531283, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:35,816 [classy] Got parameters {'Omega_m': 0.30106300269950487, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:35,816 [classy] Re-using computed results
2023-07-02 10:34:35,816 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.6570763618066}
2023-07-02 10:34:35,816 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:35,816 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5635160162531283, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:35,816 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:35,836 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.22001
2023-07-02 10:34:35,836 [model] Computed derived parameters: {}
2023-07-02 10:34:35,836 [model] Posterior to be computed for parameters {'Omega_m': 0.27454084515778016, 'b1': 0.571641734201339}
2023-07-02 10:34:35,836 [prior] Evaluating prior at array([0.27454085, 0.57164173])
2023-07-02 10:34:35,836 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:35,836 [model] Got input parameters: {'Omega_m': 0.27454084515778016, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.571641734201339, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:35,836 [classy] Got parameters {'Omega_m': 0.27454084515778016, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:35,836 [classy] Computing new state
2023-07-02 10:34:35,836 [classy] Setting parameters: {'Omega_m': 0.27454084515778016, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:35,883 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.08857893330432}
2023-07-02 10:34:35,883 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:35,885 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0975775
2023-07-02 10:34:35,885 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.571641734201339, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:35,885 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:35,904 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.0976
2023-07-02 10:34:35,904 [model] Computed derived parameters: {}
2023-07-02 10:34:35,904 [model] Posterior to be computed for parameters {'Omega_m': 0.30106300269950487, 'b1': 0.5165518387326689}
2023-07-02 10:34:35,904 [prior] Evaluating prior at array([0.301063 , 0.51655184])
2023-07-02 10:34:35,905 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:35,905 [model] Got input parameters: {'Omega_m': 0.30106300269950487, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5165518387326689, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:35,905 [classy] Got parameters {'Omega_m': 0.30106300269950487, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:35,905 [classy] Re-using computed results
2023-07-02 10:34:35,905 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.6570763618066}
2023-07-02 10:34:35,905 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:35,905 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5165518387326689, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:35,905 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:35,925 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.5173
2023-07-02 10:34:35,925 [model] Computed derived parameters: {}
2023-07-02 10:34:35,925 [mcmc] New sample, #736:
Omega_m:0.301063, b1:0.5255362
2023-07-02 10:34:35,925 [model] Posterior to be computed for parameters {'Omega_m': 0.29877966224659547, 'b1': 0.5205211513333666}
2023-07-02 10:34:35,925 [prior] Evaluating prior at array([0.29877966, 0.52052115])
2023-07-02 10:34:35,926 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:35,926 [model] Got input parameters: {'Omega_m': 0.29877966224659547, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5205211513333666, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:35,926 [classy] Got parameters {'Omega_m': 0.29877966224659547, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:35,926 [classy] Computing new state
2023-07-02 10:34:35,926 [classy] Setting parameters: {'Omega_m': 0.29877966224659547, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:35,972 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.9419550418081}
2023-07-02 10:34:35,972 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:35,974 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0121236
2023-07-02 10:34:35,974 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5205211513333666, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:35,974 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:35,994 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.07787
2023-07-02 10:34:35,994 [model] Computed derived parameters: {}
2023-07-02 10:34:35,994 [mcmc] New sample, #737:
Omega_m:0.301063, b1:0.5165518
2023-07-02 10:34:35,994 [model] Posterior to be computed for parameters {'Omega_m': 0.29877966224659547, 'b1': 0.4666415873877423}
2023-07-02 10:34:35,994 [prior] Evaluating prior at array([0.29877966, 0.46664159])
2023-07-02 10:34:35,994 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:35,994 [model] Got input parameters: {'Omega_m': 0.29877966224659547, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4666415873877423, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:35,994 [classy] Got parameters {'Omega_m': 0.29877966224659547, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:35,994 [classy] Re-using computed results
2023-07-02 10:34:35,994 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.9419550418081}
2023-07-02 10:34:35,994 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:35,994 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4666415873877423, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:35,994 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:36,013 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.62356
2023-07-02 10:34:36,013 [model] Computed derived parameters: {}
2023-07-02 10:34:36,013 [model] Posterior to be computed for parameters {'Omega_m': 0.32892436169525674, 'b1': 0.4681182189483354}
2023-07-02 10:34:36,014 [prior] Evaluating prior at array([0.32892436, 0.46811822])
2023-07-02 10:34:36,014 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:36,014 [model] Got input parameters: {'Omega_m': 0.32892436169525674, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4681182189483354, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:36,014 [classy] Got parameters {'Omega_m': 0.32892436169525674, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:36,014 [classy] Computing new state
2023-07-02 10:34:36,014 [classy] Setting parameters: {'Omega_m': 0.32892436169525674, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:36,060 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.32685184225735}
2023-07-02 10:34:36,060 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:36,062 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0161225
2023-07-02 10:34:36,062 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4681182189483354, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:36,062 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:36,083 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.79419
2023-07-02 10:34:36,083 [model] Computed derived parameters: {}
2023-07-02 10:34:36,083 [mcmc] New sample, #738:
Omega_m:0.2987797, b1:0.5205212
2023-07-02 10:34:36,083 [model] Posterior to be computed for parameters {'Omega_m': 0.32892436169525674, 'b1': 0.50606052806406}
2023-07-02 10:34:36,083 [prior] Evaluating prior at array([0.32892436, 0.50606053])
2023-07-02 10:34:36,083 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:36,083 [model] Got input parameters: {'Omega_m': 0.32892436169525674, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.50606052806406, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:36,083 [classy] Got parameters {'Omega_m': 0.32892436169525674, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:36,083 [classy] Re-using computed results
2023-07-02 10:34:36,083 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.32685184225735}
2023-07-02 10:34:36,083 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:36,083 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.50606052806406, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:36,083 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:36,103 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.773872
2023-07-02 10:34:36,103 [model] Computed derived parameters: {}
2023-07-02 10:34:36,103 [model] Posterior to be computed for parameters {'Omega_m': 0.29716199835611096, 'b1': 0.523333265337659}
2023-07-02 10:34:36,103 [prior] Evaluating prior at array([0.297162 , 0.52333327])
2023-07-02 10:34:36,103 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:36,103 [model] Got input parameters: {'Omega_m': 0.29716199835611096, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.523333265337659, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:36,103 [classy] Got parameters {'Omega_m': 0.29716199835611096, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:36,103 [classy] Computing new state
2023-07-02 10:34:36,103 [classy] Setting parameters: {'Omega_m': 0.29716199835611096, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:36,153 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.14493797952687}
2023-07-02 10:34:36,153 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:36,155 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0151661
2023-07-02 10:34:36,155 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.523333265337659, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:36,155 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:36,174 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.723322
2023-07-02 10:34:36,174 [model] Computed derived parameters: {}
2023-07-02 10:34:36,175 [model] Posterior to be computed for parameters {'Omega_m': 0.32892436169525674, 'b1': 0.4676315279242922}
2023-07-02 10:34:36,175 [prior] Evaluating prior at array([0.32892436, 0.46763153])
2023-07-02 10:34:36,175 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:36,175 [model] Got input parameters: {'Omega_m': 0.32892436169525674, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4676315279242922, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:36,175 [classy] Got parameters {'Omega_m': 0.32892436169525674, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:36,175 [classy] Re-using computed results
2023-07-02 10:34:36,175 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.32685184225735}
2023-07-02 10:34:36,175 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:36,175 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4676315279242922, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:36,175 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:36,195 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.7752
2023-07-02 10:34:36,195 [model] Computed derived parameters: {}
2023-07-02 10:34:36,195 [mcmc] New sample, #739:
Omega_m:0.3289244, b1:0.4681182
2023-07-02 10:34:36,195 [model] Posterior to be computed for parameters {'Omega_m': 0.31640776265317944, 'b1': 0.4893901291141824}
2023-07-02 10:34:36,195 [prior] Evaluating prior at array([0.31640776, 0.48939013])
2023-07-02 10:34:36,195 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:36,195 [model] Got input parameters: {'Omega_m': 0.31640776265317944, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4893901291141824, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:36,195 [classy] Got parameters {'Omega_m': 0.31640776265317944, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:36,195 [classy] Computing new state
2023-07-02 10:34:36,195 [classy] Setting parameters: {'Omega_m': 0.31640776265317944, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:36,241 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.7906012332484}
2023-07-02 10:34:36,241 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:36,243 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00113737
2023-07-02 10:34:36,243 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4893901291141824, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:36,243 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:36,263 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.72948
2023-07-02 10:34:36,263 [model] Computed derived parameters: {}
2023-07-02 10:34:36,263 [mcmc] New sample, #740:
Omega_m:0.3289244, b1:0.4676315
2023-07-02 10:34:36,263 [model] Posterior to be computed for parameters {'Omega_m': 0.31640776265317944, 'b1': 0.4796693642285248}
2023-07-02 10:34:36,263 [prior] Evaluating prior at array([0.31640776, 0.47966936])
2023-07-02 10:34:36,263 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:36,263 [model] Got input parameters: {'Omega_m': 0.31640776265317944, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4796693642285248, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:36,263 [classy] Got parameters {'Omega_m': 0.31640776265317944, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:36,263 [classy] Re-using computed results
2023-07-02 10:34:36,263 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.7906012332484}
2023-07-02 10:34:36,263 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:36,263 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4796693642285248, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:36,263 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:36,283 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.04782
2023-07-02 10:34:36,283 [model] Computed derived parameters: {}
2023-07-02 10:34:36,283 [mcmc] New sample, #741:
Omega_m:0.3164078, b1:0.4893901
2023-07-02 10:34:36,283 [model] Posterior to be computed for parameters {'Omega_m': 0.31314704679190153, 'b1': 0.4853377263595307}
2023-07-02 10:34:36,284 [prior] Evaluating prior at array([0.31314705, 0.48533773])
2023-07-02 10:34:36,284 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:36,284 [model] Got input parameters: {'Omega_m': 0.31314704679190153, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4853377263595307, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:36,284 [classy] Got parameters {'Omega_m': 0.31314704679190153, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:36,284 [classy] Computing new state
2023-07-02 10:34:36,284 [classy] Setting parameters: {'Omega_m': 0.31314704679190153, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:36,330 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.18041492383904}
2023-07-02 10:34:36,330 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:36,332 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000229295
2023-07-02 10:34:36,332 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4853377263595307, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:36,332 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:36,351 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.01101
2023-07-02 10:34:36,351 [model] Computed derived parameters: {}
2023-07-02 10:34:36,351 [mcmc] New sample, #742:
Omega_m:0.3164078, b1:0.4796694
2023-07-02 10:34:36,352 [model] Posterior to be computed for parameters {'Omega_m': 0.31314704679190153, 'b1': 0.49013806891124495}
2023-07-02 10:34:36,352 [prior] Evaluating prior at array([0.31314705, 0.49013807])
2023-07-02 10:34:36,352 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:36,352 [model] Got input parameters: {'Omega_m': 0.31314704679190153, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49013806891124495, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:36,352 [classy] Got parameters {'Omega_m': 0.31314704679190153, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:36,352 [classy] Re-using computed results
2023-07-02 10:34:36,352 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.18041492383904}
2023-07-02 10:34:36,352 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:36,352 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49013806891124495, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:36,352 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:36,371 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.41384
2023-07-02 10:34:36,371 [model] Computed derived parameters: {}
2023-07-02 10:34:36,371 [mcmc] New sample, #743:
Omega_m:0.313147, b1:0.4853377
2023-07-02 10:34:36,371 [model] Posterior to be computed for parameters {'Omega_m': 0.2930719948366561, 'b1': 0.5250361309081256}
2023-07-02 10:34:36,371 [prior] Evaluating prior at array([0.29307199, 0.52503613])
2023-07-02 10:34:36,372 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:36,372 [model] Got input parameters: {'Omega_m': 0.2930719948366561, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5250361309081256, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:36,372 [classy] Got parameters {'Omega_m': 0.2930719948366561, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:36,372 [classy] Computing new state
2023-07-02 10:34:36,372 [classy] Setting parameters: {'Omega_m': 0.2930719948366561, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:36,418 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.66247729967716}
2023-07-02 10:34:36,418 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:36,420 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0244759
2023-07-02 10:34:36,420 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5250361309081256, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:36,420 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:36,439 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.685077
2023-07-02 10:34:36,440 [model] Computed derived parameters: {}
2023-07-02 10:34:36,440 [model] Posterior to be computed for parameters {'Omega_m': 0.31314704679190153, 'b1': 0.4696568252575498}
2023-07-02 10:34:36,440 [prior] Evaluating prior at array([0.31314705, 0.46965683])
2023-07-02 10:34:36,440 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:36,440 [model] Got input parameters: {'Omega_m': 0.31314704679190153, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4696568252575498, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:36,440 [classy] Got parameters {'Omega_m': 0.31314704679190153, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:36,440 [classy] Re-using computed results
2023-07-02 10:34:36,440 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.18041492383904}
2023-07-02 10:34:36,440 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:36,440 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4696568252575498, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:36,440 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:36,459 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.112946
2023-07-02 10:34:36,459 [model] Computed derived parameters: {}
2023-07-02 10:34:36,460 [model] Posterior to be computed for parameters {'Omega_m': 0.35917293420651714, 'b1': 0.41012760238605056}
2023-07-02 10:34:36,460 [prior] Evaluating prior at array([0.35917293, 0.4101276 ])
2023-07-02 10:34:36,460 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:36,460 [model] Got input parameters: {'Omega_m': 0.35917293420651714, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.41012760238605056, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:36,460 [classy] Got parameters {'Omega_m': 0.35917293420651714, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:36,460 [classy] Computing new state
2023-07-02 10:34:36,460 [classy] Setting parameters: {'Omega_m': 0.35917293420651714, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:36,507 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.9876552379094}
2023-07-02 10:34:36,507 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:36,509 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.1198
2023-07-02 10:34:36,509 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.41012760238605056, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:36,509 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:36,528 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.40195
2023-07-02 10:34:36,528 [model] Computed derived parameters: {}
2023-07-02 10:34:36,528 [model] Posterior to be computed for parameters {'Omega_m': 0.31314704679190153, 'b1': 0.44739147781832467}
2023-07-02 10:34:36,528 [prior] Evaluating prior at array([0.31314705, 0.44739148])
2023-07-02 10:34:36,528 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:36,528 [model] Got input parameters: {'Omega_m': 0.31314704679190153, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44739147781832467, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:36,528 [classy] Got parameters {'Omega_m': 0.31314704679190153, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:36,528 [classy] Re-using computed results
2023-07-02 10:34:36,528 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.18041492383904}
2023-07-02 10:34:36,528 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:36,528 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44739147781832467, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:36,528 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:36,548 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.16119
2023-07-02 10:34:36,548 [model] Computed derived parameters: {}
2023-07-02 10:34:36,548 [model] Posterior to be computed for parameters {'Omega_m': 0.3367056026860735, 'b1': 0.4491843545206343}
2023-07-02 10:34:36,548 [prior] Evaluating prior at array([0.3367056 , 0.44918435])
2023-07-02 10:34:36,549 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:36,549 [model] Got input parameters: {'Omega_m': 0.3367056026860735, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4491843545206343, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:36,549 [classy] Got parameters {'Omega_m': 0.3367056026860735, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:36,549 [classy] Computing new state
2023-07-02 10:34:36,549 [classy] Setting parameters: {'Omega_m': 0.3367056026860735, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:36,595 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.44197327068946}
2023-07-02 10:34:36,595 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:36,597 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0341195
2023-07-02 10:34:36,597 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4491843545206343, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:36,597 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:36,616 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.170146
2023-07-02 10:34:36,616 [model] Computed derived parameters: {}
2023-07-02 10:34:36,616 [model] Posterior to be computed for parameters {'Omega_m': 0.31314704679190153, 'b1': 0.5590726744269169}
2023-07-02 10:34:36,617 [prior] Evaluating prior at array([0.31314705, 0.55907267])
2023-07-02 10:34:36,617 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:36,617 [model] Got input parameters: {'Omega_m': 0.31314704679190153, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5590726744269169, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:36,617 [classy] Got parameters {'Omega_m': 0.31314704679190153, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:36,617 [classy] Re-using computed results
2023-07-02 10:34:36,617 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.18041492383904}
2023-07-02 10:34:36,617 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:36,617 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5590726744269169, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:36,617 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:36,636 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.81153
2023-07-02 10:34:36,636 [model] Computed derived parameters: {}
2023-07-02 10:34:36,637 [model] Posterior to be computed for parameters {'Omega_m': 0.3344704274065653, 'b1': 0.4530699377635604}
2023-07-02 10:34:36,637 [prior] Evaluating prior at array([0.33447043, 0.45306994])
2023-07-02 10:34:36,637 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:36,637 [model] Got input parameters: {'Omega_m': 0.3344704274065653, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4530699377635604, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:36,637 [classy] Got parameters {'Omega_m': 0.3344704274065653, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:36,637 [classy] Computing new state
2023-07-02 10:34:36,637 [classy] Setting parameters: {'Omega_m': 0.3344704274065653, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:36,684 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.69425198804524}
2023-07-02 10:34:36,684 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:36,686 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0282977
2023-07-02 10:34:36,686 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4530699377635604, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:36,686 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:36,706 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.610885
2023-07-02 10:34:36,706 [model] Computed derived parameters: {}
2023-07-02 10:34:36,706 [model] Posterior to be computed for parameters {'Omega_m': 0.31314704679190153, 'b1': 0.42426879996283895}
2023-07-02 10:34:36,706 [prior] Evaluating prior at array([0.31314705, 0.4242688 ])
2023-07-02 10:34:36,706 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:36,706 [model] Got input parameters: {'Omega_m': 0.31314704679190153, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42426879996283895, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:36,706 [classy] Got parameters {'Omega_m': 0.31314704679190153, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:36,706 [classy] Re-using computed results
2023-07-02 10:34:36,706 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.18041492383904}
2023-07-02 10:34:36,706 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:36,706 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42426879996283895, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:36,706 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:36,725 [fs_likelihood.fslikelihood] Computed log-likelihood = -12.7669
2023-07-02 10:34:36,726 [model] Computed derived parameters: {}
2023-07-02 10:34:36,726 [model] Posterior to be computed for parameters {'Omega_m': 0.3202630945552841, 'b1': 0.4777676762182187}
2023-07-02 10:34:36,726 [prior] Evaluating prior at array([0.32026309, 0.47776768])
2023-07-02 10:34:36,726 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:36,726 [model] Got input parameters: {'Omega_m': 0.3202630945552841, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4777676762182187, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:36,726 [classy] Got parameters {'Omega_m': 0.3202630945552841, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:36,726 [classy] Computing new state
2023-07-02 10:34:36,726 [classy] Setting parameters: {'Omega_m': 0.3202630945552841, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:36,772 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.33431730301433}
2023-07-02 10:34:36,772 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:36,774 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00384223
2023-07-02 10:34:36,774 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4777676762182187, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:36,774 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:36,794 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.33133
2023-07-02 10:34:36,794 [model] Computed derived parameters: {}
2023-07-02 10:34:36,794 [mcmc] New sample, #744:
Omega_m:0.313147, b1:0.4901381
2023-07-02 10:34:36,794 [model] Posterior to be computed for parameters {'Omega_m': 0.3202630945552841, 'b1': 0.4660254405281234}
2023-07-02 10:34:36,794 [prior] Evaluating prior at array([0.32026309, 0.46602544])
2023-07-02 10:34:36,794 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:36,794 [model] Got input parameters: {'Omega_m': 0.3202630945552841, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4660254405281234, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:36,795 [classy] Got parameters {'Omega_m': 0.3202630945552841, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:36,795 [classy] Re-using computed results
2023-07-02 10:34:36,795 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.33431730301433}
2023-07-02 10:34:36,795 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:36,795 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4660254405281234, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:36,795 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:36,814 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.16391
2023-07-02 10:34:36,814 [model] Computed derived parameters: {}
2023-07-02 10:34:36,814 [model] Posterior to be computed for parameters {'Omega_m': 0.26844027490734024, 'b1': 0.567855411829511}
2023-07-02 10:34:36,814 [prior] Evaluating prior at array([0.26844027, 0.56785541])
2023-07-02 10:34:36,814 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:36,814 [model] Got input parameters: {'Omega_m': 0.26844027490734024, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.567855411829511, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:36,814 [classy] Got parameters {'Omega_m': 0.26844027490734024, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:36,814 [classy] Computing new state
2023-07-02 10:34:36,815 [classy] Setting parameters: {'Omega_m': 0.26844027490734024, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:36,862 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.91798514000342}
2023-07-02 10:34:36,862 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:36,864 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.13359
2023-07-02 10:34:36,864 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.567855411829511, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:36,864 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:36,883 [fs_likelihood.fslikelihood] Computed log-likelihood = -12.7132
2023-07-02 10:34:36,883 [model] Computed derived parameters: {}
2023-07-02 10:34:36,884 [model] Posterior to be computed for parameters {'Omega_m': 0.3202630945552841, 'b1': 0.510739127035056}
2023-07-02 10:34:36,884 [prior] Evaluating prior at array([0.32026309, 0.51073913])
2023-07-02 10:34:36,884 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:36,884 [model] Got input parameters: {'Omega_m': 0.3202630945552841, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.510739127035056, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:36,884 [classy] Got parameters {'Omega_m': 0.3202630945552841, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:36,884 [classy] Re-using computed results
2023-07-02 10:34:36,884 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.33431730301433}
2023-07-02 10:34:36,884 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:36,884 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.510739127035056, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:36,884 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:36,905 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.68584
2023-07-02 10:34:36,905 [model] Computed derived parameters: {}
2023-07-02 10:34:36,906 [mcmc] New sample, #745:
Omega_m:0.3202631, b1:0.4777677
2023-07-02 10:34:36,906 [model] Posterior to be computed for parameters {'Omega_m': 0.34028475515776324, 'b1': 0.475933879479856}
2023-07-02 10:34:36,906 [prior] Evaluating prior at array([0.34028476, 0.47593388])
2023-07-02 10:34:36,906 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:36,906 [model] Got input parameters: {'Omega_m': 0.34028475515776324, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.475933879479856, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:36,906 [classy] Got parameters {'Omega_m': 0.34028475515776324, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:36,906 [classy] Computing new state
2023-07-02 10:34:36,906 [classy] Setting parameters: {'Omega_m': 0.34028475515776324, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:36,953 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.04114786871142}
2023-07-02 10:34:36,953 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:36,955 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0445068
2023-07-02 10:34:36,955 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.475933879479856, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:36,955 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:36,974 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.5413
2023-07-02 10:34:36,974 [model] Computed derived parameters: {}
2023-07-02 10:34:36,974 [model] Posterior to be computed for parameters {'Omega_m': 0.3202630945552841, 'b1': 0.6710385676331297}
2023-07-02 10:34:36,974 [prior] Evaluating prior at array([0.32026309, 0.67103857])
2023-07-02 10:34:36,974 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:36,974 [model] Got input parameters: {'Omega_m': 0.3202630945552841, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6710385676331297, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:36,974 [classy] Got parameters {'Omega_m': 0.3202630945552841, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:36,974 [classy] Re-using computed results
2023-07-02 10:34:36,975 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.33431730301433}
2023-07-02 10:34:36,975 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:36,975 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6710385676331297, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:36,975 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:36,995 [fs_likelihood.fslikelihood] Computed log-likelihood = -102.22
2023-07-02 10:34:36,995 [model] Computed derived parameters: {}
2023-07-02 10:34:36,995 [model] Posterior to be computed for parameters {'Omega_m': 0.27752718083777406, 'b1': 0.5850303702025397}
2023-07-02 10:34:36,995 [prior] Evaluating prior at array([0.27752718, 0.58503037])
2023-07-02 10:34:36,995 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:36,995 [model] Got input parameters: {'Omega_m': 0.27752718083777406, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5850303702025397, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:36,995 [classy] Got parameters {'Omega_m': 0.27752718083777406, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:36,995 [classy] Computing new state
2023-07-02 10:34:36,995 [classy] Setting parameters: {'Omega_m': 0.27752718083777406, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:37,045 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.68829370852148}
2023-07-02 10:34:37,045 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:37,047 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0821957
2023-07-02 10:34:37,047 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5850303702025397, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:37,047 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:37,067 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.15351
2023-07-02 10:34:37,067 [model] Computed derived parameters: {}
2023-07-02 10:34:37,067 [model] Posterior to be computed for parameters {'Omega_m': 0.3202630945552841, 'b1': 0.48769735467306813}
2023-07-02 10:34:37,067 [prior] Evaluating prior at array([0.32026309, 0.48769735])
2023-07-02 10:34:37,067 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:37,067 [model] Got input parameters: {'Omega_m': 0.3202630945552841, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48769735467306813, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:37,067 [classy] Got parameters {'Omega_m': 0.3202630945552841, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:37,067 [classy] Re-using computed results
2023-07-02 10:34:37,067 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.33431730301433}
2023-07-02 10:34:37,067 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:37,067 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48769735467306813, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:37,067 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:37,088 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.75927
2023-07-02 10:34:37,088 [model] Computed derived parameters: {}
2023-07-02 10:34:37,088 [mcmc] New sample, #746:
Omega_m:0.3202631, b1:0.5107391
2023-07-02 10:34:37,088 [model] Posterior to be computed for parameters {'Omega_m': 0.3862205947016154, 'b1': 0.3730381779796551}
2023-07-02 10:34:37,088 [prior] Evaluating prior at array([0.38622059, 0.37303818])
2023-07-02 10:34:37,089 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:37,089 [model] Got input parameters: {'Omega_m': 0.3862205947016154, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.3730381779796551, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:37,089 [classy] Got parameters {'Omega_m': 0.3862205947016154, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:37,089 [classy] Computing new state
2023-07-02 10:34:37,089 [classy] Setting parameters: {'Omega_m': 0.3862205947016154, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:37,139 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 139.21486279800766}
2023-07-02 10:34:37,139 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:37,141 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.281035
2023-07-02 10:34:37,141 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.3730381779796551, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:37,141 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:37,161 [fs_likelihood.fslikelihood] Computed log-likelihood = -18.0128
2023-07-02 10:34:37,161 [model] Computed derived parameters: {}
2023-07-02 10:34:37,161 [model] Posterior to be computed for parameters {'Omega_m': 0.3202630945552841, 'b1': 0.45872511504971347}
2023-07-02 10:34:37,161 [prior] Evaluating prior at array([0.32026309, 0.45872512])
2023-07-02 10:34:37,161 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:37,161 [model] Got input parameters: {'Omega_m': 0.3202630945552841, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45872511504971347, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:37,161 [classy] Got parameters {'Omega_m': 0.3202630945552841, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:37,161 [classy] Re-using computed results
2023-07-02 10:34:37,161 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.33431730301433}
2023-07-02 10:34:37,161 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:37,161 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45872511504971347, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:37,161 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:37,181 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.0874987
2023-07-02 10:34:37,181 [model] Computed derived parameters: {}
2023-07-02 10:34:37,181 [model] Posterior to be computed for parameters {'Omega_m': 0.3410817647151713, 'b1': 0.4515066019142681}
2023-07-02 10:34:37,181 [prior] Evaluating prior at array([0.34108176, 0.4515066 ])
2023-07-02 10:34:37,181 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:37,181 [model] Got input parameters: {'Omega_m': 0.3410817647151713, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4515066019142681, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:37,181 [classy] Got parameters {'Omega_m': 0.3410817647151713, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:37,181 [classy] Computing new state
2023-07-02 10:34:37,181 [classy] Setting parameters: {'Omega_m': 0.3410817647151713, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:37,228 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.95240939339246}
2023-07-02 10:34:37,228 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:37,230 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0469957
2023-07-02 10:34:37,230 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4515066019142681, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:37,230 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:37,250 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.457608
2023-07-02 10:34:37,250 [model] Computed derived parameters: {}
2023-07-02 10:34:37,250 [model] Posterior to be computed for parameters {'Omega_m': 0.3202630945552841, 'b1': 0.4958450496577228}
2023-07-02 10:34:37,250 [prior] Evaluating prior at array([0.32026309, 0.49584505])
2023-07-02 10:34:37,250 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:37,250 [model] Got input parameters: {'Omega_m': 0.3202630945552841, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4958450496577228, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:37,250 [classy] Got parameters {'Omega_m': 0.3202630945552841, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:37,251 [classy] Re-using computed results
2023-07-02 10:34:37,251 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.33431730301433}
2023-07-02 10:34:37,251 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:37,251 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4958450496577228, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:37,251 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:37,270 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.71578
2023-07-02 10:34:37,270 [model] Computed derived parameters: {}
2023-07-02 10:34:37,270 [mcmc] New sample, #747:
Omega_m:0.3202631, b1:0.4876974
2023-07-02 10:34:37,270 [model] Posterior to be computed for parameters {'Omega_m': 0.3246187336868214, 'b1': 0.4882732951841952}
2023-07-02 10:34:37,270 [prior] Evaluating prior at array([0.32461873, 0.4882733 ])
2023-07-02 10:34:37,270 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:37,270 [model] Got input parameters: {'Omega_m': 0.3246187336868214, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4882732951841952, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:37,271 [classy] Got parameters {'Omega_m': 0.3246187336868214, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:37,271 [classy] Computing new state
2023-07-02 10:34:37,271 [classy] Setting parameters: {'Omega_m': 0.3246187336868214, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:37,317 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.82467008377762}
2023-07-02 10:34:37,317 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:37,319 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00896599
2023-07-02 10:34:37,319 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4882732951841952, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:37,319 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:37,338 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.36756
2023-07-02 10:34:37,338 [model] Computed derived parameters: {}
2023-07-02 10:34:37,339 [model] Posterior to be computed for parameters {'Omega_m': 0.3202630945552841, 'b1': 0.49398858438585264}
2023-07-02 10:34:37,339 [prior] Evaluating prior at array([0.32026309, 0.49398858])
2023-07-02 10:34:37,339 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:37,339 [model] Got input parameters: {'Omega_m': 0.3202630945552841, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49398858438585264, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:37,339 [classy] Got parameters {'Omega_m': 0.3202630945552841, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:37,339 [classy] Re-using computed results
2023-07-02 10:34:37,339 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.33431730301433}
2023-07-02 10:34:37,339 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:37,339 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49398858438585264, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:37,339 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:37,358 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.75749
2023-07-02 10:34:37,359 [model] Computed derived parameters: {}
2023-07-02 10:34:37,359 [mcmc] New sample, #748:
Omega_m:0.3202631, b1:0.495845
2023-07-02 10:34:37,359 [model] Posterior to be computed for parameters {'Omega_m': 0.3255076416606446, 'b1': 0.48487157037082246}
2023-07-02 10:34:37,359 [prior] Evaluating prior at array([0.32550764, 0.48487157])
2023-07-02 10:34:37,359 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:37,359 [model] Got input parameters: {'Omega_m': 0.3255076416606446, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48487157037082246, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:37,359 [classy] Got parameters {'Omega_m': 0.3255076416606446, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:37,359 [classy] Computing new state
2023-07-02 10:34:37,359 [classy] Setting parameters: {'Omega_m': 0.3255076416606446, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:37,405 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.7214113530546}
2023-07-02 10:34:37,405 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:37,407 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0102753
2023-07-02 10:34:37,407 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48487157037082246, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:37,407 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:37,427 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.31882
2023-07-02 10:34:37,427 [model] Computed derived parameters: {}
2023-07-02 10:34:37,427 [mcmc] New sample, #749:
Omega_m:0.3202631, b1:0.4939886
2023-07-02 10:34:37,427 [model] Posterior to be computed for parameters {'Omega_m': 0.3255076416606446, 'b1': 0.4844878589886201}
2023-07-02 10:34:37,427 [prior] Evaluating prior at array([0.32550764, 0.48448786])
2023-07-02 10:34:37,427 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:37,427 [model] Got input parameters: {'Omega_m': 0.3255076416606446, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4844878589886201, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:37,427 [classy] Got parameters {'Omega_m': 0.3255076416606446, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:37,427 [classy] Re-using computed results
2023-07-02 10:34:37,427 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.7214113530546}
2023-07-02 10:34:37,427 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:37,427 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4844878589886201, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:37,427 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:37,447 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.32595
2023-07-02 10:34:37,447 [model] Computed derived parameters: {}
2023-07-02 10:34:37,447 [mcmc] New sample, #750:
Omega_m:0.3255076, b1:0.4848716
2023-07-02 10:34:37,447 [model] Posterior to be computed for parameters {'Omega_m': 0.35069412778565917, 'b1': 0.44070418379645365}
2023-07-02 10:34:37,447 [prior] Evaluating prior at array([0.35069413, 0.44070418])
2023-07-02 10:34:37,447 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:37,447 [model] Got input parameters: {'Omega_m': 0.35069412778565917, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44070418379645365, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:37,447 [classy] Got parameters {'Omega_m': 0.35069412778565917, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:37,447 [classy] Computing new state
2023-07-02 10:34:37,447 [classy] Setting parameters: {'Omega_m': 0.35069412778565917, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:37,494 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.89690641318637}
2023-07-02 10:34:37,494 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:37,496 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0818818
2023-07-02 10:34:37,496 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44070418379645365, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:37,496 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:37,515 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.23403
2023-07-02 10:34:37,515 [model] Computed derived parameters: {}
2023-07-02 10:34:37,515 [model] Posterior to be computed for parameters {'Omega_m': 0.3255076416606446, 'b1': 0.3811148769491803}
2023-07-02 10:34:37,515 [prior] Evaluating prior at array([0.32550764, 0.38111488])
2023-07-02 10:34:37,515 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:37,515 [model] Got input parameters: {'Omega_m': 0.3255076416606446, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.3811148769491803, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:37,515 [classy] Got parameters {'Omega_m': 0.3255076416606446, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:37,515 [classy] Re-using computed results
2023-07-02 10:34:37,515 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.7214113530546}
2023-07-02 10:34:37,515 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:37,515 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.3811148769491803, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:37,515 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:37,534 [fs_likelihood.fslikelihood] Computed log-likelihood = -22.2976
2023-07-02 10:34:37,534 [model] Computed derived parameters: {}
2023-07-02 10:34:37,535 [model] Posterior to be computed for parameters {'Omega_m': 0.33485819003418127, 'b1': 0.46823305588415043}
2023-07-02 10:34:37,535 [prior] Evaluating prior at array([0.33485819, 0.46823306])
2023-07-02 10:34:37,535 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:37,535 [model] Got input parameters: {'Omega_m': 0.33485819003418127, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46823305588415043, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:37,535 [classy] Got parameters {'Omega_m': 0.33485819003418127, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:37,535 [classy] Computing new state
2023-07-02 10:34:37,535 [classy] Setting parameters: {'Omega_m': 0.33485819003418127, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:37,581 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.65037772027145}
2023-07-02 10:34:37,581 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:37,583 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0292705
2023-07-02 10:34:37,583 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46823305588415043, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:37,583 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:37,603 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.88467
2023-07-02 10:34:37,603 [model] Computed derived parameters: {}
2023-07-02 10:34:37,603 [model] Posterior to be computed for parameters {'Omega_m': 0.3255076416606446, 'b1': 0.5074830659032157}
2023-07-02 10:34:37,603 [prior] Evaluating prior at array([0.32550764, 0.50748307])
2023-07-02 10:34:37,603 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:37,603 [model] Got input parameters: {'Omega_m': 0.3255076416606446, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5074830659032157, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:37,603 [classy] Got parameters {'Omega_m': 0.3255076416606446, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:37,603 [classy] Re-using computed results
2023-07-02 10:34:37,603 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.7214113530546}
2023-07-02 10:34:37,603 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:37,603 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5074830659032157, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:37,603 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:37,622 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.436058
2023-07-02 10:34:37,622 [model] Computed derived parameters: {}
2023-07-02 10:34:37,623 [model] Posterior to be computed for parameters {'Omega_m': 0.33635685341375754, 'b1': 0.46562780994757685}
2023-07-02 10:34:37,623 [prior] Evaluating prior at array([0.33635685, 0.46562781])
2023-07-02 10:34:37,623 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:37,623 [model] Got input parameters: {'Omega_m': 0.33635685341375754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46562780994757685, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:37,623 [classy] Got parameters {'Omega_m': 0.33635685341375754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:37,623 [classy] Computing new state
2023-07-02 10:34:37,623 [classy] Setting parameters: {'Omega_m': 0.33635685341375754, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:37,669 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.48123788784355}
2023-07-02 10:34:37,669 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:37,671 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.033177
2023-07-02 10:34:37,671 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46562780994757685, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:37,671 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:37,690 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.580561
2023-07-02 10:34:37,690 [model] Computed derived parameters: {}
2023-07-02 10:34:37,691 [mcmc] New sample, #751:
Omega_m:0.3255076, b1:0.4844879
2023-07-02 10:34:37,691 [model] Posterior to be computed for parameters {'Omega_m': 0.33635685341375754, 'b1': 0.4628278680361772}
2023-07-02 10:34:37,691 [prior] Evaluating prior at array([0.33635685, 0.46282787])
2023-07-02 10:34:37,691 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:37,691 [model] Got input parameters: {'Omega_m': 0.33635685341375754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4628278680361772, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:37,691 [classy] Got parameters {'Omega_m': 0.33635685341375754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:37,691 [classy] Re-using computed results
2023-07-02 10:34:37,691 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.48123788784355}
2023-07-02 10:34:37,691 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:37,691 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4628278680361772, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:37,691 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:37,711 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.620249
2023-07-02 10:34:37,711 [model] Computed derived parameters: {}
2023-07-02 10:34:37,711 [mcmc] New sample, #752:
Omega_m:0.3363569, b1:0.4656278
2023-07-02 10:34:37,711 [model] Posterior to be computed for parameters {'Omega_m': 0.3811396943962407, 'b1': 0.38497828814531226}
2023-07-02 10:34:37,712 [prior] Evaluating prior at array([0.38113969, 0.38497829])
2023-07-02 10:34:37,712 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:37,712 [model] Got input parameters: {'Omega_m': 0.3811396943962407, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.38497828814531226, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:37,712 [classy] Got parameters {'Omega_m': 0.3811396943962407, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:37,712 [classy] Computing new state
2023-07-02 10:34:37,712 [classy] Setting parameters: {'Omega_m': 0.3811396943962407, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:37,758 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 139.7215758872967}
2023-07-02 10:34:37,758 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:37,760 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.246389
2023-07-02 10:34:37,760 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.38497828814531226, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:37,760 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:37,779 [fs_likelihood.fslikelihood] Computed log-likelihood = -15.5541
2023-07-02 10:34:37,779 [model] Computed derived parameters: {}
2023-07-02 10:34:37,779 [model] Posterior to be computed for parameters {'Omega_m': 0.33635685341375754, 'b1': 0.49827872943770196}
2023-07-02 10:34:37,779 [prior] Evaluating prior at array([0.33635685, 0.49827873])
2023-07-02 10:34:37,779 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:37,779 [model] Got input parameters: {'Omega_m': 0.33635685341375754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49827872943770196, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:37,779 [classy] Got parameters {'Omega_m': 0.33635685341375754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:37,779 [classy] Re-using computed results
2023-07-02 10:34:37,779 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.48123788784355}
2023-07-02 10:34:37,779 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:37,779 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49827872943770196, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:37,780 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:37,799 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.19835
2023-07-02 10:34:37,799 [model] Computed derived parameters: {}
2023-07-02 10:34:37,799 [model] Posterior to be computed for parameters {'Omega_m': 0.3713272153695658, 'b1': 0.4020361021016301}
2023-07-02 10:34:37,799 [prior] Evaluating prior at array([0.37132722, 0.4020361 ])
2023-07-02 10:34:37,799 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:37,799 [model] Got input parameters: {'Omega_m': 0.3713272153695658, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4020361021016301, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:37,799 [classy] Got parameters {'Omega_m': 0.3713272153695658, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:37,800 [classy] Computing new state
2023-07-02 10:34:37,800 [classy] Setting parameters: {'Omega_m': 0.3713272153695658, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:37,845 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.7183639463817}
2023-07-02 10:34:37,846 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:37,847 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.185025
2023-07-02 10:34:37,848 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4020361021016301, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:37,848 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:37,867 [fs_likelihood.fslikelihood] Computed log-likelihood = -11.0455
2023-07-02 10:34:37,867 [model] Computed derived parameters: {}
2023-07-02 10:34:37,867 [model] Posterior to be computed for parameters {'Omega_m': 0.33635685341375754, 'b1': 0.48699445666645913}
2023-07-02 10:34:37,867 [prior] Evaluating prior at array([0.33635685, 0.48699446])
2023-07-02 10:34:37,867 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:37,867 [model] Got input parameters: {'Omega_m': 0.33635685341375754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48699445666645913, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:37,868 [classy] Got parameters {'Omega_m': 0.33635685341375754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:37,868 [classy] Re-using computed results
2023-07-02 10:34:37,868 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.48123788784355}
2023-07-02 10:34:37,868 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:37,868 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48699445666645913, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:37,868 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:37,887 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.18496
2023-07-02 10:34:37,887 [model] Computed derived parameters: {}
2023-07-02 10:34:37,887 [model] Posterior to be computed for parameters {'Omega_m': 0.3503070525538146, 'b1': 0.43857712559506806}
2023-07-02 10:34:37,887 [prior] Evaluating prior at array([0.35030705, 0.43857713])
2023-07-02 10:34:37,887 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:37,887 [model] Got input parameters: {'Omega_m': 0.3503070525538146, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.43857712559506806, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:37,887 [classy] Got parameters {'Omega_m': 0.3503070525538146, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:37,887 [classy] Computing new state
2023-07-02 10:34:37,888 [classy] Setting parameters: {'Omega_m': 0.3503070525538146, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:37,935 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.93889326041227}
2023-07-02 10:34:37,935 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:37,937 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0803074
2023-07-02 10:34:37,937 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.43857712559506806, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:37,937 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:37,957 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.0575
2023-07-02 10:34:37,957 [model] Computed derived parameters: {}
2023-07-02 10:34:37,957 [model] Posterior to be computed for parameters {'Omega_m': 0.33635685341375754, 'b1': 0.4840158747602889}
2023-07-02 10:34:37,957 [prior] Evaluating prior at array([0.33635685, 0.48401587])
2023-07-02 10:34:37,958 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:37,958 [model] Got input parameters: {'Omega_m': 0.33635685341375754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4840158747602889, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:37,958 [classy] Got parameters {'Omega_m': 0.33635685341375754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:37,958 [classy] Re-using computed results
2023-07-02 10:34:37,958 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.48123788784355}
2023-07-02 10:34:37,958 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:37,958 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4840158747602889, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:37,958 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:37,977 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.780399
2023-07-02 10:34:37,977 [model] Computed derived parameters: {}
2023-07-02 10:34:37,977 [model] Posterior to be computed for parameters {'Omega_m': 0.35907154372119454, 'b1': 0.4233411124175072}
2023-07-02 10:34:37,977 [prior] Evaluating prior at array([0.35907154, 0.42334111])
2023-07-02 10:34:37,978 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:37,978 [model] Got input parameters: {'Omega_m': 0.35907154372119454, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4233411124175072, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:37,978 [classy] Got parameters {'Omega_m': 0.35907154372119454, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:37,978 [classy] Computing new state
2023-07-02 10:34:37,978 [classy] Setting parameters: {'Omega_m': 0.35907154372119454, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:38,024 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.99841206500398}
2023-07-02 10:34:38,025 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:38,026 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.119309
2023-07-02 10:34:38,027 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4233411124175072, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:38,027 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:38,046 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.07346
2023-07-02 10:34:38,046 [model] Computed derived parameters: {}
2023-07-02 10:34:38,046 [model] Posterior to be computed for parameters {'Omega_m': 0.33635685341375754, 'b1': 0.4729556847783608}
2023-07-02 10:34:38,046 [prior] Evaluating prior at array([0.33635685, 0.47295568])
2023-07-02 10:34:38,047 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:38,047 [model] Got input parameters: {'Omega_m': 0.33635685341375754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4729556847783608, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:38,047 [classy] Got parameters {'Omega_m': 0.33635685341375754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:38,047 [classy] Re-using computed results
2023-07-02 10:34:38,047 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.48123788784355}
2023-07-02 10:34:38,047 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:38,047 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4729556847783608, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:38,047 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:38,067 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.269415
2023-07-02 10:34:38,067 [model] Computed derived parameters: {}
2023-07-02 10:34:38,067 [mcmc] New sample, #753:
Omega_m:0.3363569, b1:0.4628279
2023-07-02 10:34:38,067 [model] Posterior to be computed for parameters {'Omega_m': 0.34532150705747455, 'b1': 0.4573717132231961}
2023-07-02 10:34:38,067 [prior] Evaluating prior at array([0.34532151, 0.45737171])
2023-07-02 10:34:38,067 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:38,067 [model] Got input parameters: {'Omega_m': 0.34532150705747455, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4573717132231961, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:38,067 [classy] Got parameters {'Omega_m': 0.34532150705747455, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:38,067 [classy] Computing new state
2023-07-02 10:34:38,067 [classy] Setting parameters: {'Omega_m': 0.34532150705747455, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:38,115 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.48352484527382}
2023-07-02 10:34:38,115 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:38,117 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0612887
2023-07-02 10:34:38,117 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4573717132231961, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:38,117 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:38,139 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.95946
2023-07-02 10:34:38,139 [model] Computed derived parameters: {}
2023-07-02 10:34:38,139 [model] Posterior to be computed for parameters {'Omega_m': 0.33635685341375754, 'b1': 0.49949218989880756}
2023-07-02 10:34:38,139 [prior] Evaluating prior at array([0.33635685, 0.49949219])
2023-07-02 10:34:38,139 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:38,139 [model] Got input parameters: {'Omega_m': 0.33635685341375754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49949218989880756, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:38,139 [classy] Got parameters {'Omega_m': 0.33635685341375754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:38,139 [classy] Re-using computed results
2023-07-02 10:34:38,139 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.48123788784355}
2023-07-02 10:34:38,139 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:38,139 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49949218989880756, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:38,139 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:38,159 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.46085
2023-07-02 10:34:38,160 [model] Computed derived parameters: {}
2023-07-02 10:34:38,160 [model] Posterior to be computed for parameters {'Omega_m': 0.3445862425760497, 'b1': 0.4586498820425881}
2023-07-02 10:34:38,160 [prior] Evaluating prior at array([0.34458624, 0.45864988])
2023-07-02 10:34:38,160 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:38,160 [model] Got input parameters: {'Omega_m': 0.3445862425760497, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4586498820425881, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:38,160 [classy] Got parameters {'Omega_m': 0.3445862425760497, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:38,160 [classy] Computing new state
2023-07-02 10:34:38,160 [classy] Setting parameters: {'Omega_m': 0.3445862425760497, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:38,207 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.56445448044835}
2023-07-02 10:34:38,207 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:38,208 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0586847
2023-07-02 10:34:38,208 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4586498820425881, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:38,208 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:38,228 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.75314
2023-07-02 10:34:38,228 [model] Computed derived parameters: {}
2023-07-02 10:34:38,228 [model] Posterior to be computed for parameters {'Omega_m': 0.33635685341375754, 'b1': 0.45542141185437185}
2023-07-02 10:34:38,228 [prior] Evaluating prior at array([0.33635685, 0.45542141])
2023-07-02 10:34:38,228 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:38,228 [model] Got input parameters: {'Omega_m': 0.33635685341375754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45542141185437185, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:38,228 [classy] Got parameters {'Omega_m': 0.33635685341375754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:38,228 [classy] Re-using computed results
2023-07-02 10:34:38,228 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.48123788784355}
2023-07-02 10:34:38,228 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:38,228 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45542141185437185, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:38,229 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:38,248 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.517815
2023-07-02 10:34:38,248 [model] Computed derived parameters: {}
2023-07-02 10:34:38,248 [mcmc] New sample, #754:
Omega_m:0.3363569, b1:0.4729557
2023-07-02 10:34:38,248 [model] Posterior to be computed for parameters {'Omega_m': 0.3755867455110882, 'b1': 0.3872249653597034}
2023-07-02 10:34:38,248 [prior] Evaluating prior at array([0.37558675, 0.38722497])
2023-07-02 10:34:38,248 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:38,248 [model] Got input parameters: {'Omega_m': 0.3755867455110882, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.3872249653597034, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:38,248 [classy] Got parameters {'Omega_m': 0.3755867455110882, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:38,248 [classy] Computing new state
2023-07-02 10:34:38,248 [classy] Setting parameters: {'Omega_m': 0.3755867455110882, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:38,296 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.28264618587073}
2023-07-02 10:34:38,296 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:38,298 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.210747
2023-07-02 10:34:38,298 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.3872249653597034, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:38,298 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:38,318 [fs_likelihood.fslikelihood] Computed log-likelihood = -12.9772
2023-07-02 10:34:38,318 [model] Computed derived parameters: {}
2023-07-02 10:34:38,319 [model] Posterior to be computed for parameters {'Omega_m': 0.33635685341375754, 'b1': 0.45654731895382333}
2023-07-02 10:34:38,319 [prior] Evaluating prior at array([0.33635685, 0.45654732])
2023-07-02 10:34:38,319 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:38,319 [model] Got input parameters: {'Omega_m': 0.33635685341375754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45654731895382333, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:38,319 [classy] Got parameters {'Omega_m': 0.33635685341375754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:38,319 [classy] Re-using computed results
2023-07-02 10:34:38,319 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.48123788784355}
2023-07-02 10:34:38,319 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:38,319 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45654731895382333, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:38,319 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:38,338 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.552611
2023-07-02 10:34:38,338 [model] Computed derived parameters: {}
2023-07-02 10:34:38,338 [mcmc] New sample, #755:
Omega_m:0.3363569, b1:0.4554214
2023-07-02 10:34:38,339 [model] Posterior to be computed for parameters {'Omega_m': 0.3265152158172258, 'b1': 0.47365582157490144}
2023-07-02 10:34:38,339 [prior] Evaluating prior at array([0.32651522, 0.47365582])
2023-07-02 10:34:38,339 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:38,339 [model] Got input parameters: {'Omega_m': 0.3265152158172258, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47365582157490144, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:38,339 [classy] Got parameters {'Omega_m': 0.3265152158172258, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:38,339 [classy] Computing new state
2023-07-02 10:34:38,339 [classy] Setting parameters: {'Omega_m': 0.3265152158172258, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:38,385 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.60467261049305}
2023-07-02 10:34:38,385 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:38,387 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0118658
2023-07-02 10:34:38,387 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47365582157490144, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:38,387 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:38,407 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.14824
2023-07-02 10:34:38,407 [model] Computed derived parameters: {}
2023-07-02 10:34:38,407 [mcmc] New sample, #756:
Omega_m:0.3363569, b1:0.4565473
2023-07-02 10:34:38,407 [model] Posterior to be computed for parameters {'Omega_m': 0.3265152158172258, 'b1': 0.4438026901837657}
2023-07-02 10:34:38,407 [prior] Evaluating prior at array([0.32651522, 0.44380269])
2023-07-02 10:34:38,407 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:38,407 [model] Got input parameters: {'Omega_m': 0.3265152158172258, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4438026901837657, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:38,408 [classy] Got parameters {'Omega_m': 0.3265152158172258, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:38,408 [classy] Re-using computed results
2023-07-02 10:34:38,408 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.60467261049305}
2023-07-02 10:34:38,408 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:38,408 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4438026901837657, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:38,408 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:38,428 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.10147
2023-07-02 10:34:38,428 [model] Computed derived parameters: {}
2023-07-02 10:34:38,428 [model] Posterior to be computed for parameters {'Omega_m': 0.31569369555732, 'b1': 0.49246773228739227}
2023-07-02 10:34:38,428 [prior] Evaluating prior at array([0.3156937 , 0.49246773])
2023-07-02 10:34:38,428 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:38,428 [model] Got input parameters: {'Omega_m': 0.31569369555732, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49246773228739227, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:38,428 [classy] Got parameters {'Omega_m': 0.31569369555732, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:38,428 [classy] Computing new state
2023-07-02 10:34:38,428 [classy] Setting parameters: {'Omega_m': 0.31569369555732, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:38,475 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.87565400572376}
2023-07-02 10:34:38,475 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:38,477 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000829195
2023-07-02 10:34:38,477 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49246773228739227, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:38,477 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:38,501 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.80784
2023-07-02 10:34:38,501 [model] Computed derived parameters: {}
2023-07-02 10:34:38,501 [mcmc] New sample, #757:
Omega_m:0.3265152, b1:0.4736558
2023-07-02 10:34:38,502 [model] Posterior to be computed for parameters {'Omega_m': 0.31569369555732, 'b1': 0.5113203711058749}
2023-07-02 10:34:38,502 [prior] Evaluating prior at array([0.3156937 , 0.51132037])
2023-07-02 10:34:38,502 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:38,502 [model] Got input parameters: {'Omega_m': 0.31569369555732, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5113203711058749, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:38,502 [classy] Got parameters {'Omega_m': 0.31569369555732, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:38,502 [classy] Re-using computed results
2023-07-02 10:34:38,502 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.87565400572376}
2023-07-02 10:34:38,502 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:38,502 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5113203711058749, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:38,502 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:38,524 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.51671
2023-07-02 10:34:38,524 [model] Computed derived parameters: {}
2023-07-02 10:34:38,524 [model] Posterior to be computed for parameters {'Omega_m': 0.31379880877790595, 'b1': 0.49576176492314755}
2023-07-02 10:34:38,524 [prior] Evaluating prior at array([0.31379881, 0.49576176])
2023-07-02 10:34:38,525 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:38,525 [model] Got input parameters: {'Omega_m': 0.31379880877790595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49576176492314755, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:38,525 [classy] Got parameters {'Omega_m': 0.31379880877790595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:38,525 [classy] Computing new state
2023-07-02 10:34:38,525 [classy] Setting parameters: {'Omega_m': 0.31379880877790595, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:38,585 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.10220557808188}
2023-07-02 10:34:38,585 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:38,587 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000308072
2023-07-02 10:34:38,587 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49576176492314755, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:38,587 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:38,608 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.79327
2023-07-02 10:34:38,608 [model] Computed derived parameters: {}
2023-07-02 10:34:38,608 [mcmc] New sample, #758:
Omega_m:0.3156937, b1:0.4924677
2023-07-02 10:34:38,608 [model] Posterior to be computed for parameters {'Omega_m': 0.31379880877790595, 'b1': 0.4593721149852985}
2023-07-02 10:34:38,608 [prior] Evaluating prior at array([0.31379881, 0.45937211])
2023-07-02 10:34:38,608 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:38,608 [model] Got input parameters: {'Omega_m': 0.31379880877790595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4593721149852985, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:38,608 [classy] Got parameters {'Omega_m': 0.31379880877790595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:38,608 [classy] Re-using computed results
2023-07-02 10:34:38,608 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.10220557808188}
2023-07-02 10:34:38,608 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:38,608 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4593721149852985, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:38,608 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:38,629 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.88607
2023-07-02 10:34:38,629 [model] Computed derived parameters: {}
2023-07-02 10:34:38,629 [model] Posterior to be computed for parameters {'Omega_m': 0.33139865813599606, 'b1': 0.4651665447760882}
2023-07-02 10:34:38,629 [prior] Evaluating prior at array([0.33139866, 0.46516654])
2023-07-02 10:34:38,629 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:38,629 [model] Got input parameters: {'Omega_m': 0.33139865813599606, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4651665447760882, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:38,629 [classy] Got parameters {'Omega_m': 0.33139865813599606, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:38,629 [classy] Computing new state
2023-07-02 10:34:38,629 [classy] Setting parameters: {'Omega_m': 0.33139865813599606, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:38,676 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.04344216152742}
2023-07-02 10:34:38,676 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:38,678 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0211496
2023-07-02 10:34:38,678 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4651665447760882, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:38,678 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:38,700 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.46687
2023-07-02 10:34:38,700 [model] Computed derived parameters: {}
2023-07-02 10:34:38,700 [mcmc] New sample, #759:
Omega_m:0.3137988, b1:0.4957618
2023-07-02 10:34:38,700 [model] Posterior to be computed for parameters {'Omega_m': 0.33139865813599606, 'b1': 0.411127302665654}
2023-07-02 10:34:38,700 [prior] Evaluating prior at array([0.33139866, 0.4111273 ])
2023-07-02 10:34:38,700 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:38,700 [model] Got input parameters: {'Omega_m': 0.33139865813599606, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.411127302665654, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:38,700 [classy] Got parameters {'Omega_m': 0.33139865813599606, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:38,700 [classy] Re-using computed results
2023-07-02 10:34:38,700 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.04344216152742}
2023-07-02 10:34:38,700 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:38,700 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.411127302665654, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:38,700 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:38,722 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.56461
2023-07-02 10:34:38,722 [model] Computed derived parameters: {}
2023-07-02 10:34:38,722 [model] Posterior to be computed for parameters {'Omega_m': 0.33346782254831997, 'b1': 0.461569551448051}
2023-07-02 10:34:38,722 [prior] Evaluating prior at array([0.33346782, 0.46156955])
2023-07-02 10:34:38,722 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:38,722 [model] Got input parameters: {'Omega_m': 0.33346782254831997, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.461569551448051, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:38,722 [classy] Got parameters {'Omega_m': 0.33346782254831997, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:38,722 [classy] Computing new state
2023-07-02 10:34:38,723 [classy] Setting parameters: {'Omega_m': 0.33346782254831997, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:38,769 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.80790504176113}
2023-07-02 10:34:38,769 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:38,771 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0258554
2023-07-02 10:34:38,771 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.461569551448051, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:38,771 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:38,791 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.11172
2023-07-02 10:34:38,791 [model] Computed derived parameters: {}
2023-07-02 10:34:38,791 [mcmc] New sample, #760:
Omega_m:0.3313987, b1:0.4651665
2023-07-02 10:34:38,791 [model] Posterior to be computed for parameters {'Omega_m': 0.33346782254831997, 'b1': 0.4969515998280746}
2023-07-02 10:34:38,791 [prior] Evaluating prior at array([0.33346782, 0.4969516 ])
2023-07-02 10:34:38,791 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:38,791 [model] Got input parameters: {'Omega_m': 0.33346782254831997, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4969515998280746, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:38,791 [classy] Got parameters {'Omega_m': 0.33346782254831997, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:38,791 [classy] Re-using computed results
2023-07-02 10:34:38,791 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.80790504176113}
2023-07-02 10:34:38,791 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:38,791 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4969515998280746, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:38,791 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:38,811 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.36627
2023-07-02 10:34:38,812 [model] Computed derived parameters: {}
2023-07-02 10:34:38,812 [model] Posterior to be computed for parameters {'Omega_m': 0.3315139141755904, 'b1': 0.46496618602113987}
2023-07-02 10:34:38,812 [prior] Evaluating prior at array([0.33151391, 0.46496619])
2023-07-02 10:34:38,812 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:38,812 [model] Got input parameters: {'Omega_m': 0.3315139141755904, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46496618602113987, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:38,812 [classy] Got parameters {'Omega_m': 0.3315139141755904, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:38,812 [classy] Computing new state
2023-07-02 10:34:38,812 [classy] Setting parameters: {'Omega_m': 0.3315139141755904, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:38,858 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.0302858588546}
2023-07-02 10:34:38,858 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:38,860 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0213999
2023-07-02 10:34:38,860 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46496618602113987, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:38,860 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:38,880 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.44811
2023-07-02 10:34:38,880 [model] Computed derived parameters: {}
2023-07-02 10:34:38,880 [mcmc] New sample, #761:
Omega_m:0.3334678, b1:0.4615696
2023-07-02 10:34:38,880 [model] Posterior to be computed for parameters {'Omega_m': 0.3315139141755904, 'b1': 0.5687986012798748}
2023-07-02 10:34:38,881 [prior] Evaluating prior at array([0.33151391, 0.5687986 ])
2023-07-02 10:34:38,881 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:38,881 [model] Got input parameters: {'Omega_m': 0.3315139141755904, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5687986012798748, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:38,881 [classy] Got parameters {'Omega_m': 0.3315139141755904, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:38,881 [classy] Re-using computed results
2023-07-02 10:34:38,881 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.0302858588546}
2023-07-02 10:34:38,881 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:38,881 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5687986012798748, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:38,881 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:38,900 [fs_likelihood.fslikelihood] Computed log-likelihood = -27.6885
2023-07-02 10:34:38,900 [model] Computed derived parameters: {}
2023-07-02 10:34:38,900 [model] Posterior to be computed for parameters {'Omega_m': 0.3003077317290742, 'b1': 0.5192143788593125}
2023-07-02 10:34:38,901 [prior] Evaluating prior at array([0.30030773, 0.51921438])
2023-07-02 10:34:38,901 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:38,901 [model] Got input parameters: {'Omega_m': 0.3003077317290742, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5192143788593125, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:38,901 [classy] Got parameters {'Omega_m': 0.3003077317290742, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:38,901 [classy] Computing new state
2023-07-02 10:34:38,901 [classy] Setting parameters: {'Omega_m': 0.3003077317290742, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:38,948 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.7510903153864}
2023-07-02 10:34:38,948 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:38,950 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00957637
2023-07-02 10:34:38,950 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5192143788593125, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:38,950 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:38,970 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.43984
2023-07-02 10:34:38,970 [model] Computed derived parameters: {}
2023-07-02 10:34:38,970 [mcmc] New sample, #762:
Omega_m:0.3315139, b1:0.4649662
2023-07-02 10:34:38,970 [model] Posterior to be computed for parameters {'Omega_m': 0.3003077317290742, 'b1': 0.4695065455964744}
2023-07-02 10:34:38,970 [prior] Evaluating prior at array([0.30030773, 0.46950655])
2023-07-02 10:34:38,970 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:38,970 [model] Got input parameters: {'Omega_m': 0.3003077317290742, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4695065455964744, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:38,970 [classy] Got parameters {'Omega_m': 0.3003077317290742, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:38,970 [classy] Re-using computed results
2023-07-02 10:34:38,971 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.7510903153864}
2023-07-02 10:34:38,971 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:38,971 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4695065455964744, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:38,971 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:38,990 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.69413
2023-07-02 10:34:38,990 [model] Computed derived parameters: {}
2023-07-02 10:34:38,990 [model] Posterior to be computed for parameters {'Omega_m': 0.2786128976831972, 'b1': 0.5569282370965375}
2023-07-02 10:34:38,990 [prior] Evaluating prior at array([0.2786129 , 0.55692824])
2023-07-02 10:34:38,990 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:38,990 [model] Got input parameters: {'Omega_m': 0.2786128976831972, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5569282370965375, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:38,990 [classy] Got parameters {'Omega_m': 0.2786128976831972, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:38,990 [classy] Computing new state
2023-07-02 10:34:38,990 [classy] Setting parameters: {'Omega_m': 0.2786128976831972, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:39,037 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.54367566879856}
2023-07-02 10:34:39,037 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:39,039 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0769594
2023-07-02 10:34:39,039 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5569282370965375, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:39,039 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:39,059 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.0662
2023-07-02 10:34:39,059 [model] Computed derived parameters: {}
2023-07-02 10:34:39,059 [model] Posterior to be computed for parameters {'Omega_m': 0.3003077317290742, 'b1': 0.5394917723483511}
2023-07-02 10:34:39,059 [prior] Evaluating prior at array([0.30030773, 0.53949177])
2023-07-02 10:34:39,059 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:39,059 [model] Got input parameters: {'Omega_m': 0.3003077317290742, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5394917723483511, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:39,059 [classy] Got parameters {'Omega_m': 0.3003077317290742, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:39,059 [classy] Re-using computed results
2023-07-02 10:34:39,059 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.7510903153864}
2023-07-02 10:34:39,060 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:39,060 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5394917723483511, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:39,060 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:39,080 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.18292
2023-07-02 10:34:39,080 [model] Computed derived parameters: {}
2023-07-02 10:34:39,080 [model] Posterior to be computed for parameters {'Omega_m': 0.3053295321117728, 'b1': 0.5104845832163388}
2023-07-02 10:34:39,080 [prior] Evaluating prior at array([0.30532953, 0.51048458])
2023-07-02 10:34:39,080 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:39,080 [model] Got input parameters: {'Omega_m': 0.3053295321117728, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5104845832163388, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:39,080 [classy] Got parameters {'Omega_m': 0.3053295321117728, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:39,080 [classy] Computing new state
2023-07-02 10:34:39,080 [classy] Setting parameters: {'Omega_m': 0.3053295321117728, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:39,130 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.12985431648022}
2023-07-02 10:34:39,130 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:39,133 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00339803
2023-07-02 10:34:39,133 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5104845832163388, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:39,133 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:39,153 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.21057
2023-07-02 10:34:39,153 [model] Computed derived parameters: {}
2023-07-02 10:34:39,153 [mcmc] New sample, #763:
Omega_m:0.3003077, b1:0.5192144
2023-07-02 10:34:39,153 [model] Posterior to be computed for parameters {'Omega_m': 0.3053295321117728, 'b1': 0.5236493443246252}
2023-07-02 10:34:39,153 [prior] Evaluating prior at array([0.30532953, 0.52364934])
2023-07-02 10:34:39,153 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:39,153 [model] Got input parameters: {'Omega_m': 0.3053295321117728, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5236493443246252, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:39,153 [classy] Got parameters {'Omega_m': 0.3053295321117728, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:39,153 [classy] Re-using computed results
2023-07-02 10:34:39,153 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.12985431648022}
2023-07-02 10:34:39,153 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:39,153 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5236493443246252, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:39,153 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:39,173 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.26823
2023-07-02 10:34:39,173 [model] Computed derived parameters: {}
2023-07-02 10:34:39,173 [mcmc] New sample, #764:
Omega_m:0.3053295, b1:0.5104846
2023-07-02 10:34:39,173 [model] Posterior to be computed for parameters {'Omega_m': 0.23460781564004618, 'b1': 0.6465905377749988}
2023-07-02 10:34:39,173 [prior] Evaluating prior at array([0.23460782, 0.64659054])
2023-07-02 10:34:39,173 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:39,173 [model] Got input parameters: {'Omega_m': 0.23460781564004618, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6465905377749988, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:39,173 [classy] Got parameters {'Omega_m': 0.23460781564004618, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:39,173 [classy] Computing new state
2023-07-02 10:34:39,174 [classy] Setting parameters: {'Omega_m': 0.23460781564004618, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:39,220 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 157.82599679170184}
2023-07-02 10:34:39,220 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:39,222 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.459036
2023-07-02 10:34:39,222 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6465905377749988, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:39,222 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:39,241 [fs_likelihood.fslikelihood] Computed log-likelihood = -48.1099
2023-07-02 10:34:39,241 [model] Computed derived parameters: {}
2023-07-02 10:34:39,241 [model] Posterior to be computed for parameters {'Omega_m': 0.3053295321117728, 'b1': 0.48401793403836596}
2023-07-02 10:34:39,241 [prior] Evaluating prior at array([0.30532953, 0.48401793])
2023-07-02 10:34:39,241 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:39,241 [model] Got input parameters: {'Omega_m': 0.3053295321117728, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48401793403836596, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:39,241 [classy] Got parameters {'Omega_m': 0.3053295321117728, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:39,241 [classy] Re-using computed results
2023-07-02 10:34:39,242 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.12985431648022}
2023-07-02 10:34:39,242 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:39,242 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48401793403836596, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:39,242 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:39,261 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.607945
2023-07-02 10:34:39,261 [model] Computed derived parameters: {}
2023-07-02 10:34:39,261 [model] Posterior to be computed for parameters {'Omega_m': 0.33810979996237267, 'b1': 0.46666479343654244}
2023-07-02 10:34:39,261 [prior] Evaluating prior at array([0.3381098 , 0.46666479])
2023-07-02 10:34:39,261 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:39,261 [model] Got input parameters: {'Omega_m': 0.33810979996237267, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46666479343654244, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:39,261 [classy] Got parameters {'Omega_m': 0.33810979996237267, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:39,261 [classy] Computing new state
2023-07-02 10:34:39,261 [classy] Setting parameters: {'Omega_m': 0.33810979996237267, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:39,307 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.28426163359194}
2023-07-02 10:34:39,307 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:39,309 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0380397
2023-07-02 10:34:39,309 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46666479343654244, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:39,309 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:39,329 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.06168
2023-07-02 10:34:39,329 [model] Computed derived parameters: {}
2023-07-02 10:34:39,329 [model] Posterior to be computed for parameters {'Omega_m': 0.3053295321117728, 'b1': 0.5354878330613593}
2023-07-02 10:34:39,329 [prior] Evaluating prior at array([0.30532953, 0.53548783])
2023-07-02 10:34:39,329 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:39,329 [model] Got input parameters: {'Omega_m': 0.3053295321117728, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5354878330613593, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:39,329 [classy] Got parameters {'Omega_m': 0.3053295321117728, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:39,329 [classy] Re-using computed results
2023-07-02 10:34:39,329 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.12985431648022}
2023-07-02 10:34:39,329 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:39,329 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5354878330613593, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:39,329 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:39,348 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.51706
2023-07-02 10:34:39,348 [model] Computed derived parameters: {}
2023-07-02 10:34:39,349 [model] Posterior to be computed for parameters {'Omega_m': 0.3414181474454102, 'b1': 0.4609136294630863}
2023-07-02 10:34:39,349 [prior] Evaluating prior at array([0.34141815, 0.46091363])
2023-07-02 10:34:39,349 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:39,349 [model] Got input parameters: {'Omega_m': 0.3414181474454102, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4609136294630863, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:39,349 [classy] Got parameters {'Omega_m': 0.3414181474454102, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:39,349 [classy] Computing new state
2023-07-02 10:34:39,349 [classy] Setting parameters: {'Omega_m': 0.3414181474454102, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:39,395 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.91501721580573}
2023-07-02 10:34:39,395 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:39,397 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0480649
2023-07-02 10:34:39,397 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4609136294630863, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:39,397 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:39,416 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.729208
2023-07-02 10:34:39,417 [model] Computed derived parameters: {}
2023-07-02 10:34:39,417 [model] Posterior to be computed for parameters {'Omega_m': 0.3053295321117728, 'b1': 0.5183514789114523}
2023-07-02 10:34:39,417 [prior] Evaluating prior at array([0.30532953, 0.51835148])
2023-07-02 10:34:39,417 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:39,417 [model] Got input parameters: {'Omega_m': 0.3053295321117728, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5183514789114523, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:39,417 [classy] Got parameters {'Omega_m': 0.3053295321117728, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:39,417 [classy] Re-using computed results
2023-07-02 10:34:39,417 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.12985431648022}
2023-07-02 10:34:39,417 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:39,417 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5183514789114523, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:39,417 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:39,437 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.35618
2023-07-02 10:34:39,437 [model] Computed derived parameters: {}
2023-07-02 10:34:39,437 [mcmc] New sample, #765:
Omega_m:0.3053295, b1:0.5236493
2023-07-02 10:34:39,437 [model] Posterior to be computed for parameters {'Omega_m': 0.28541073712308157, 'b1': 0.5529779069759072}
2023-07-02 10:34:39,437 [prior] Evaluating prior at array([0.28541074, 0.55297791])
2023-07-02 10:34:39,437 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:39,437 [model] Got input parameters: {'Omega_m': 0.28541073712308157, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5529779069759072, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:39,438 [classy] Got parameters {'Omega_m': 0.28541073712308157, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:39,438 [classy] Computing new state
2023-07-02 10:34:39,438 [classy] Setting parameters: {'Omega_m': 0.28541073712308157, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:39,484 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.64898226471203}
2023-07-02 10:34:39,484 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:39,486 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0483665
2023-07-02 10:34:39,486 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5529779069759072, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:39,486 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:39,505 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.72614
2023-07-02 10:34:39,505 [model] Computed derived parameters: {}
2023-07-02 10:34:39,506 [model] Posterior to be computed for parameters {'Omega_m': 0.3053295321117728, 'b1': 0.5344592517950444}
2023-07-02 10:34:39,506 [prior] Evaluating prior at array([0.30532953, 0.53445925])
2023-07-02 10:34:39,506 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:39,506 [model] Got input parameters: {'Omega_m': 0.3053295321117728, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5344592517950444, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:39,506 [classy] Got parameters {'Omega_m': 0.3053295321117728, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:39,506 [classy] Re-using computed results
2023-07-02 10:34:39,506 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.12985431648022}
2023-07-02 10:34:39,506 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:39,506 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5344592517950444, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:39,506 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:39,525 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.6132
2023-07-02 10:34:39,525 [model] Computed derived parameters: {}
2023-07-02 10:34:39,526 [model] Posterior to be computed for parameters {'Omega_m': 0.2695130115049873, 'b1': 0.5806141898341783}
2023-07-02 10:34:39,526 [prior] Evaluating prior at array([0.26951301, 0.58061419])
2023-07-02 10:34:39,526 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:39,526 [model] Got input parameters: {'Omega_m': 0.2695130115049873, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5806141898341783, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:39,526 [classy] Got parameters {'Omega_m': 0.2695130115049873, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:39,526 [classy] Computing new state
2023-07-02 10:34:39,526 [classy] Setting parameters: {'Omega_m': 0.2695130115049873, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:39,573 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.77098650270267}
2023-07-02 10:34:39,573 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:39,575 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.126801
2023-07-02 10:34:39,575 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5806141898341783, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:39,575 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:39,594 [fs_likelihood.fslikelihood] Computed log-likelihood = -11.2842
2023-07-02 10:34:39,594 [model] Computed derived parameters: {}
2023-07-02 10:34:39,594 [model] Posterior to be computed for parameters {'Omega_m': 0.3053295321117728, 'b1': 0.4909378201764896}
2023-07-02 10:34:39,594 [prior] Evaluating prior at array([0.30532953, 0.49093782])
2023-07-02 10:34:39,594 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:39,594 [model] Got input parameters: {'Omega_m': 0.3053295321117728, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4909378201764896, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:39,594 [classy] Got parameters {'Omega_m': 0.3053295321117728, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:39,594 [classy] Re-using computed results
2023-07-02 10:34:39,595 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.12985431648022}
2023-07-02 10:34:39,595 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:39,595 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4909378201764896, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:39,595 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:39,614 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.465948
2023-07-02 10:34:39,614 [model] Computed derived parameters: {}
2023-07-02 10:34:39,614 [model] Posterior to be computed for parameters {'Omega_m': 0.3261443607016598, 'b1': 0.48216740425980387}
2023-07-02 10:34:39,614 [prior] Evaluating prior at array([0.32614436, 0.4821674 ])
2023-07-02 10:34:39,614 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:39,614 [model] Got input parameters: {'Omega_m': 0.3261443607016598, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48216740425980387, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:39,614 [classy] Got parameters {'Omega_m': 0.3261443607016598, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:39,614 [classy] Computing new state
2023-07-02 10:34:39,614 [classy] Setting parameters: {'Omega_m': 0.3261443607016598, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:39,660 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.6476039425837}
2023-07-02 10:34:39,660 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:39,662 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0112673
2023-07-02 10:34:39,662 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48216740425980387, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:39,662 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:39,682 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.27148
2023-07-02 10:34:39,682 [model] Computed derived parameters: {}
2023-07-02 10:34:39,682 [mcmc] New sample, #766:
Omega_m:0.3053295, b1:0.5183515
2023-07-02 10:34:39,682 [model] Posterior to be computed for parameters {'Omega_m': 0.3261443607016598, 'b1': 0.4497161625034583}
2023-07-02 10:34:39,682 [prior] Evaluating prior at array([0.32614436, 0.44971616])
2023-07-02 10:34:39,683 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:39,683 [model] Got input parameters: {'Omega_m': 0.3261443607016598, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4497161625034583, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:39,683 [classy] Got parameters {'Omega_m': 0.3261443607016598, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:39,683 [classy] Re-using computed results
2023-07-02 10:34:39,683 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.6476039425837}
2023-07-02 10:34:39,683 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:39,683 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4497161625034583, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:39,683 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:39,702 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.160427
2023-07-02 10:34:39,702 [model] Computed derived parameters: {}
2023-07-02 10:34:39,702 [model] Posterior to be computed for parameters {'Omega_m': 0.27772982751507047, 'b1': 0.5663302440104706}
2023-07-02 10:34:39,702 [prior] Evaluating prior at array([0.27772983, 0.56633024])
2023-07-02 10:34:39,703 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:39,703 [model] Got input parameters: {'Omega_m': 0.27772982751507047, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5663302440104706, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:39,703 [classy] Got parameters {'Omega_m': 0.27772982751507047, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:39,703 [classy] Computing new state
2023-07-02 10:34:39,703 [classy] Setting parameters: {'Omega_m': 0.27772982751507047, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:39,749 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.66126454272208}
2023-07-02 10:34:39,749 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:39,751 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0812041
2023-07-02 10:34:39,751 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5663302440104706, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:39,751 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:39,770 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.31035
2023-07-02 10:34:39,770 [model] Computed derived parameters: {}
2023-07-02 10:34:39,770 [model] Posterior to be computed for parameters {'Omega_m': 0.3261443607016598, 'b1': 0.49963888791574146}
2023-07-02 10:34:39,770 [prior] Evaluating prior at array([0.32614436, 0.49963889])
2023-07-02 10:34:39,771 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:39,771 [model] Got input parameters: {'Omega_m': 0.3261443607016598, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49963888791574146, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:39,771 [classy] Got parameters {'Omega_m': 0.3261443607016598, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:39,771 [classy] Re-using computed results
2023-07-02 10:34:39,771 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.6476039425837}
2023-07-02 10:34:39,771 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:39,771 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49963888791574146, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:39,771 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:39,790 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.22596
2023-07-02 10:34:39,790 [model] Computed derived parameters: {}
2023-07-02 10:34:39,790 [model] Posterior to be computed for parameters {'Omega_m': 0.40661443212211046, 'b1': 0.3422798688459525}
2023-07-02 10:34:39,790 [prior] Evaluating prior at array([0.40661443, 0.34227987])
2023-07-02 10:34:39,791 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:39,791 [model] Got input parameters: {'Omega_m': 0.40661443212211046, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.3422798688459525, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:39,791 [classy] Got parameters {'Omega_m': 0.40661443212211046, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:39,791 [classy] Computing new state
2023-07-02 10:34:39,791 [classy] Setting parameters: {'Omega_m': 0.40661443212211046, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:39,837 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 137.24253741553542}
2023-07-02 10:34:39,837 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:39,839 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.438279
2023-07-02 10:34:39,839 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.3422798688459525, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:39,839 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:39,858 [fs_likelihood.fslikelihood] Computed log-likelihood = -28.8837
2023-07-02 10:34:39,858 [model] Computed derived parameters: {}
2023-07-02 10:34:39,858 [model] Posterior to be computed for parameters {'Omega_m': 0.3261443607016598, 'b1': 0.478452255207607}
2023-07-02 10:34:39,859 [prior] Evaluating prior at array([0.32614436, 0.47845226])
2023-07-02 10:34:39,859 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:39,859 [model] Got input parameters: {'Omega_m': 0.3261443607016598, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.478452255207607, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:39,859 [classy] Got parameters {'Omega_m': 0.3261443607016598, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:39,859 [classy] Re-using computed results
2023-07-02 10:34:39,859 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.6476039425837}
2023-07-02 10:34:39,859 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:39,859 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.478452255207607, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:39,859 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:39,878 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.2751
2023-07-02 10:34:39,879 [model] Computed derived parameters: {}
2023-07-02 10:34:39,879 [mcmc] New sample, #767:
Omega_m:0.3261444, b1:0.4821674
2023-07-02 10:34:39,879 [model] Posterior to be computed for parameters {'Omega_m': 0.29475546985082696, 'b1': 0.5330180646195952}
2023-07-02 10:34:39,879 [prior] Evaluating prior at array([0.29475547, 0.53301806])
2023-07-02 10:34:39,879 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:39,879 [model] Got input parameters: {'Omega_m': 0.29475546985082696, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5330180646195952, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:39,879 [classy] Got parameters {'Omega_m': 0.29475546985082696, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:39,879 [classy] Computing new state
2023-07-02 10:34:39,879 [classy] Setting parameters: {'Omega_m': 0.29475546985082696, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:39,925 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.4486975006506}
2023-07-02 10:34:39,925 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:39,927 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0203604
2023-07-02 10:34:39,927 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5330180646195952, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:39,927 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:39,946 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.324234
2023-07-02 10:34:39,947 [model] Computed derived parameters: {}
2023-07-02 10:34:39,947 [model] Posterior to be computed for parameters {'Omega_m': 0.3261443607016598, 'b1': 0.4608599315138536}
2023-07-02 10:34:39,947 [prior] Evaluating prior at array([0.32614436, 0.46085993])
2023-07-02 10:34:39,947 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:39,947 [model] Got input parameters: {'Omega_m': 0.3261443607016598, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4608599315138536, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:39,947 [classy] Got parameters {'Omega_m': 0.3261443607016598, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:39,947 [classy] Re-using computed results
2023-07-02 10:34:39,947 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.6476039425837}
2023-07-02 10:34:39,947 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:39,947 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4608599315138536, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:39,947 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:39,966 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.29069
2023-07-02 10:34:39,966 [model] Computed derived parameters: {}
2023-07-02 10:34:39,966 [model] Posterior to be computed for parameters {'Omega_m': 0.31602389791783503, 'b1': 0.4960454618630326}
2023-07-02 10:34:39,966 [prior] Evaluating prior at array([0.3160239 , 0.49604546])
2023-07-02 10:34:39,967 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:39,967 [model] Got input parameters: {'Omega_m': 0.31602389791783503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4960454618630326, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:39,967 [classy] Got parameters {'Omega_m': 0.31602389791783503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:39,967 [classy] Computing new state
2023-07-02 10:34:39,967 [classy] Setting parameters: {'Omega_m': 0.31602389791783503, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:40,013 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.83630110117804}
2023-07-02 10:34:40,013 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:40,015 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000964149
2023-07-02 10:34:40,015 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4960454618630326, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:40,015 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:40,035 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.90678
2023-07-02 10:34:40,035 [model] Computed derived parameters: {}
2023-07-02 10:34:40,035 [mcmc] New sample, #768:
Omega_m:0.3261444, b1:0.4784523
2023-07-02 10:34:40,035 [model] Posterior to be computed for parameters {'Omega_m': 0.31602389791783503, 'b1': 0.47198623761670777}
2023-07-02 10:34:40,035 [prior] Evaluating prior at array([0.3160239 , 0.47198624])
2023-07-02 10:34:40,035 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:40,035 [model] Got input parameters: {'Omega_m': 0.31602389791783503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47198623761670777, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:40,035 [classy] Got parameters {'Omega_m': 0.31602389791783503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:40,035 [classy] Re-using computed results
2023-07-02 10:34:40,035 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.83630110117804}
2023-07-02 10:34:40,035 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:40,035 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47198623761670777, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:40,035 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:40,055 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.07727
2023-07-02 10:34:40,055 [model] Computed derived parameters: {}
2023-07-02 10:34:40,055 [model] Posterior to be computed for parameters {'Omega_m': 0.32671646172209057, 'b1': 0.4774577264300984}
2023-07-02 10:34:40,055 [prior] Evaluating prior at array([0.32671646, 0.47745773])
2023-07-02 10:34:40,055 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:40,055 [model] Got input parameters: {'Omega_m': 0.32671646172209057, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4774577264300984, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:40,055 [classy] Got parameters {'Omega_m': 0.32671646172209057, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:40,055 [classy] Computing new state
2023-07-02 10:34:40,055 [classy] Setting parameters: {'Omega_m': 0.32671646172209057, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:40,101 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.58139602975714}
2023-07-02 10:34:40,101 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:40,103 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.012197
2023-07-02 10:34:40,103 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4774577264300984, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:40,103 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:40,124 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.20817
2023-07-02 10:34:40,124 [model] Computed derived parameters: {}
2023-07-02 10:34:40,125 [model] Posterior to be computed for parameters {'Omega_m': 0.31602389791783503, 'b1': 0.5393181046647049}
2023-07-02 10:34:40,125 [prior] Evaluating prior at array([0.3160239, 0.5393181])
2023-07-02 10:34:40,125 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:40,125 [model] Got input parameters: {'Omega_m': 0.31602389791783503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5393181046647049, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:40,125 [classy] Got parameters {'Omega_m': 0.31602389791783503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:40,125 [classy] Re-using computed results
2023-07-02 10:34:40,125 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.83630110117804}
2023-07-02 10:34:40,125 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:40,125 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5393181046647049, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:40,125 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:40,146 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.76287
2023-07-02 10:34:40,146 [model] Computed derived parameters: {}
2023-07-02 10:34:40,146 [model] Posterior to be computed for parameters {'Omega_m': 0.36346288775858804, 'b1': 0.41357848682243187}
2023-07-02 10:34:40,146 [prior] Evaluating prior at array([0.36346289, 0.41357849])
2023-07-02 10:34:40,146 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:40,146 [model] Got input parameters: {'Omega_m': 0.36346288775858804, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.41357848682243187, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:40,146 [classy] Got parameters {'Omega_m': 0.36346288775858804, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:40,146 [classy] Computing new state
2023-07-02 10:34:40,146 [classy] Setting parameters: {'Omega_m': 0.36346288775858804, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:40,193 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.5351660932445}
2023-07-02 10:34:40,193 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:40,195 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.141402
2023-07-02 10:34:40,195 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.41357848682243187, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:40,195 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:40,214 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.74218
2023-07-02 10:34:40,214 [model] Computed derived parameters: {}
2023-07-02 10:34:40,214 [model] Posterior to be computed for parameters {'Omega_m': 0.31602389791783503, 'b1': 0.49112070537120145}
2023-07-02 10:34:40,214 [prior] Evaluating prior at array([0.3160239 , 0.49112071])
2023-07-02 10:34:40,215 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:40,215 [model] Got input parameters: {'Omega_m': 0.31602389791783503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49112070537120145, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:40,215 [classy] Got parameters {'Omega_m': 0.31602389791783503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:40,215 [classy] Re-using computed results
2023-07-02 10:34:40,215 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.83630110117804}
2023-07-02 10:34:40,215 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:40,215 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49112070537120145, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:40,215 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:40,235 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.77741
2023-07-02 10:34:40,235 [model] Computed derived parameters: {}
2023-07-02 10:34:40,235 [mcmc] New sample, #769:
Omega_m:0.3160239, b1:0.4960455
2023-07-02 10:34:40,235 [model] Posterior to be computed for parameters {'Omega_m': 0.33346454744745213, 'b1': 0.46080223496787026}
2023-07-02 10:34:40,235 [prior] Evaluating prior at array([0.33346455, 0.46080223])
2023-07-02 10:34:40,235 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:40,235 [model] Got input parameters: {'Omega_m': 0.33346454744745213, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46080223496787026, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:40,235 [classy] Got parameters {'Omega_m': 0.33346454744745213, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:40,235 [classy] Computing new state
2023-07-02 10:34:40,235 [classy] Setting parameters: {'Omega_m': 0.33346454744745213, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:40,281 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.8082770406441}
2023-07-02 10:34:40,282 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:40,283 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0258476
2023-07-02 10:34:40,283 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46080223496787026, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:40,283 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:40,302 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.08839
2023-07-02 10:34:40,303 [model] Computed derived parameters: {}
2023-07-02 10:34:40,303 [model] Posterior to be computed for parameters {'Omega_m': 0.31602389791783503, 'b1': 0.43861872524879814}
2023-07-02 10:34:40,303 [prior] Evaluating prior at array([0.3160239 , 0.43861873])
2023-07-02 10:34:40,303 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:40,303 [model] Got input parameters: {'Omega_m': 0.31602389791783503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.43861872524879814, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:40,303 [classy] Got parameters {'Omega_m': 0.31602389791783503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:40,303 [classy] Re-using computed results
2023-07-02 10:34:40,303 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.83630110117804}
2023-07-02 10:34:40,303 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:40,303 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.43861872524879814, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:40,303 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:40,323 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.18111
2023-07-02 10:34:40,323 [model] Computed derived parameters: {}
2023-07-02 10:34:40,323 [model] Posterior to be computed for parameters {'Omega_m': 0.26827142854813074, 'b1': 0.5741326268488268}
2023-07-02 10:34:40,323 [prior] Evaluating prior at array([0.26827143, 0.57413263])
2023-07-02 10:34:40,323 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:40,323 [model] Got input parameters: {'Omega_m': 0.26827142854813074, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5741326268488268, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:40,323 [classy] Got parameters {'Omega_m': 0.26827142854813074, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:40,323 [classy] Computing new state
2023-07-02 10:34:40,323 [classy] Setting parameters: {'Omega_m': 0.26827142854813074, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:40,369 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.94116581640944}
2023-07-02 10:34:40,369 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:40,371 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.134676
2023-07-02 10:34:40,371 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5741326268488268, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:40,371 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:40,390 [fs_likelihood.fslikelihood] Computed log-likelihood = -12.4227
2023-07-02 10:34:40,390 [model] Computed derived parameters: {}
2023-07-02 10:34:40,391 [model] Posterior to be computed for parameters {'Omega_m': 0.31602389791783503, 'b1': 0.5168026734130112}
2023-07-02 10:34:40,391 [prior] Evaluating prior at array([0.3160239 , 0.51680267])
2023-07-02 10:34:40,391 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:40,391 [model] Got input parameters: {'Omega_m': 0.31602389791783503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5168026734130112, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:40,391 [classy] Got parameters {'Omega_m': 0.31602389791783503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:40,391 [classy] Re-using computed results
2023-07-02 10:34:40,391 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.83630110117804}
2023-07-02 10:34:40,391 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:40,391 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5168026734130112, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:40,391 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:40,411 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.00102
2023-07-02 10:34:40,411 [model] Computed derived parameters: {}
2023-07-02 10:34:40,411 [mcmc] New sample, #770:
Omega_m:0.3160239, b1:0.4911207
2023-07-02 10:34:40,411 [model] Posterior to be computed for parameters {'Omega_m': 0.3283229725643699, 'b1': 0.4954222122079339}
2023-07-02 10:34:40,411 [prior] Evaluating prior at array([0.32832297, 0.49542221])
2023-07-02 10:34:40,411 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:40,411 [model] Got input parameters: {'Omega_m': 0.3283229725643699, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4954222122079339, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:40,411 [classy] Got parameters {'Omega_m': 0.3283229725643699, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:40,411 [classy] Computing new state
2023-07-02 10:34:40,411 [classy] Setting parameters: {'Omega_m': 0.3283229725643699, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:40,458 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.39603148429538}
2023-07-02 10:34:40,458 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:40,459 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0150004
2023-07-02 10:34:40,460 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4954222122079339, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:40,460 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:40,479 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.980245
2023-07-02 10:34:40,479 [model] Computed derived parameters: {}
2023-07-02 10:34:40,479 [model] Posterior to be computed for parameters {'Omega_m': 0.31602389791783503, 'b1': 0.42416777057580346}
2023-07-02 10:34:40,479 [prior] Evaluating prior at array([0.3160239 , 0.42416777])
2023-07-02 10:34:40,479 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:40,479 [model] Got input parameters: {'Omega_m': 0.31602389791783503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42416777057580346, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:40,479 [classy] Got parameters {'Omega_m': 0.31602389791783503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:40,479 [classy] Re-using computed results
2023-07-02 10:34:40,479 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.83630110117804}
2023-07-02 10:34:40,479 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:40,479 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42416777057580346, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:40,480 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:40,499 [fs_likelihood.fslikelihood] Computed log-likelihood = -10.9002
2023-07-02 10:34:40,499 [model] Computed derived parameters: {}
2023-07-02 10:34:40,499 [model] Posterior to be computed for parameters {'Omega_m': 0.29262265512236846, 'b1': 0.557482917912546}
2023-07-02 10:34:40,499 [prior] Evaluating prior at array([0.29262266, 0.55748292])
2023-07-02 10:34:40,500 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:40,500 [model] Got input parameters: {'Omega_m': 0.29262265512236846, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.557482917912546, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:40,500 [classy] Got parameters {'Omega_m': 0.29262265512236846, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:40,500 [classy] Computing new state
2023-07-02 10:34:40,500 [classy] Setting parameters: {'Omega_m': 0.29262265512236846, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:40,546 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.7197163896965}
2023-07-02 10:34:40,546 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:40,548 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0256421
2023-07-02 10:34:40,548 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.557482917912546, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:40,548 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:40,568 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.95211
2023-07-02 10:34:40,568 [model] Computed derived parameters: {}
2023-07-02 10:34:40,568 [model] Posterior to be computed for parameters {'Omega_m': 0.31602389791783503, 'b1': 0.481421286094445}
2023-07-02 10:34:40,568 [prior] Evaluating prior at array([0.3160239 , 0.48142129])
2023-07-02 10:34:40,568 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:40,568 [model] Got input parameters: {'Omega_m': 0.31602389791783503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.481421286094445, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:40,568 [classy] Got parameters {'Omega_m': 0.31602389791783503, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:40,568 [classy] Re-using computed results
2023-07-02 10:34:40,568 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.83630110117804}
2023-07-02 10:34:40,568 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:40,568 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.481421286094445, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:40,568 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:40,588 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.15009
2023-07-02 10:34:40,588 [model] Computed derived parameters: {}
2023-07-02 10:34:40,588 [mcmc] New sample, #771:
Omega_m:0.3160239, b1:0.5168027
2023-07-02 10:34:40,588 [model] Posterior to be computed for parameters {'Omega_m': 0.3175506987124721, 'b1': 0.4787671266478385}
2023-07-02 10:34:40,588 [prior] Evaluating prior at array([0.3175507 , 0.47876713])
2023-07-02 10:34:40,588 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:40,588 [model] Got input parameters: {'Omega_m': 0.3175506987124721, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4787671266478385, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:40,588 [classy] Got parameters {'Omega_m': 0.3175506987124721, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:40,588 [classy] Computing new state
2023-07-02 10:34:40,589 [classy] Setting parameters: {'Omega_m': 0.3175506987124721, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:40,635 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.65482018296456}
2023-07-02 10:34:40,635 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:40,637 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00175689
2023-07-02 10:34:40,637 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4787671266478385, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:40,637 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:40,656 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.1324
2023-07-02 10:34:40,656 [model] Computed derived parameters: {}
2023-07-02 10:34:40,656 [mcmc] New sample, #772:
Omega_m:0.3160239, b1:0.4814213
2023-07-02 10:34:40,656 [model] Posterior to be computed for parameters {'Omega_m': 0.3175506987124721, 'b1': 0.49083957429593067}
2023-07-02 10:34:40,656 [prior] Evaluating prior at array([0.3175507 , 0.49083957])
2023-07-02 10:34:40,657 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:40,657 [model] Got input parameters: {'Omega_m': 0.3175506987124721, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49083957429593067, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:40,657 [classy] Got parameters {'Omega_m': 0.3175506987124721, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:40,657 [classy] Re-using computed results
2023-07-02 10:34:40,657 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.65482018296456}
2023-07-02 10:34:40,657 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:40,657 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49083957429593067, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:40,657 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:40,676 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.83176
2023-07-02 10:34:40,676 [model] Computed derived parameters: {}
2023-07-02 10:34:40,676 [mcmc] New sample, #773:
Omega_m:0.3175507, b1:0.4787671
2023-07-02 10:34:40,676 [model] Posterior to be computed for parameters {'Omega_m': 0.30584831429012355, 'b1': 0.5111827613518297}
2023-07-02 10:34:40,676 [prior] Evaluating prior at array([0.30584831, 0.51118276])
2023-07-02 10:34:40,676 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:40,676 [model] Got input parameters: {'Omega_m': 0.30584831429012355, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5111827613518297, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:40,676 [classy] Got parameters {'Omega_m': 0.30584831429012355, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:40,676 [classy] Computing new state
2023-07-02 10:34:40,676 [classy] Setting parameters: {'Omega_m': 0.30584831429012355, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:40,723 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.06618918910124}
2023-07-02 10:34:40,723 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:40,725 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00294782
2023-07-02 10:34:40,725 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5111827613518297, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:40,725 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:40,745 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.32732
2023-07-02 10:34:40,745 [model] Computed derived parameters: {}
2023-07-02 10:34:40,745 [mcmc] New sample, #774:
Omega_m:0.3175507, b1:0.4908396
2023-07-02 10:34:40,745 [model] Posterior to be computed for parameters {'Omega_m': 0.30584831429012355, 'b1': 0.48785006240798906}
2023-07-02 10:34:40,745 [prior] Evaluating prior at array([0.30584831, 0.48785006])
2023-07-02 10:34:40,745 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:40,745 [model] Got input parameters: {'Omega_m': 0.30584831429012355, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48785006240798906, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:40,745 [classy] Got parameters {'Omega_m': 0.30584831429012355, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:40,745 [classy] Re-using computed results
2023-07-02 10:34:40,745 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.06618918910124}
2023-07-02 10:34:40,745 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:40,746 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48785006240798906, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:40,746 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:40,765 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.216264
2023-07-02 10:34:40,765 [model] Computed derived parameters: {}
2023-07-02 10:34:40,765 [mcmc] New sample, #775:
Omega_m:0.3058483, b1:0.5111828
2023-07-02 10:34:40,765 [model] Posterior to be computed for parameters {'Omega_m': 0.3322652118899987, 'b1': 0.44192746493422236}
2023-07-02 10:34:40,765 [prior] Evaluating prior at array([0.33226521, 0.44192746])
2023-07-02 10:34:40,765 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:40,765 [model] Got input parameters: {'Omega_m': 0.3322652118899987, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44192746493422236, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:40,765 [classy] Got parameters {'Omega_m': 0.3322652118899987, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:40,765 [classy] Computing new state
2023-07-02 10:34:40,765 [classy] Setting parameters: {'Omega_m': 0.3322652118899987, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:40,812 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.94463939689018}
2023-07-02 10:34:40,812 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:40,813 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0230652
2023-07-02 10:34:40,814 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44192746493422236, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:40,814 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:40,833 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.557584
2023-07-02 10:34:40,833 [model] Computed derived parameters: {}
2023-07-02 10:34:40,833 [model] Posterior to be computed for parameters {'Omega_m': 0.30584831429012355, 'b1': 0.5426840624558239}
2023-07-02 10:34:40,833 [prior] Evaluating prior at array([0.30584831, 0.54268406])
2023-07-02 10:34:40,833 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:40,833 [model] Got input parameters: {'Omega_m': 0.30584831429012355, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5426840624558239, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:40,833 [classy] Got parameters {'Omega_m': 0.30584831429012355, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:40,833 [classy] Re-using computed results
2023-07-02 10:34:40,833 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.06618918910124}
2023-07-02 10:34:40,833 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:40,833 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5426840624558239, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:40,833 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:40,853 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.603565
2023-07-02 10:34:40,853 [model] Computed derived parameters: {}
2023-07-02 10:34:40,854 [mcmc] New sample, #776:
Omega_m:0.3058483, b1:0.4878501
2023-07-02 10:34:40,854 [model] Posterior to be computed for parameters {'Omega_m': 0.3082858250716271, 'b1': 0.5384467432916884}
2023-07-02 10:34:40,854 [prior] Evaluating prior at array([0.30828583, 0.53844674])
2023-07-02 10:34:40,854 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:40,854 [model] Got input parameters: {'Omega_m': 0.3082858250716271, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5384467432916884, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:40,854 [classy] Got parameters {'Omega_m': 0.3082858250716271, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:40,854 [classy] Computing new state
2023-07-02 10:34:40,854 [classy] Setting parameters: {'Omega_m': 0.3082858250716271, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:40,900 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.7683193622377}
2023-07-02 10:34:40,900 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:40,902 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0012946
2023-07-02 10:34:40,902 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5384467432916884, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:40,902 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:40,922 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.806231
2023-07-02 10:34:40,922 [model] Computed derived parameters: {}
2023-07-02 10:34:40,922 [mcmc] New sample, #777:
Omega_m:0.3058483, b1:0.5426841
2023-07-02 10:34:40,922 [model] Posterior to be computed for parameters {'Omega_m': 0.3082858250716271, 'b1': 0.5800332425820844}
2023-07-02 10:34:40,922 [prior] Evaluating prior at array([0.30828583, 0.58003324])
2023-07-02 10:34:40,922 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:40,923 [model] Got input parameters: {'Omega_m': 0.3082858250716271, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5800332425820844, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:40,923 [classy] Got parameters {'Omega_m': 0.3082858250716271, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:40,923 [classy] Re-using computed results
2023-07-02 10:34:40,923 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.7683193622377}
2023-07-02 10:34:40,923 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:40,923 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5800332425820844, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:40,923 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:40,942 [fs_likelihood.fslikelihood] Computed log-likelihood = -10.3921
2023-07-02 10:34:40,943 [model] Computed derived parameters: {}
2023-07-02 10:34:40,943 [model] Posterior to be computed for parameters {'Omega_m': 0.2469184908734055, 'b1': 0.645126468863868}
2023-07-02 10:34:40,943 [prior] Evaluating prior at array([0.24691849, 0.64512647])
2023-07-02 10:34:40,943 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:40,943 [model] Got input parameters: {'Omega_m': 0.2469184908734055, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.645126468863868, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:40,943 [classy] Got parameters {'Omega_m': 0.2469184908734055, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:40,943 [classy] Computing new state
2023-07-02 10:34:40,943 [classy] Setting parameters: {'Omega_m': 0.2469184908734055, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:40,989 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 155.976321776195}
2023-07-02 10:34:40,989 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:40,991 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.314057
2023-07-02 10:34:40,991 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.645126468863868, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:40,991 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:41,010 [fs_likelihood.fslikelihood] Computed log-likelihood = -33.1863
2023-07-02 10:34:41,011 [model] Computed derived parameters: {}
2023-07-02 10:34:41,011 [model] Posterior to be computed for parameters {'Omega_m': 0.3082858250716271, 'b1': 0.5526399073424195}
2023-07-02 10:34:41,011 [prior] Evaluating prior at array([0.30828583, 0.55263991])
2023-07-02 10:34:41,011 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:41,011 [model] Got input parameters: {'Omega_m': 0.3082858250716271, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5526399073424195, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:41,011 [classy] Got parameters {'Omega_m': 0.3082858250716271, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:41,011 [classy] Re-using computed results
2023-07-02 10:34:41,011 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.7683193622377}
2023-07-02 10:34:41,011 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:41,011 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5526399073424195, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:41,011 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:41,031 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.83095
2023-07-02 10:34:41,031 [model] Computed derived parameters: {}
2023-07-02 10:34:41,031 [model] Posterior to be computed for parameters {'Omega_m': 0.2938648706093703, 'b1': 0.5635158372098505}
2023-07-02 10:34:41,031 [prior] Evaluating prior at array([0.29386487, 0.56351584])
2023-07-02 10:34:41,031 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:41,031 [model] Got input parameters: {'Omega_m': 0.2938648706093703, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5635158372098505, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:41,031 [classy] Got parameters {'Omega_m': 0.2938648706093703, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:41,031 [classy] Computing new state
2023-07-02 10:34:41,031 [classy] Setting parameters: {'Omega_m': 0.2938648706093703, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:41,078 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.56165806521935}
2023-07-02 10:34:41,078 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:41,079 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0224877
2023-07-02 10:34:41,079 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5635158372098505, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:41,079 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:41,100 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.53255
2023-07-02 10:34:41,100 [model] Computed derived parameters: {}
2023-07-02 10:34:41,100 [model] Posterior to be computed for parameters {'Omega_m': 0.3082858250716271, 'b1': 0.5228464856309065}
2023-07-02 10:34:41,100 [prior] Evaluating prior at array([0.30828583, 0.52284649])
2023-07-02 10:34:41,100 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:41,100 [model] Got input parameters: {'Omega_m': 0.3082858250716271, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5228464856309065, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:41,100 [classy] Got parameters {'Omega_m': 0.3082858250716271, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:41,100 [classy] Re-using computed results
2023-07-02 10:34:41,100 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.7683193622377}
2023-07-02 10:34:41,100 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:41,100 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5228464856309065, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:41,100 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:41,120 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.36328
2023-07-02 10:34:41,120 [model] Computed derived parameters: {}
2023-07-02 10:34:41,120 [mcmc] New sample, #778:
Omega_m:0.3082858, b1:0.5384467
2023-07-02 10:34:41,120 [model] Posterior to be computed for parameters {'Omega_m': 0.30367716098031533, 'b1': 0.5308580935480344}
2023-07-02 10:34:41,120 [prior] Evaluating prior at array([0.30367716, 0.53085809])
2023-07-02 10:34:41,120 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:41,120 [model] Got input parameters: {'Omega_m': 0.30367716098031533, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5308580935480344, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:41,120 [classy] Got parameters {'Omega_m': 0.30367716098031533, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:41,120 [classy] Computing new state
2023-07-02 10:34:41,121 [classy] Setting parameters: {'Omega_m': 0.30367716098031533, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:41,169 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.33327043780565}
2023-07-02 10:34:41,169 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:41,171 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00506472
2023-07-02 10:34:41,171 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5308580935480344, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:41,171 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:41,190 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.87785
2023-07-02 10:34:41,190 [model] Computed derived parameters: {}
2023-07-02 10:34:41,190 [mcmc] New sample, #779:
Omega_m:0.3082858, b1:0.5228465
2023-07-02 10:34:41,190 [model] Posterior to be computed for parameters {'Omega_m': 0.30367716098031533, 'b1': 0.5470873425066852}
2023-07-02 10:34:41,190 [prior] Evaluating prior at array([0.30367716, 0.54708734])
2023-07-02 10:34:41,191 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:41,191 [model] Got input parameters: {'Omega_m': 0.30367716098031533, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5470873425066852, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:41,191 [classy] Got parameters {'Omega_m': 0.30367716098031533, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:41,191 [classy] Re-using computed results
2023-07-02 10:34:41,191 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.33327043780565}
2023-07-02 10:34:41,191 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:41,191 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5470873425066852, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:41,191 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:41,211 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.269559
2023-07-02 10:34:41,211 [model] Computed derived parameters: {}
2023-07-02 10:34:41,211 [model] Posterior to be computed for parameters {'Omega_m': 0.2816542705360652, 'b1': 0.5691422383555966}
2023-07-02 10:34:41,211 [prior] Evaluating prior at array([0.28165427, 0.56914224])
2023-07-02 10:34:41,212 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:41,212 [model] Got input parameters: {'Omega_m': 0.2816542705360652, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5691422383555966, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:41,212 [classy] Got parameters {'Omega_m': 0.2816542705360652, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:41,212 [classy] Computing new state
2023-07-02 10:34:41,212 [classy] Setting parameters: {'Omega_m': 0.2816542705360652, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:41,258 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.141101369418}
2023-07-02 10:34:41,258 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:41,260 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0632824
2023-07-02 10:34:41,260 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5691422383555966, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:41,260 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:41,279 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.53401
2023-07-02 10:34:41,280 [model] Computed derived parameters: {}
2023-07-02 10:34:41,280 [model] Posterior to be computed for parameters {'Omega_m': 0.30367716098031533, 'b1': 0.5239350205432896}
2023-07-02 10:34:41,280 [prior] Evaluating prior at array([0.30367716, 0.52393502])
2023-07-02 10:34:41,280 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:41,280 [model] Got input parameters: {'Omega_m': 0.30367716098031533, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5239350205432896, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:41,280 [classy] Got parameters {'Omega_m': 0.30367716098031533, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:41,280 [classy] Re-using computed results
2023-07-02 10:34:41,280 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.33327043780565}
2023-07-02 10:34:41,280 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:41,280 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5239350205432896, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:41,280 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:41,300 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.11981
2023-07-02 10:34:41,300 [model] Computed derived parameters: {}
2023-07-02 10:34:41,300 [mcmc] New sample, #780:
Omega_m:0.3036772, b1:0.5308581
2023-07-02 10:34:41,300 [model] Posterior to be computed for parameters {'Omega_m': 0.342380037977216, 'b1': 0.45665472637983806}
2023-07-02 10:34:41,301 [prior] Evaluating prior at array([0.34238004, 0.45665473])
2023-07-02 10:34:41,301 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:41,301 [model] Got input parameters: {'Omega_m': 0.342380037977216, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45665472637983806, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:41,301 [classy] Got parameters {'Omega_m': 0.342380037977216, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:41,301 [classy] Computing new state
2023-07-02 10:34:41,301 [classy] Setting parameters: {'Omega_m': 0.342380037977216, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:41,347 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.80826801596197}
2023-07-02 10:34:41,347 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:41,349 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.051185
2023-07-02 10:34:41,350 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45665472637983806, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:41,350 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:41,369 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.872241
2023-07-02 10:34:41,369 [model] Computed derived parameters: {}
2023-07-02 10:34:41,369 [model] Posterior to be computed for parameters {'Omega_m': 0.30367716098031533, 'b1': 0.503719821139953}
2023-07-02 10:34:41,369 [prior] Evaluating prior at array([0.30367716, 0.50371982])
2023-07-02 10:34:41,370 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:41,370 [model] Got input parameters: {'Omega_m': 0.30367716098031533, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.503719821139953, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:41,370 [classy] Got parameters {'Omega_m': 0.30367716098031533, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:41,370 [classy] Re-using computed results
2023-07-02 10:34:41,370 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.33327043780565}
2023-07-02 10:34:41,370 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:41,370 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.503719821139953, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:41,370 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:41,389 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.36997
2023-07-02 10:34:41,389 [model] Computed derived parameters: {}
2023-07-02 10:34:41,389 [mcmc] New sample, #781:
Omega_m:0.3036772, b1:0.523935
2023-07-02 10:34:41,389 [model] Posterior to be computed for parameters {'Omega_m': 0.30266591616154437, 'b1': 0.5054777485644084}
2023-07-02 10:34:41,389 [prior] Evaluating prior at array([0.30266592, 0.50547775])
2023-07-02 10:34:41,389 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:41,389 [model] Got input parameters: {'Omega_m': 0.30266591616154437, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5054777485644084, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:41,389 [classy] Got parameters {'Omega_m': 0.30266591616154437, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:41,390 [classy] Computing new state
2023-07-02 10:34:41,390 [classy] Setting parameters: {'Omega_m': 0.30266591616154437, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:41,436 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.45824102905965}
2023-07-02 10:34:41,436 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:41,438 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00626089
2023-07-02 10:34:41,438 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5054777485644084, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:41,438 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:41,458 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.21638
2023-07-02 10:34:41,458 [model] Computed derived parameters: {}
2023-07-02 10:34:41,458 [mcmc] New sample, #782:
Omega_m:0.3036772, b1:0.5037198
2023-07-02 10:34:41,458 [model] Posterior to be computed for parameters {'Omega_m': 0.30266591616154437, 'b1': 0.5442602187845831}
2023-07-02 10:34:41,459 [prior] Evaluating prior at array([0.30266592, 0.54426022])
2023-07-02 10:34:41,459 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:41,459 [model] Got input parameters: {'Omega_m': 0.30266591616154437, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5442602187845831, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:41,459 [classy] Got parameters {'Omega_m': 0.30266591616154437, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:41,459 [classy] Re-using computed results
2023-07-02 10:34:41,459 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.45824102905965}
2023-07-02 10:34:41,459 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:41,459 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5442602187845831, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:41,459 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:41,478 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.737774
2023-07-02 10:34:41,478 [model] Computed derived parameters: {}
2023-07-02 10:34:41,478 [mcmc] New sample, #783:
Omega_m:0.3026659, b1:0.5054777
2023-07-02 10:34:41,479 [model] Posterior to be computed for parameters {'Omega_m': 0.2833346185868904, 'b1': 0.5778653532940432}
2023-07-02 10:34:41,479 [prior] Evaluating prior at array([0.28333462, 0.57786535])
2023-07-02 10:34:41,479 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:41,479 [model] Got input parameters: {'Omega_m': 0.2833346185868904, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5778653532940432, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:41,479 [classy] Got parameters {'Omega_m': 0.2833346185868904, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:41,479 [classy] Computing new state
2023-07-02 10:34:41,479 [classy] Setting parameters: {'Omega_m': 0.2833346185868904, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:41,525 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.92027446112164}
2023-07-02 10:34:41,525 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:41,527 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0563434
2023-07-02 10:34:41,527 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5778653532940432, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:41,527 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:41,547 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.66759
2023-07-02 10:34:41,547 [model] Computed derived parameters: {}
2023-07-02 10:34:41,547 [model] Posterior to be computed for parameters {'Omega_m': 0.30266591616154437, 'b1': 0.4869976580864138}
2023-07-02 10:34:41,547 [prior] Evaluating prior at array([0.30266592, 0.48699766])
2023-07-02 10:34:41,547 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:41,547 [model] Got input parameters: {'Omega_m': 0.30266591616154437, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4869976580864138, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:41,547 [classy] Got parameters {'Omega_m': 0.30266591616154437, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:41,547 [classy] Re-using computed results
2023-07-02 10:34:41,547 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.45824102905965}
2023-07-02 10:34:41,547 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:41,547 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4869976580864138, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:41,547 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:41,568 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.28638
2023-07-02 10:34:41,568 [model] Computed derived parameters: {}
2023-07-02 10:34:41,568 [model] Posterior to be computed for parameters {'Omega_m': 0.2910660739730825, 'b1': 0.5644251485067799}
2023-07-02 10:34:41,568 [prior] Evaluating prior at array([0.29106607, 0.56442515])
2023-07-02 10:34:41,568 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:41,568 [model] Got input parameters: {'Omega_m': 0.2910660739730825, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5644251485067799, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:41,568 [classy] Got parameters {'Omega_m': 0.2910660739730825, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:41,568 [classy] Computing new state
2023-07-02 10:34:41,568 [classy] Setting parameters: {'Omega_m': 0.2910660739730825, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:41,615 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.91859362843394}
2023-07-02 10:34:41,615 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:41,617 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0299053
2023-07-02 10:34:41,617 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5644251485067799, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:41,617 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:41,636 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.83744
2023-07-02 10:34:41,636 [model] Computed derived parameters: {}
2023-07-02 10:34:41,636 [model] Posterior to be computed for parameters {'Omega_m': 0.30266591616154437, 'b1': 0.5348174977176182}
2023-07-02 10:34:41,636 [prior] Evaluating prior at array([0.30266592, 0.5348175 ])
2023-07-02 10:34:41,636 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:41,636 [model] Got input parameters: {'Omega_m': 0.30266591616154437, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5348174977176182, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:41,636 [classy] Got parameters {'Omega_m': 0.30266591616154437, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:41,636 [classy] Re-using computed results
2023-07-02 10:34:41,636 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.45824102905965}
2023-07-02 10:34:41,636 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:41,636 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5348174977176182, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:41,636 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:41,656 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.60417
2023-07-02 10:34:41,656 [model] Computed derived parameters: {}
2023-07-02 10:34:41,657 [mcmc] New sample, #784:
Omega_m:0.3026659, b1:0.5442602
2023-07-02 10:34:41,657 [model] Posterior to be computed for parameters {'Omega_m': 0.26220290395518897, 'b1': 0.6051575751284248}
2023-07-02 10:34:41,657 [prior] Evaluating prior at array([0.2622029 , 0.60515758])
2023-07-02 10:34:41,657 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:41,657 [model] Got input parameters: {'Omega_m': 0.26220290395518897, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6051575751284248, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:41,657 [classy] Got parameters {'Omega_m': 0.26220290395518897, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:41,657 [classy] Computing new state
2023-07-02 10:34:41,657 [classy] Setting parameters: {'Omega_m': 0.26220290395518897, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:41,703 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.78261164877955}
2023-07-02 10:34:41,703 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:41,705 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.17704
2023-07-02 10:34:41,705 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6051575751284248, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:41,706 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:41,726 [fs_likelihood.fslikelihood] Computed log-likelihood = -17.0012
2023-07-02 10:34:41,726 [model] Computed derived parameters: {}
2023-07-02 10:34:41,726 [model] Posterior to be computed for parameters {'Omega_m': 0.30266591616154437, 'b1': 0.5444710670383351}
2023-07-02 10:34:41,726 [prior] Evaluating prior at array([0.30266592, 0.54447107])
2023-07-02 10:34:41,726 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:41,726 [model] Got input parameters: {'Omega_m': 0.30266591616154437, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5444710670383351, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:41,726 [classy] Got parameters {'Omega_m': 0.30266591616154437, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:41,726 [classy] Re-using computed results
2023-07-02 10:34:41,726 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.45824102905965}
2023-07-02 10:34:41,726 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:41,726 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5444710670383351, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:41,726 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:41,745 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.712706
2023-07-02 10:34:41,746 [model] Computed derived parameters: {}
2023-07-02 10:34:41,746 [mcmc] New sample, #785:
Omega_m:0.3026659, b1:0.5348175
2023-07-02 10:34:41,746 [model] Posterior to be computed for parameters {'Omega_m': 0.3043816828491978, 'b1': 0.5414884131268335}
2023-07-02 10:34:41,746 [prior] Evaluating prior at array([0.30438168, 0.54148841])
2023-07-02 10:34:41,746 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:41,746 [model] Got input parameters: {'Omega_m': 0.3043816828491978, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5414884131268335, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:41,746 [classy] Got parameters {'Omega_m': 0.3043816828491978, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:41,746 [classy] Computing new state
2023-07-02 10:34:41,746 [classy] Setting parameters: {'Omega_m': 0.3043816828491978, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:41,792 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.24642289816748}
2023-07-02 10:34:41,793 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:41,794 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00431064
2023-07-02 10:34:41,794 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5414884131268335, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:41,794 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:41,815 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.936685
2023-07-02 10:34:41,815 [model] Computed derived parameters: {}
2023-07-02 10:34:41,815 [mcmc] New sample, #786:
Omega_m:0.3026659, b1:0.5444711
2023-07-02 10:34:41,815 [model] Posterior to be computed for parameters {'Omega_m': 0.3043816828491978, 'b1': 0.5752089902239124}
2023-07-02 10:34:41,815 [prior] Evaluating prior at array([0.30438168, 0.57520899])
2023-07-02 10:34:41,815 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:41,815 [model] Got input parameters: {'Omega_m': 0.3043816828491978, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5752089902239124, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:41,815 [classy] Got parameters {'Omega_m': 0.3043816828491978, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:41,815 [classy] Re-using computed results
2023-07-02 10:34:41,815 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.24642289816748}
2023-07-02 10:34:41,815 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:41,815 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5752089902239124, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:41,815 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:41,835 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.46639
2023-07-02 10:34:41,835 [model] Computed derived parameters: {}
2023-07-02 10:34:41,835 [model] Posterior to be computed for parameters {'Omega_m': 0.2856089630700188, 'b1': 0.5741225273579887}
2023-07-02 10:34:41,835 [prior] Evaluating prior at array([0.28560896, 0.57412253])
2023-07-02 10:34:41,835 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:41,835 [model] Got input parameters: {'Omega_m': 0.2856089630700188, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5741225273579887, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:41,835 [classy] Got parameters {'Omega_m': 0.2856089630700188, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:41,835 [classy] Computing new state
2023-07-02 10:34:41,835 [classy] Setting parameters: {'Omega_m': 0.2856089630700188, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:41,882 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.6231671360117}
2023-07-02 10:34:41,882 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:41,884 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.047639
2023-07-02 10:34:41,884 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5741225273579887, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:41,884 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:41,903 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.75951
2023-07-02 10:34:41,903 [model] Computed derived parameters: {}
2023-07-02 10:34:41,903 [model] Posterior to be computed for parameters {'Omega_m': 0.3043816828491978, 'b1': 0.5362285178165631}
2023-07-02 10:34:41,903 [prior] Evaluating prior at array([0.30438168, 0.53622852])
2023-07-02 10:34:41,903 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:41,903 [model] Got input parameters: {'Omega_m': 0.3043816828491978, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5362285178165631, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:41,903 [classy] Got parameters {'Omega_m': 0.3043816828491978, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:41,903 [classy] Re-using computed results
2023-07-02 10:34:41,903 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.24642289816748}
2023-07-02 10:34:41,903 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:41,903 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5362285178165631, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:41,904 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:41,924 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.49202
2023-07-02 10:34:41,924 [model] Computed derived parameters: {}
2023-07-02 10:34:41,924 [mcmc] New sample, #787:
Omega_m:0.3043817, b1:0.5414884
2023-07-02 10:34:41,924 [model] Posterior to be computed for parameters {'Omega_m': 0.3369676934174711, 'b1': 0.4795816598369268}
2023-07-02 10:34:41,924 [prior] Evaluating prior at array([0.33696769, 0.47958166])
2023-07-02 10:34:41,924 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:41,924 [model] Got input parameters: {'Omega_m': 0.3369676934174711, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4795816598369268, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:41,924 [classy] Got parameters {'Omega_m': 0.3369676934174711, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:41,924 [classy] Computing new state
2023-07-02 10:34:41,924 [classy] Setting parameters: {'Omega_m': 0.3369676934174711, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:41,971 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.41249149916416}
2023-07-02 10:34:41,971 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:41,973 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0348359
2023-07-02 10:34:41,973 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4795816598369268, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:41,973 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:41,992 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.518652
2023-07-02 10:34:41,992 [model] Computed derived parameters: {}
2023-07-02 10:34:41,992 [model] Posterior to be computed for parameters {'Omega_m': 0.3043816828491978, 'b1': 0.591308321744088}
2023-07-02 10:34:41,992 [prior] Evaluating prior at array([0.30438168, 0.59130832])
2023-07-02 10:34:41,992 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:41,992 [model] Got input parameters: {'Omega_m': 0.3043816828491978, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.591308321744088, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:41,992 [classy] Got parameters {'Omega_m': 0.3043816828491978, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:41,992 [classy] Re-using computed results
2023-07-02 10:34:41,992 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.24642289816748}
2023-07-02 10:34:41,992 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:41,992 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.591308321744088, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:41,992 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:42,012 [fs_likelihood.fslikelihood] Computed log-likelihood = -12.4699
2023-07-02 10:34:42,012 [model] Computed derived parameters: {}
2023-07-02 10:34:42,012 [model] Posterior to be computed for parameters {'Omega_m': 0.40267265769820704, 'b1': 0.36536148635574106}
2023-07-02 10:34:42,012 [prior] Evaluating prior at array([0.40267266, 0.36536149])
2023-07-02 10:34:42,013 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:42,013 [model] Got input parameters: {'Omega_m': 0.40267265769820704, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.36536148635574106, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:42,013 [classy] Got parameters {'Omega_m': 0.40267265769820704, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:42,013 [classy] Computing new state
2023-07-02 10:34:42,013 [classy] Setting parameters: {'Omega_m': 0.40267265769820704, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:42,061 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 137.61631940004492}
2023-07-02 10:34:42,061 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:42,063 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.405723
2023-07-02 10:34:42,063 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.36536148635574106, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:42,063 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:42,083 [fs_likelihood.fslikelihood] Computed log-likelihood = -27.938
2023-07-02 10:34:42,083 [model] Computed derived parameters: {}
2023-07-02 10:34:42,083 [model] Posterior to be computed for parameters {'Omega_m': 0.3043816828491978, 'b1': 0.5264408056703963}
2023-07-02 10:34:42,083 [prior] Evaluating prior at array([0.30438168, 0.52644081])
2023-07-02 10:34:42,083 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:42,083 [model] Got input parameters: {'Omega_m': 0.3043816828491978, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5264408056703963, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:42,083 [classy] Got parameters {'Omega_m': 0.3043816828491978, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:42,083 [classy] Re-using computed results
2023-07-02 10:34:42,083 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.24642289816748}
2023-07-02 10:34:42,083 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:42,083 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5264408056703963, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:42,083 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:42,102 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.11458
2023-07-02 10:34:42,102 [model] Computed derived parameters: {}
2023-07-02 10:34:42,102 [mcmc] New sample, #788:
Omega_m:0.3043817, b1:0.5362285
2023-07-02 10:34:42,103 [model] Posterior to be computed for parameters {'Omega_m': 0.3547698331407739, 'b1': 0.43884707008735613}
2023-07-02 10:34:42,103 [prior] Evaluating prior at array([0.35476983, 0.43884707])
2023-07-02 10:34:42,103 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:42,103 [model] Got input parameters: {'Omega_m': 0.3547698331407739, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.43884707008735613, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:42,103 [classy] Got parameters {'Omega_m': 0.3547698331407739, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:42,103 [classy] Computing new state
2023-07-02 10:34:42,103 [classy] Setting parameters: {'Omega_m': 0.3547698331407739, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:42,153 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.45734625143666}
2023-07-02 10:34:42,153 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:42,155 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0992993
2023-07-02 10:34:42,155 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.43884707008735613, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:42,155 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:42,175 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.81555
2023-07-02 10:34:42,175 [model] Computed derived parameters: {}
2023-07-02 10:34:42,175 [model] Posterior to be computed for parameters {'Omega_m': 0.3043816828491978, 'b1': 0.5012873130838296}
2023-07-02 10:34:42,175 [prior] Evaluating prior at array([0.30438168, 0.50128731])
2023-07-02 10:34:42,175 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:42,175 [model] Got input parameters: {'Omega_m': 0.3043816828491978, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5012873130838296, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:42,175 [classy] Got parameters {'Omega_m': 0.3043816828491978, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:42,175 [classy] Re-using computed results
2023-07-02 10:34:42,175 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.24642289816748}
2023-07-02 10:34:42,175 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:42,175 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5012873130838296, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:42,175 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:42,195 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.35783
2023-07-02 10:34:42,195 [model] Computed derived parameters: {}
2023-07-02 10:34:42,195 [mcmc] New sample, #789:
Omega_m:0.3043817, b1:0.5264408
2023-07-02 10:34:42,195 [model] Posterior to be computed for parameters {'Omega_m': 0.3602424143771391, 'b1': 0.40418015359058446}
2023-07-02 10:34:42,195 [prior] Evaluating prior at array([0.36024241, 0.40418015])
2023-07-02 10:34:42,195 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:42,195 [model] Got input parameters: {'Omega_m': 0.3602424143771391, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.40418015359058446, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:42,195 [classy] Got parameters {'Omega_m': 0.3602424143771391, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:42,196 [classy] Computing new state
2023-07-02 10:34:42,196 [classy] Setting parameters: {'Omega_m': 0.3602424143771391, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:42,243 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.8743783163688}
2023-07-02 10:34:42,243 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:42,245 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.125038
2023-07-02 10:34:42,245 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.40418015359058446, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:42,245 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:42,265 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.08152
2023-07-02 10:34:42,265 [model] Computed derived parameters: {}
2023-07-02 10:34:42,265 [model] Posterior to be computed for parameters {'Omega_m': 0.3043816828491978, 'b1': 0.5038994006916178}
2023-07-02 10:34:42,265 [prior] Evaluating prior at array([0.30438168, 0.5038994 ])
2023-07-02 10:34:42,265 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:42,265 [model] Got input parameters: {'Omega_m': 0.3043816828491978, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5038994006916178, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:42,265 [classy] Got parameters {'Omega_m': 0.3043816828491978, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:42,265 [classy] Re-using computed results
2023-07-02 10:34:42,265 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.24642289816748}
2023-07-02 10:34:42,265 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:42,265 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5038994006916178, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:42,265 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:42,284 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.58925
2023-07-02 10:34:42,285 [model] Computed derived parameters: {}
2023-07-02 10:34:42,285 [mcmc] New sample, #790:
Omega_m:0.3043817, b1:0.5012873
2023-07-02 10:34:42,285 [model] Posterior to be computed for parameters {'Omega_m': 0.29667274637761143, 'b1': 0.5173004590557603}
2023-07-02 10:34:42,285 [prior] Evaluating prior at array([0.29667275, 0.51730046])
2023-07-02 10:34:42,285 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:42,285 [model] Got input parameters: {'Omega_m': 0.29667274637761143, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5173004590557603, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:42,285 [classy] Got parameters {'Omega_m': 0.29667274637761143, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:42,285 [classy] Computing new state
2023-07-02 10:34:42,285 [classy] Setting parameters: {'Omega_m': 0.29667274637761143, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:42,332 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.20652241366867}
2023-07-02 10:34:42,332 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:42,334 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0161572
2023-07-02 10:34:42,334 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5173004590557603, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:42,334 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:42,353 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.148945
2023-07-02 10:34:42,353 [model] Computed derived parameters: {}
2023-07-02 10:34:42,354 [model] Posterior to be computed for parameters {'Omega_m': 0.3043816828491978, 'b1': 0.4823589532902795}
2023-07-02 10:34:42,354 [prior] Evaluating prior at array([0.30438168, 0.48235895])
2023-07-02 10:34:42,354 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:42,354 [model] Got input parameters: {'Omega_m': 0.3043816828491978, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4823589532902795, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:42,354 [classy] Got parameters {'Omega_m': 0.3043816828491978, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:42,354 [classy] Re-using computed results
2023-07-02 10:34:42,354 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.24642289816748}
2023-07-02 10:34:42,354 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:42,354 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4823589532902795, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:42,354 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:42,374 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.33071
2023-07-02 10:34:42,374 [model] Computed derived parameters: {}
2023-07-02 10:34:42,374 [model] Posterior to be computed for parameters {'Omega_m': 0.3403286488422774, 'b1': 0.4414099261625883}
2023-07-02 10:34:42,374 [prior] Evaluating prior at array([0.34032865, 0.44140993])
2023-07-02 10:34:42,374 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:42,374 [model] Got input parameters: {'Omega_m': 0.3403286488422774, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4414099261625883, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:42,374 [classy] Got parameters {'Omega_m': 0.3403286488422774, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:42,374 [classy] Computing new state
2023-07-02 10:34:42,375 [classy] Setting parameters: {'Omega_m': 0.3403286488422774, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:42,421 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.03625300742303}
2023-07-02 10:34:42,421 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:42,423 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0446424
2023-07-02 10:34:42,423 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4414099261625883, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:42,423 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:42,442 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.732306
2023-07-02 10:34:42,442 [model] Computed derived parameters: {}
2023-07-02 10:34:42,442 [mcmc] New sample, #791:
Omega_m:0.3043817, b1:0.5038994
2023-07-02 10:34:42,442 [model] Posterior to be computed for parameters {'Omega_m': 0.3403286488422774, 'b1': 0.43483404863056474}
2023-07-02 10:34:42,442 [prior] Evaluating prior at array([0.34032865, 0.43483405])
2023-07-02 10:34:42,442 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:42,442 [model] Got input parameters: {'Omega_m': 0.3403286488422774, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.43483404863056474, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:42,443 [classy] Got parameters {'Omega_m': 0.3403286488422774, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:42,443 [classy] Re-using computed results
2023-07-02 10:34:42,443 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.03625300742303}
2023-07-02 10:34:42,443 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:42,443 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.43483404863056474, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:42,443 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:42,462 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.31069
2023-07-02 10:34:42,462 [model] Computed derived parameters: {}
2023-07-02 10:34:42,462 [mcmc] New sample, #792:
Omega_m:0.3403286, b1:0.4414099
2023-07-02 10:34:42,462 [model] Posterior to be computed for parameters {'Omega_m': 0.3458665924355705, 'b1': 0.4252070001285323}
2023-07-02 10:34:42,462 [prior] Evaluating prior at array([0.34586659, 0.425207 ])
2023-07-02 10:34:42,462 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:42,462 [model] Got input parameters: {'Omega_m': 0.3458665924355705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4252070001285323, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:42,462 [classy] Got parameters {'Omega_m': 0.3458665924355705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:42,462 [classy] Computing new state
2023-07-02 10:34:42,462 [classy] Setting parameters: {'Omega_m': 0.3458665924355705, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:42,508 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.42363122408656}
2023-07-02 10:34:42,508 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:42,510 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0632527
2023-07-02 10:34:42,510 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4252070001285323, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:42,510 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:42,531 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.7304
2023-07-02 10:34:42,531 [model] Computed derived parameters: {}
2023-07-02 10:34:42,531 [mcmc] New sample, #793:
Omega_m:0.3403286, b1:0.434834
2023-07-02 10:34:42,531 [model] Posterior to be computed for parameters {'Omega_m': 0.3458665924355705, 'b1': 0.37153771754793086}
2023-07-02 10:34:42,531 [prior] Evaluating prior at array([0.34586659, 0.37153772])
2023-07-02 10:34:42,531 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:42,531 [model] Got input parameters: {'Omega_m': 0.3458665924355705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.37153771754793086, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:42,531 [classy] Got parameters {'Omega_m': 0.3458665924355705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:42,531 [classy] Re-using computed results
2023-07-02 10:34:42,531 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.42363122408656}
2023-07-02 10:34:42,531 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:42,531 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.37153771754793086, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:42,531 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:42,550 [fs_likelihood.fslikelihood] Computed log-likelihood = -15.3922
2023-07-02 10:34:42,550 [model] Computed derived parameters: {}
2023-07-02 10:34:42,551 [model] Posterior to be computed for parameters {'Omega_m': 0.36015791900005417, 'b1': 0.4003632487112563}
2023-07-02 10:34:42,551 [prior] Evaluating prior at array([0.36015792, 0.40036325])
2023-07-02 10:34:42,551 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:42,551 [model] Got input parameters: {'Omega_m': 0.36015791900005417, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4003632487112563, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:42,551 [classy] Got parameters {'Omega_m': 0.36015791900005417, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:42,551 [classy] Computing new state
2023-07-02 10:34:42,551 [classy] Setting parameters: {'Omega_m': 0.36015791900005417, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:42,598 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.88331589515113}
2023-07-02 10:34:42,598 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:42,600 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.12462
2023-07-02 10:34:42,600 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4003632487112563, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:42,600 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:42,620 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.40806
2023-07-02 10:34:42,620 [model] Computed derived parameters: {}
2023-07-02 10:34:42,620 [model] Posterior to be computed for parameters {'Omega_m': 0.3458665924355705, 'b1': 0.4136453673454006}
2023-07-02 10:34:42,620 [prior] Evaluating prior at array([0.34586659, 0.41364537])
2023-07-02 10:34:42,620 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:42,620 [model] Got input parameters: {'Omega_m': 0.3458665924355705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4136453673454006, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:42,620 [classy] Got parameters {'Omega_m': 0.3458665924355705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:42,620 [classy] Re-using computed results
2023-07-02 10:34:42,620 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.42363122408656}
2023-07-02 10:34:42,620 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:42,620 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4136453673454006, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:42,620 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:42,640 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.27433
2023-07-02 10:34:42,640 [model] Computed derived parameters: {}
2023-07-02 10:34:42,640 [model] Posterior to be computed for parameters {'Omega_m': 0.3815199072723073, 'b1': 0.36322800279688966}
2023-07-02 10:34:42,640 [prior] Evaluating prior at array([0.38151991, 0.363228 ])
2023-07-02 10:34:42,640 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:42,640 [model] Got input parameters: {'Omega_m': 0.3815199072723073, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.36322800279688966, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:42,640 [classy] Got parameters {'Omega_m': 0.3815199072723073, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:42,640 [classy] Computing new state
2023-07-02 10:34:42,640 [classy] Setting parameters: {'Omega_m': 0.3815199072723073, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:42,686 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 139.6834397324104}
2023-07-02 10:34:42,686 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:42,688 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.248916
2023-07-02 10:34:42,688 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.36322800279688966, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:42,688 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:42,707 [fs_likelihood.fslikelihood] Computed log-likelihood = -16.5998
2023-07-02 10:34:42,707 [model] Computed derived parameters: {}
2023-07-02 10:34:42,708 [model] Posterior to be computed for parameters {'Omega_m': 0.3458665924355705, 'b1': 0.42088960539487486}
2023-07-02 10:34:42,708 [prior] Evaluating prior at array([0.34586659, 0.42088961])
2023-07-02 10:34:42,708 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:42,708 [model] Got input parameters: {'Omega_m': 0.3458665924355705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42088960539487486, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:42,708 [classy] Got parameters {'Omega_m': 0.3458665924355705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:42,708 [classy] Re-using computed results
2023-07-02 10:34:42,708 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.42363122408656}
2023-07-02 10:34:42,708 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:42,708 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42088960539487486, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:42,708 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:42,728 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.22678
2023-07-02 10:34:42,728 [model] Computed derived parameters: {}
2023-07-02 10:34:42,728 [mcmc] New sample, #794:
Omega_m:0.3458666, b1:0.425207
2023-07-02 10:34:42,729 [model] Posterior to be computed for parameters {'Omega_m': 0.3137597747715905, 'b1': 0.4767034441763654}
2023-07-02 10:34:42,729 [prior] Evaluating prior at array([0.31375977, 0.47670344])
2023-07-02 10:34:42,729 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:42,729 [model] Got input parameters: {'Omega_m': 0.3137597747715905, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4767034441763654, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:42,729 [classy] Got parameters {'Omega_m': 0.3137597747715905, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:42,729 [classy] Computing new state
2023-07-02 10:34:42,729 [classy] Setting parameters: {'Omega_m': 0.3137597747715905, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:42,775 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.10688291892384}
2023-07-02 10:34:42,775 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:42,777 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000301913
2023-07-02 10:34:42,777 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4767034441763654, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:42,777 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:42,797 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.15573
2023-07-02 10:34:42,797 [model] Computed derived parameters: {}
2023-07-02 10:34:42,797 [mcmc] New sample, #795:
Omega_m:0.3458666, b1:0.4208896
2023-07-02 10:34:42,797 [model] Posterior to be computed for parameters {'Omega_m': 0.3137597747715905, 'b1': 0.42204928489382776}
2023-07-02 10:34:42,797 [prior] Evaluating prior at array([0.31375977, 0.42204928])
2023-07-02 10:34:42,797 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:42,797 [model] Got input parameters: {'Omega_m': 0.3137597747715905, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42204928489382776, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:42,797 [classy] Got parameters {'Omega_m': 0.3137597747715905, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:42,797 [classy] Re-using computed results
2023-07-02 10:34:42,797 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.10688291892384}
2023-07-02 10:34:42,797 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:42,797 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42204928489382776, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:42,797 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:42,817 [fs_likelihood.fslikelihood] Computed log-likelihood = -13.1853
2023-07-02 10:34:42,817 [model] Computed derived parameters: {}
2023-07-02 10:34:42,817 [model] Posterior to be computed for parameters {'Omega_m': 0.3153874591131351, 'b1': 0.4738739108237639}
2023-07-02 10:34:42,817 [prior] Evaluating prior at array([0.31538746, 0.47387391])
2023-07-02 10:34:42,817 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:42,817 [model] Got input parameters: {'Omega_m': 0.3153874591131351, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4738739108237639, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:42,817 [classy] Got parameters {'Omega_m': 0.3153874591131351, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:42,817 [classy] Computing new state
2023-07-02 10:34:42,817 [classy] Setting parameters: {'Omega_m': 0.3153874591131351, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:42,864 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.91218104872976}
2023-07-02 10:34:42,864 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:42,865 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000715725
2023-07-02 10:34:42,865 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4738739108237639, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:42,865 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:42,885 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.18125
2023-07-02 10:34:42,886 [model] Computed derived parameters: {}
2023-07-02 10:34:42,886 [mcmc] New sample, #796:
Omega_m:0.3137598, b1:0.4767034
2023-07-02 10:34:42,886 [model] Posterior to be computed for parameters {'Omega_m': 0.3153874591131351, 'b1': 0.42379505715565974}
2023-07-02 10:34:42,886 [prior] Evaluating prior at array([0.31538746, 0.42379506])
2023-07-02 10:34:42,886 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:42,886 [model] Got input parameters: {'Omega_m': 0.3153874591131351, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42379505715565974, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:42,886 [classy] Got parameters {'Omega_m': 0.3153874591131351, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:42,886 [classy] Re-using computed results
2023-07-02 10:34:42,886 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.91218104872976}
2023-07-02 10:34:42,886 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:42,886 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42379505715565974, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:42,886 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:42,905 [fs_likelihood.fslikelihood] Computed log-likelihood = -11.4399
2023-07-02 10:34:42,906 [model] Computed derived parameters: {}
2023-07-02 10:34:42,906 [model] Posterior to be computed for parameters {'Omega_m': 0.3461063187541538, 'b1': 0.4204728700386298}
2023-07-02 10:34:42,906 [prior] Evaluating prior at array([0.34610632, 0.42047287])
2023-07-02 10:34:42,906 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:42,906 [model] Got input parameters: {'Omega_m': 0.3461063187541538, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4204728700386298, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:42,906 [classy] Got parameters {'Omega_m': 0.3461063187541538, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:42,906 [classy] Computing new state
2023-07-02 10:34:42,906 [classy] Setting parameters: {'Omega_m': 0.3461063187541538, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:42,955 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.39731779911975}
2023-07-02 10:34:42,955 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:42,957 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0641255
2023-07-02 10:34:42,957 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4204728700386298, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:42,957 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:42,978 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.29331
2023-07-02 10:34:42,978 [model] Computed derived parameters: {}
2023-07-02 10:34:42,978 [model] Posterior to be computed for parameters {'Omega_m': 0.3153874591131351, 'b1': 0.4942549780272488}
2023-07-02 10:34:42,978 [prior] Evaluating prior at array([0.31538746, 0.49425498])
2023-07-02 10:34:42,978 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:42,978 [model] Got input parameters: {'Omega_m': 0.3153874591131351, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4942549780272488, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:42,978 [classy] Got parameters {'Omega_m': 0.3153874591131351, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:42,978 [classy] Re-using computed results
2023-07-02 10:34:42,978 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.91218104872976}
2023-07-02 10:34:42,978 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:42,979 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4942549780272488, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:42,979 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:42,999 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.8486
2023-07-02 10:34:42,999 [model] Computed derived parameters: {}
2023-07-02 10:34:42,999 [mcmc] New sample, #797:
Omega_m:0.3153875, b1:0.4738739
2023-07-02 10:34:42,999 [model] Posterior to be computed for parameters {'Omega_m': 0.2356799079964429, 'b1': 0.6328169636545408}
2023-07-02 10:34:42,999 [prior] Evaluating prior at array([0.23567991, 0.63281696])
2023-07-02 10:34:43,000 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:43,000 [model] Got input parameters: {'Omega_m': 0.2356799079964429, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6328169636545408, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:43,000 [classy] Got parameters {'Omega_m': 0.2356799079964429, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:43,000 [classy] Computing new state
2023-07-02 10:34:43,000 [classy] Setting parameters: {'Omega_m': 0.2356799079964429, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:43,048 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 157.6618313408032}
2023-07-02 10:34:43,048 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:43,051 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.445091
2023-07-02 10:34:43,051 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6328169636545408, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:43,051 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:43,073 [fs_likelihood.fslikelihood] Computed log-likelihood = -46.7176
2023-07-02 10:34:43,073 [model] Computed derived parameters: {}
2023-07-02 10:34:43,073 [model] Posterior to be computed for parameters {'Omega_m': 0.3153874591131351, 'b1': 0.47374242746918743}
2023-07-02 10:34:43,073 [prior] Evaluating prior at array([0.31538746, 0.47374243])
2023-07-02 10:34:43,073 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:43,073 [model] Got input parameters: {'Omega_m': 0.3153874591131351, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47374242746918743, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:43,073 [classy] Got parameters {'Omega_m': 0.3153874591131351, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:43,073 [classy] Re-using computed results
2023-07-02 10:34:43,073 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.91218104872976}
2023-07-02 10:34:43,073 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:43,073 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47374242746918743, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:43,073 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:43,094 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.16363
2023-07-02 10:34:43,094 [model] Computed derived parameters: {}
2023-07-02 10:34:43,094 [model] Posterior to be computed for parameters {'Omega_m': 0.32631991305359587, 'b1': 0.4752502224608477}
2023-07-02 10:34:43,094 [prior] Evaluating prior at array([0.32631991, 0.47525022])
2023-07-02 10:34:43,095 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:43,095 [model] Got input parameters: {'Omega_m': 0.32631991305359587, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4752502224608477, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:43,095 [classy] Got parameters {'Omega_m': 0.32631991305359587, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:43,095 [classy] Computing new state
2023-07-02 10:34:43,095 [classy] Setting parameters: {'Omega_m': 0.32631991305359587, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:43,143 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.62727700823066}
2023-07-02 10:34:43,143 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:43,145 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0115487
2023-07-02 10:34:43,145 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4752502224608477, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:43,145 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:43,165 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.20597
2023-07-02 10:34:43,165 [model] Computed derived parameters: {}
2023-07-02 10:34:43,165 [model] Posterior to be computed for parameters {'Omega_m': 0.3153874591131351, 'b1': 0.48195540245663937}
2023-07-02 10:34:43,165 [prior] Evaluating prior at array([0.31538746, 0.4819554 ])
2023-07-02 10:34:43,165 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:43,165 [model] Got input parameters: {'Omega_m': 0.3153874591131351, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48195540245663937, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:43,165 [classy] Got parameters {'Omega_m': 0.3153874591131351, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:43,165 [classy] Re-using computed results
2023-07-02 10:34:43,166 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.91218104872976}
2023-07-02 10:34:43,166 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:43,166 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48195540245663937, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:43,166 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:43,186 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.09749
2023-07-02 10:34:43,186 [model] Computed derived parameters: {}
2023-07-02 10:34:43,186 [model] Posterior to be computed for parameters {'Omega_m': 0.31929377016042, 'b1': 0.4874643263561518}
2023-07-02 10:34:43,186 [prior] Evaluating prior at array([0.31929377, 0.48746433])
2023-07-02 10:34:43,186 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:43,186 [model] Got input parameters: {'Omega_m': 0.31929377016042, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4874643263561518, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:43,186 [classy] Got parameters {'Omega_m': 0.31929377016042, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:43,186 [classy] Computing new state
2023-07-02 10:34:43,186 [classy] Setting parameters: {'Omega_m': 0.31929377016042, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:43,233 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.44857471327862}
2023-07-02 10:34:43,233 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:43,235 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00299834
2023-07-02 10:34:43,235 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4874643263561518, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:43,235 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:43,255 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.76397
2023-07-02 10:34:43,255 [model] Computed derived parameters: {}
2023-07-02 10:34:43,255 [mcmc] New sample, #798:
Omega_m:0.3153875, b1:0.494255
2023-07-02 10:34:43,255 [model] Posterior to be computed for parameters {'Omega_m': 0.31929377016042, 'b1': 0.49814941208734426}
2023-07-02 10:34:43,255 [prior] Evaluating prior at array([0.31929377, 0.49814941])
2023-07-02 10:34:43,255 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:43,255 [model] Got input parameters: {'Omega_m': 0.31929377016042, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49814941208734426, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:43,255 [classy] Got parameters {'Omega_m': 0.31929377016042, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:43,256 [classy] Re-using computed results
2023-07-02 10:34:43,256 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.44857471327862}
2023-07-02 10:34:43,256 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:43,256 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49814941208734426, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:43,256 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:43,275 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.74854
2023-07-02 10:34:43,275 [model] Computed derived parameters: {}
2023-07-02 10:34:43,275 [mcmc] New sample, #799:
Omega_m:0.3192938, b1:0.4874643
2023-07-02 10:34:43,275 [model] Posterior to be computed for parameters {'Omega_m': 0.3453512456537857, 'b1': 0.4528516266929673}
2023-07-02 10:34:43,275 [prior] Evaluating prior at array([0.34535125, 0.45285163])
2023-07-02 10:34:43,275 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:43,275 [model] Got input parameters: {'Omega_m': 0.3453512456537857, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4528516266929673, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:43,275 [classy] Got parameters {'Omega_m': 0.3453512456537857, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:43,275 [classy] Computing new state
2023-07-02 10:34:43,275 [classy] Setting parameters: {'Omega_m': 0.3453512456537857, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:43,322 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.48025714747325}
2023-07-02 10:34:43,322 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:43,324 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.061395
2023-07-02 10:34:43,324 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4528516266929673, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:43,324 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:43,344 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.72606
2023-07-02 10:34:43,344 [model] Computed derived parameters: {}
2023-07-02 10:34:43,345 [model] Posterior to be computed for parameters {'Omega_m': 0.31929377016042, 'b1': 0.47447788549897574}
2023-07-02 10:34:43,345 [prior] Evaluating prior at array([0.31929377, 0.47447789])
2023-07-02 10:34:43,345 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:43,345 [model] Got input parameters: {'Omega_m': 0.31929377016042, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47447788549897574, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:43,345 [classy] Got parameters {'Omega_m': 0.31929377016042, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:43,345 [classy] Re-using computed results
2023-07-02 10:34:43,345 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.44857471327862}
2023-07-02 10:34:43,345 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:43,345 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47447788549897574, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:43,345 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:43,364 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.9652
2023-07-02 10:34:43,364 [model] Computed derived parameters: {}
2023-07-02 10:34:43,364 [model] Posterior to be computed for parameters {'Omega_m': 0.3338476446344413, 'b1': 0.4728492527242945}
2023-07-02 10:34:43,364 [prior] Evaluating prior at array([0.33384764, 0.47284925])
2023-07-02 10:34:43,365 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:43,365 [model] Got input parameters: {'Omega_m': 0.3338476446344413, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4728492527242945, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:43,365 [classy] Got parameters {'Omega_m': 0.3338476446344413, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:43,365 [classy] Computing new state
2023-07-02 10:34:43,365 [classy] Setting parameters: {'Omega_m': 0.3338476446344413, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:43,411 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.76481309330012}
2023-07-02 10:34:43,411 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:43,413 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0267682
2023-07-02 10:34:43,413 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4728492527242945, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:43,413 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:43,434 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.996145
2023-07-02 10:34:43,434 [model] Computed derived parameters: {}
2023-07-02 10:34:43,434 [model] Posterior to be computed for parameters {'Omega_m': 0.31929377016042, 'b1': 0.46539182933233414}
2023-07-02 10:34:43,434 [prior] Evaluating prior at array([0.31929377, 0.46539183])
2023-07-02 10:34:43,434 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:43,434 [model] Got input parameters: {'Omega_m': 0.31929377016042, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46539182933233414, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:43,434 [classy] Got parameters {'Omega_m': 0.31929377016042, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:43,434 [classy] Re-using computed results
2023-07-02 10:34:43,434 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.44857471327862}
2023-07-02 10:34:43,434 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:43,434 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46539182933233414, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:43,434 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:43,454 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.890601
2023-07-02 10:34:43,454 [model] Computed derived parameters: {}
2023-07-02 10:34:43,454 [model] Posterior to be computed for parameters {'Omega_m': 0.3265792281624715, 'b1': 0.4854845200811828}
2023-07-02 10:34:43,454 [prior] Evaluating prior at array([0.32657923, 0.48548452])
2023-07-02 10:34:43,454 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:43,454 [model] Got input parameters: {'Omega_m': 0.3265792281624715, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4854845200811828, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:43,454 [classy] Got parameters {'Omega_m': 0.3265792281624715, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:43,454 [classy] Computing new state
2023-07-02 10:34:43,454 [classy] Setting parameters: {'Omega_m': 0.3265792281624715, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:43,500 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.59726813422216}
2023-07-02 10:34:43,500 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:43,502 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0119706
2023-07-02 10:34:43,502 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4854845200811828, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:43,502 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:43,522 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.12857
2023-07-02 10:34:43,522 [model] Computed derived parameters: {}
2023-07-02 10:34:43,522 [mcmc] New sample, #800:
Omega_m:0.3192938, b1:0.4981494
2023-07-02 10:34:43,522 [mcmc] Learn + convergence test @ 800 samples accepted.
2023-07-02 10:34:43,522 [mcmc] Ready to check convergence and learn a new proposal covmat
2023-07-02 10:34:43,527 [mcmc] - Acceptance rate: 0.472
2023-07-02 10:34:43,527 [mcmc] - Condition number = 22.5773
2023-07-02 10:34:43,527 [mcmc] - Eigenvalues = array([0.00184236, 0.04159555])
2023-07-02 10:34:43,527 [mcmc] - Convergence of means: R-1 = 0.041596 after 640 accepted steps
2023-07-02 10:34:43,534 [mcmc] - normalized std's of bounds = array([[0.21469746, 0.24337169],
[0.19071008, 0.24074066]])
2023-07-02 10:34:43,535 [mcmc] - Convergence of bounds: R-1 = 0.243372 after 800 accepted steps
2023-07-02 10:34:43,535 [mcmc] - Updated covariance matrix of proposal pdf.
2023-07-02 10:34:43,535 [mcmc] array([[ 0.00010823, -0.00019247],
[-0.00019247, 0.00051802]])
2023-07-02 10:34:43,545 [mcmc] Dumped checkpoint and progress info, and current covmat.
2023-07-02 10:34:43,545 [model] Posterior to be computed for parameters {'Omega_m': 0.3265792281624715, 'b1': 0.46017549491572796}
2023-07-02 10:34:43,545 [prior] Evaluating prior at array([0.32657923, 0.46017549])
2023-07-02 10:34:43,546 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:43,546 [model] Got input parameters: {'Omega_m': 0.3265792281624715, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46017549491572796, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:43,546 [classy] Got parameters {'Omega_m': 0.3265792281624715, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:43,546 [classy] Re-using computed results
2023-07-02 10:34:43,546 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.59726813422216}
2023-07-02 10:34:43,546 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:43,546 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46017549491572796, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:43,546 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:43,566 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.24997
2023-07-02 10:34:43,566 [model] Computed derived parameters: {}
2023-07-02 10:34:43,566 [mcmc] New sample, #801:
Omega_m:0.3265792, b1:0.4854845
2023-07-02 10:34:43,566 [model] Posterior to be computed for parameters {'Omega_m': 0.3211735150038671, 'b1': 0.4697889634134423}
2023-07-02 10:34:43,566 [prior] Evaluating prior at array([0.32117352, 0.46978896])
2023-07-02 10:34:43,567 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:43,567 [model] Got input parameters: {'Omega_m': 0.3211735150038671, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4697889634134423, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:43,567 [classy] Got parameters {'Omega_m': 0.3211735150038671, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:43,567 [classy] Computing new state
2023-07-02 10:34:43,567 [classy] Setting parameters: {'Omega_m': 0.3211735150038671, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:43,614 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.2272802000452}
2023-07-02 10:34:43,614 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:43,616 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00473397
2023-07-02 10:34:43,616 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4697889634134423, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:43,616 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:43,637 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.7344
2023-07-02 10:34:43,637 [model] Computed derived parameters: {}
2023-07-02 10:34:43,637 [mcmc] New sample, #802:
Omega_m:0.3265792, b1:0.4601755
2023-07-02 10:34:43,637 [model] Posterior to be computed for parameters {'Omega_m': 0.3211735150038671, 'b1': 0.5178756627271432}
2023-07-02 10:34:43,637 [prior] Evaluating prior at array([0.32117352, 0.51787566])
2023-07-02 10:34:43,637 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:43,637 [model] Got input parameters: {'Omega_m': 0.3211735150038671, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5178756627271432, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:43,637 [classy] Got parameters {'Omega_m': 0.3211735150038671, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:43,637 [classy] Re-using computed results
2023-07-02 10:34:43,637 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.2272802000452}
2023-07-02 10:34:43,637 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:43,637 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5178756627271432, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:43,637 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:43,657 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.426808
2023-07-02 10:34:43,657 [model] Computed derived parameters: {}
2023-07-02 10:34:43,657 [model] Posterior to be computed for parameters {'Omega_m': 0.2987883390517092, 'b1': 0.5095985458899606}
2023-07-02 10:34:43,657 [prior] Evaluating prior at array([0.29878834, 0.50959855])
2023-07-02 10:34:43,658 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:43,658 [model] Got input parameters: {'Omega_m': 0.2987883390517092, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5095985458899606, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:43,658 [classy] Got parameters {'Omega_m': 0.2987883390517092, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:43,658 [classy] Computing new state
2023-07-02 10:34:43,658 [classy] Setting parameters: {'Omega_m': 0.2987883390517092, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:43,705 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.94087056930633}
2023-07-02 10:34:43,705 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:43,707 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0121083
2023-07-02 10:34:43,707 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5095985458899606, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:43,707 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:43,726 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.24688
2023-07-02 10:34:43,726 [model] Computed derived parameters: {}
2023-07-02 10:34:43,726 [model] Posterior to be computed for parameters {'Omega_m': 0.3211735150038671, 'b1': 0.403262490309104}
2023-07-02 10:34:43,727 [prior] Evaluating prior at array([0.32117352, 0.40326249])
2023-07-02 10:34:43,727 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:43,727 [model] Got input parameters: {'Omega_m': 0.3211735150038671, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.403262490309104, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:43,727 [classy] Got parameters {'Omega_m': 0.3211735150038671, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:43,727 [classy] Re-using computed results
2023-07-02 10:34:43,727 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.2272802000452}
2023-07-02 10:34:43,727 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:43,727 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.403262490309104, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:43,727 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:43,747 [fs_likelihood.fslikelihood] Computed log-likelihood = -15.5922
2023-07-02 10:34:43,747 [model] Computed derived parameters: {}
2023-07-02 10:34:43,748 [model] Posterior to be computed for parameters {'Omega_m': 0.3185501778092259, 'b1': 0.4744542811503672}
2023-07-02 10:34:43,748 [prior] Evaluating prior at array([0.31855018, 0.47445428])
2023-07-02 10:34:43,748 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:43,748 [model] Got input parameters: {'Omega_m': 0.3185501778092259, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4744542811503672, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:43,748 [classy] Got parameters {'Omega_m': 0.3185501778092259, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:43,748 [classy] Computing new state
2023-07-02 10:34:43,748 [classy] Setting parameters: {'Omega_m': 0.3185501778092259, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:43,794 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.53643702601312}
2023-07-02 10:34:43,794 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:43,796 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00242513
2023-07-02 10:34:43,796 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4744542811503672, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:43,796 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:43,815 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.8608
2023-07-02 10:34:43,815 [model] Computed derived parameters: {}
2023-07-02 10:34:43,816 [mcmc] New sample, #803:
Omega_m:0.3211735, b1:0.469789
2023-07-02 10:34:43,816 [model] Posterior to be computed for parameters {'Omega_m': 0.3185501778092259, 'b1': 0.44333947827431247}
2023-07-02 10:34:43,816 [prior] Evaluating prior at array([0.31855018, 0.44333948])
2023-07-02 10:34:43,816 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:43,816 [model] Got input parameters: {'Omega_m': 0.3185501778092259, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44333947827431247, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:43,816 [classy] Got parameters {'Omega_m': 0.3185501778092259, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:43,816 [classy] Re-using computed results
2023-07-02 10:34:43,816 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.53643702601312}
2023-07-02 10:34:43,816 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:43,816 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44333947827431247, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:43,816 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:43,835 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.70658
2023-07-02 10:34:43,835 [model] Computed derived parameters: {}
2023-07-02 10:34:43,835 [model] Posterior to be computed for parameters {'Omega_m': 0.32330564960230496, 'b1': 0.46599719566817394}
2023-07-02 10:34:43,835 [prior] Evaluating prior at array([0.32330565, 0.4659972 ])
2023-07-02 10:34:43,836 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:43,836 [model] Got input parameters: {'Omega_m': 0.32330564960230496, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46599719566817394, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:43,836 [classy] Got parameters {'Omega_m': 0.32330564960230496, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:43,836 [classy] Computing new state
2023-07-02 10:34:43,836 [classy] Setting parameters: {'Omega_m': 0.32330564960230496, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:43,882 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.97766565367994}
2023-07-02 10:34:43,882 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:43,884 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00719422
2023-07-02 10:34:43,884 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46599719566817394, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:43,884 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:43,904 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.57862
2023-07-02 10:34:43,904 [model] Computed derived parameters: {}
2023-07-02 10:34:43,904 [mcmc] New sample, #804:
Omega_m:0.3185502, b1:0.4744543
2023-07-02 10:34:43,904 [model] Posterior to be computed for parameters {'Omega_m': 0.32330564960230496, 'b1': 0.45960177027095306}
2023-07-02 10:34:43,904 [prior] Evaluating prior at array([0.32330565, 0.45960177])
2023-07-02 10:34:43,904 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:43,904 [model] Got input parameters: {'Omega_m': 0.32330564960230496, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45960177027095306, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:43,904 [classy] Got parameters {'Omega_m': 0.32330564960230496, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:43,904 [classy] Re-using computed results
2023-07-02 10:34:43,905 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.97766565367994}
2023-07-02 10:34:43,905 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:43,905 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45960177027095306, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:43,905 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:43,924 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.823947
2023-07-02 10:34:43,924 [model] Computed derived parameters: {}
2023-07-02 10:34:43,924 [model] Posterior to be computed for parameters {'Omega_m': 0.2804086928800967, 'b1': 0.5422847325753728}
2023-07-02 10:34:43,924 [prior] Evaluating prior at array([0.28040869, 0.54228473])
2023-07-02 10:34:43,924 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:43,924 [model] Got input parameters: {'Omega_m': 0.2804086928800967, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5422847325753728, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:43,924 [classy] Got parameters {'Omega_m': 0.2804086928800967, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:43,924 [classy] Computing new state
2023-07-02 10:34:43,924 [classy] Setting parameters: {'Omega_m': 0.2804086928800967, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:43,971 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.30552220515216}
2023-07-02 10:34:43,971 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:43,972 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0687083
2023-07-02 10:34:43,973 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5422847325753728, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:43,973 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:43,993 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.03853
2023-07-02 10:34:43,993 [model] Computed derived parameters: {}
2023-07-02 10:34:43,993 [model] Posterior to be computed for parameters {'Omega_m': 0.32330564960230496, 'b1': 0.4083034658192367}
2023-07-02 10:34:43,993 [prior] Evaluating prior at array([0.32330565, 0.40830347])
2023-07-02 10:34:43,993 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:43,993 [model] Got input parameters: {'Omega_m': 0.32330564960230496, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4083034658192367, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:43,993 [classy] Got parameters {'Omega_m': 0.32330564960230496, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:43,993 [classy] Re-using computed results
2023-07-02 10:34:43,993 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.97766565367994}
2023-07-02 10:34:43,993 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:43,993 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4083034658192367, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:43,993 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:44,012 [fs_likelihood.fslikelihood] Computed log-likelihood = -12.313
2023-07-02 10:34:44,012 [model] Computed derived parameters: {}
2023-07-02 10:34:44,013 [model] Posterior to be computed for parameters {'Omega_m': 0.2787236575280344, 'b1': 0.5452813833038342}
2023-07-02 10:34:44,013 [prior] Evaluating prior at array([0.27872366, 0.54528138])
2023-07-02 10:34:44,013 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:44,013 [model] Got input parameters: {'Omega_m': 0.2787236575280344, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5452813833038342, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:44,013 [classy] Got parameters {'Omega_m': 0.2787236575280344, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:44,013 [classy] Computing new state
2023-07-02 10:34:44,013 [classy] Setting parameters: {'Omega_m': 0.2787236575280344, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:44,059 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.5289474096781}
2023-07-02 10:34:44,059 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:44,061 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0764357
2023-07-02 10:34:44,061 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5452813833038342, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:44,061 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:44,081 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.88205
2023-07-02 10:34:44,081 [model] Computed derived parameters: {}
2023-07-02 10:34:44,081 [model] Posterior to be computed for parameters {'Omega_m': 0.32330564960230496, 'b1': 0.4570735419698748}
2023-07-02 10:34:44,081 [prior] Evaluating prior at array([0.32330565, 0.45707354])
2023-07-02 10:34:44,081 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:44,081 [model] Got input parameters: {'Omega_m': 0.32330564960230496, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4570735419698748, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:44,081 [classy] Got parameters {'Omega_m': 0.32330564960230496, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:44,081 [classy] Re-using computed results
2023-07-02 10:34:44,081 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.97766565367994}
2023-07-02 10:34:44,081 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:44,082 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4570735419698748, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:44,082 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:44,102 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.46876
2023-07-02 10:34:44,102 [model] Computed derived parameters: {}
2023-07-02 10:34:44,102 [mcmc] New sample, #805:
Omega_m:0.3233056, b1:0.4659972
2023-07-02 10:34:44,102 [model] Posterior to be computed for parameters {'Omega_m': 0.31935010774114214, 'b1': 0.46410803972400577}
2023-07-02 10:34:44,102 [prior] Evaluating prior at array([0.31935011, 0.46410804])
2023-07-02 10:34:44,102 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:44,102 [model] Got input parameters: {'Omega_m': 0.31935010774114214, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46410803972400577, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:44,102 [classy] Got parameters {'Omega_m': 0.31935010774114214, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:44,102 [classy] Computing new state
2023-07-02 10:34:44,102 [classy] Setting parameters: {'Omega_m': 0.31935010774114214, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:44,151 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.44192798369875}
2023-07-02 10:34:44,151 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:44,153 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00304435
2023-07-02 10:34:44,153 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46410803972400577, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:44,153 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:44,172 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.71775
2023-07-02 10:34:44,173 [model] Computed derived parameters: {}
2023-07-02 10:34:44,173 [mcmc] New sample, #806:
Omega_m:0.3233056, b1:0.4570735
2023-07-02 10:34:44,173 [model] Posterior to be computed for parameters {'Omega_m': 0.31935010774114214, 'b1': 0.400960577124302}
2023-07-02 10:34:44,173 [prior] Evaluating prior at array([0.31935011, 0.40096058])
2023-07-02 10:34:44,173 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:44,173 [model] Got input parameters: {'Omega_m': 0.31935010774114214, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.400960577124302, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:44,173 [classy] Got parameters {'Omega_m': 0.31935010774114214, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:44,173 [classy] Re-using computed results
2023-07-02 10:34:44,173 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.44192798369875}
2023-07-02 10:34:44,173 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:44,173 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.400960577124302, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:44,173 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:44,193 [fs_likelihood.fslikelihood] Computed log-likelihood = -17.8106
2023-07-02 10:34:44,193 [model] Computed derived parameters: {}
2023-07-02 10:34:44,194 [model] Posterior to be computed for parameters {'Omega_m': 0.30051770302265146, 'b1': 0.49759940787202595}
2023-07-02 10:34:44,194 [prior] Evaluating prior at array([0.3005177 , 0.49759941])
2023-07-02 10:34:44,194 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:44,194 [model] Got input parameters: {'Omega_m': 0.30051770302265146, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49759940787202595, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:44,194 [classy] Got parameters {'Omega_m': 0.30051770302265146, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:44,194 [classy] Computing new state
2023-07-02 10:34:44,194 [classy] Setting parameters: {'Omega_m': 0.30051770302265146, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:44,240 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.72492975341956}
2023-07-02 10:34:44,240 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:44,242 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00925096
2023-07-02 10:34:44,242 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49759940787202595, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:44,242 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:44,262 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.538344
2023-07-02 10:34:44,262 [model] Computed derived parameters: {}
2023-07-02 10:34:44,262 [model] Posterior to be computed for parameters {'Omega_m': 0.31935010774114214, 'b1': 0.4670020740648544}
2023-07-02 10:34:44,262 [prior] Evaluating prior at array([0.31935011, 0.46700207])
2023-07-02 10:34:44,262 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:44,262 [model] Got input parameters: {'Omega_m': 0.31935010774114214, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4670020740648544, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:44,262 [classy] Got parameters {'Omega_m': 0.31935010774114214, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:44,262 [classy] Re-using computed results
2023-07-02 10:34:44,262 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.44192798369875}
2023-07-02 10:34:44,262 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:44,262 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4670020740648544, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:44,262 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:44,281 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.12229
2023-07-02 10:34:44,282 [model] Computed derived parameters: {}
2023-07-02 10:34:44,282 [mcmc] New sample, #807:
Omega_m:0.3193501, b1:0.464108
2023-07-02 10:34:44,282 [model] Posterior to be computed for parameters {'Omega_m': 0.3384871190541839, 'b1': 0.4329689964670364}
2023-07-02 10:34:44,282 [prior] Evaluating prior at array([0.33848712, 0.432969 ])
2023-07-02 10:34:44,282 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:44,282 [model] Got input parameters: {'Omega_m': 0.3384871190541839, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4329689964670364, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:44,282 [classy] Got parameters {'Omega_m': 0.3384871190541839, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:44,282 [classy] Computing new state
2023-07-02 10:34:44,282 [classy] Setting parameters: {'Omega_m': 0.3384871190541839, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:44,328 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.24198431157012}
2023-07-02 10:34:44,328 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:44,330 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0391273
2023-07-02 10:34:44,330 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4329689964670364, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:44,330 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:44,351 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.49366
2023-07-02 10:34:44,351 [model] Computed derived parameters: {}
2023-07-02 10:34:44,351 [model] Posterior to be computed for parameters {'Omega_m': 0.31935010774114214, 'b1': 0.4822868164429757}
2023-07-02 10:34:44,351 [prior] Evaluating prior at array([0.31935011, 0.48228682])
2023-07-02 10:34:44,351 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:44,351 [model] Got input parameters: {'Omega_m': 0.31935010774114214, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4822868164429757, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:44,351 [classy] Got parameters {'Omega_m': 0.31935010774114214, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:44,351 [classy] Re-using computed results
2023-07-02 10:34:44,352 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.44192798369875}
2023-07-02 10:34:44,352 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:44,352 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4822868164429757, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:44,352 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:44,371 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.55431
2023-07-02 10:34:44,371 [model] Computed derived parameters: {}
2023-07-02 10:34:44,371 [mcmc] New sample, #808:
Omega_m:0.3193501, b1:0.4670021
2023-07-02 10:34:44,371 [model] Posterior to be computed for parameters {'Omega_m': 0.31751122942987536, 'b1': 0.48555706001636156}
2023-07-02 10:34:44,371 [prior] Evaluating prior at array([0.31751123, 0.48555706])
2023-07-02 10:34:44,371 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:44,371 [model] Got input parameters: {'Omega_m': 0.31751122942987536, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48555706001636156, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:44,371 [classy] Got parameters {'Omega_m': 0.31751122942987536, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:44,371 [classy] Computing new state
2023-07-02 10:34:44,371 [classy] Setting parameters: {'Omega_m': 0.31751122942987536, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:44,417 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.65950154047135}
2023-07-02 10:34:44,418 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:44,419 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00173292
2023-07-02 10:34:44,419 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48555706001636156, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:44,419 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:44,439 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.61673
2023-07-02 10:34:44,439 [model] Computed derived parameters: {}
2023-07-02 10:34:44,439 [mcmc] New sample, #809:
Omega_m:0.3193501, b1:0.4822868
2023-07-02 10:34:44,439 [model] Posterior to be computed for parameters {'Omega_m': 0.31751122942987536, 'b1': 0.49361526932882077}
2023-07-02 10:34:44,439 [prior] Evaluating prior at array([0.31751123, 0.49361527])
2023-07-02 10:34:44,439 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:44,439 [model] Got input parameters: {'Omega_m': 0.31751122942987536, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49361526932882077, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:44,439 [classy] Got parameters {'Omega_m': 0.31751122942987536, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:44,439 [classy] Re-using computed results
2023-07-02 10:34:44,439 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.65950154047135}
2023-07-02 10:34:44,439 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:44,439 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49361526932882077, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:44,439 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:44,460 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.88403
2023-07-02 10:34:44,460 [model] Computed derived parameters: {}
2023-07-02 10:34:44,460 [mcmc] New sample, #810:
Omega_m:0.3175112, b1:0.4855571
2023-07-02 10:34:44,460 [model] Posterior to be computed for parameters {'Omega_m': 0.321725000739603, 'b1': 0.4861215387970482}
2023-07-02 10:34:44,460 [prior] Evaluating prior at array([0.321725 , 0.48612154])
2023-07-02 10:34:44,460 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:44,460 [model] Got input parameters: {'Omega_m': 0.321725000739603, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4861215387970482, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:44,460 [classy] Got parameters {'Omega_m': 0.321725000739603, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:44,460 [classy] Computing new state
2023-07-02 10:34:44,460 [classy] Setting parameters: {'Omega_m': 0.321725000739603, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:44,506 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.16257601232937}
2023-07-02 10:34:44,507 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:44,508 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0053205
2023-07-02 10:34:44,508 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4861215387970482, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:44,509 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:44,528 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.68221
2023-07-02 10:34:44,528 [model] Computed derived parameters: {}
2023-07-02 10:34:44,528 [mcmc] New sample, #811:
Omega_m:0.3175112, b1:0.4936153
2023-07-02 10:34:44,528 [model] Posterior to be computed for parameters {'Omega_m': 0.321725000739603, 'b1': 0.5452725187805577}
2023-07-02 10:34:44,528 [prior] Evaluating prior at array([0.321725 , 0.54527252])
2023-07-02 10:34:44,528 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:44,528 [model] Got input parameters: {'Omega_m': 0.321725000739603, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5452725187805577, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:44,528 [classy] Got parameters {'Omega_m': 0.321725000739603, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:44,528 [classy] Re-using computed results
2023-07-02 10:34:44,528 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.16257601232937}
2023-07-02 10:34:44,528 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:44,528 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5452725187805577, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:44,528 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:44,549 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.68054
2023-07-02 10:34:44,549 [model] Computed derived parameters: {}
2023-07-02 10:34:44,549 [model] Posterior to be computed for parameters {'Omega_m': 0.3339480319069712, 'b1': 0.46438421725843904}
2023-07-02 10:34:44,549 [prior] Evaluating prior at array([0.33394803, 0.46438422])
2023-07-02 10:34:44,549 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:44,549 [model] Got input parameters: {'Omega_m': 0.3339480319069712, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46438421725843904, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:44,549 [classy] Got parameters {'Omega_m': 0.3339480319069712, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:44,549 [classy] Computing new state
2023-07-02 10:34:44,549 [classy] Setting parameters: {'Omega_m': 0.3339480319069712, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:44,595 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.75342971210551}
2023-07-02 10:34:44,595 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:44,597 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0270121
2023-07-02 10:34:44,597 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46438421725843904, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:44,597 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:44,617 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.09249
2023-07-02 10:34:44,617 [model] Computed derived parameters: {}
2023-07-02 10:34:44,617 [model] Posterior to be computed for parameters {'Omega_m': 0.321725000739603, 'b1': 0.495136032557442}
2023-07-02 10:34:44,617 [prior] Evaluating prior at array([0.321725 , 0.49513603])
2023-07-02 10:34:44,617 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:44,618 [model] Got input parameters: {'Omega_m': 0.321725000739603, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.495136032557442, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:44,618 [classy] Got parameters {'Omega_m': 0.321725000739603, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:44,618 [classy] Re-using computed results
2023-07-02 10:34:44,618 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.16257601232937}
2023-07-02 10:34:44,618 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:44,618 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.495136032557442, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:44,618 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:44,639 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.55972
2023-07-02 10:34:44,639 [model] Computed derived parameters: {}
2023-07-02 10:34:44,639 [mcmc] New sample, #812:
Omega_m:0.321725, b1:0.4861215
2023-07-02 10:34:44,639 [model] Posterior to be computed for parameters {'Omega_m': 0.31738083303731285, 'b1': 0.5028616587846272}
2023-07-02 10:34:44,639 [prior] Evaluating prior at array([0.31738083, 0.50286166])
2023-07-02 10:34:44,639 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:44,639 [model] Got input parameters: {'Omega_m': 0.31738083303731285, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5028616587846272, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:44,639 [classy] Got parameters {'Omega_m': 0.31738083303731285, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:44,639 [classy] Computing new state
2023-07-02 10:34:44,639 [classy] Setting parameters: {'Omega_m': 0.31738083303731285, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:44,689 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.6749739503329}
2023-07-02 10:34:44,689 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:44,691 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00165501
2023-07-02 10:34:44,691 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5028616587846272, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:44,691 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:44,711 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.77292
2023-07-02 10:34:44,711 [model] Computed derived parameters: {}
2023-07-02 10:34:44,711 [mcmc] New sample, #813:
Omega_m:0.321725, b1:0.495136
2023-07-02 10:34:44,712 [model] Posterior to be computed for parameters {'Omega_m': 0.31738083303731285, 'b1': 0.4518097602518478}
2023-07-02 10:34:44,712 [prior] Evaluating prior at array([0.31738083, 0.45180976])
2023-07-02 10:34:44,712 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:44,712 [model] Got input parameters: {'Omega_m': 0.31738083303731285, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4518097602518478, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:44,712 [classy] Got parameters {'Omega_m': 0.31738083303731285, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:44,712 [classy] Re-using computed results
2023-07-02 10:34:44,712 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.6749739503329}
2023-07-02 10:34:44,712 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:44,712 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4518097602518478, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:44,712 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:44,732 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.15174
2023-07-02 10:34:44,732 [model] Computed derived parameters: {}
2023-07-02 10:34:44,732 [model] Posterior to be computed for parameters {'Omega_m': 0.31252554661154325, 'b1': 0.511496253653432}
2023-07-02 10:34:44,732 [prior] Evaluating prior at array([0.31252555, 0.51149625])
2023-07-02 10:34:44,732 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:44,732 [model] Got input parameters: {'Omega_m': 0.31252554661154325, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.511496253653432, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:44,732 [classy] Got parameters {'Omega_m': 0.31252554661154325, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:44,733 [classy] Computing new state
2023-07-02 10:34:44,733 [classy] Setting parameters: {'Omega_m': 0.31252554661154325, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:44,782 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.25512583633224}
2023-07-02 10:34:44,782 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:44,784 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000202477
2023-07-02 10:34:44,784 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.511496253653432, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:44,784 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:44,804 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.76639
2023-07-02 10:34:44,804 [model] Computed derived parameters: {}
2023-07-02 10:34:44,804 [mcmc] New sample, #814:
Omega_m:0.3173808, b1:0.5028617
2023-07-02 10:34:44,804 [model] Posterior to be computed for parameters {'Omega_m': 0.31252554661154325, 'b1': 0.5460347698825926}
2023-07-02 10:34:44,804 [prior] Evaluating prior at array([0.31252555, 0.54603477])
2023-07-02 10:34:44,805 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:44,805 [model] Got input parameters: {'Omega_m': 0.31252554661154325, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5460347698825926, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:44,805 [classy] Got parameters {'Omega_m': 0.31252554661154325, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:44,805 [classy] Re-using computed results
2023-07-02 10:34:44,805 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.25512583633224}
2023-07-02 10:34:44,805 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:44,805 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5460347698825926, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:44,805 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:44,824 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.86886
2023-07-02 10:34:44,824 [model] Computed derived parameters: {}
2023-07-02 10:34:44,825 [model] Posterior to be computed for parameters {'Omega_m': 0.35190808623443864, 'b1': 0.4414587224496056}
2023-07-02 10:34:44,825 [prior] Evaluating prior at array([0.35190809, 0.44145872])
2023-07-02 10:34:44,825 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:44,825 [model] Got input parameters: {'Omega_m': 0.35190808623443864, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4414587224496056, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:44,825 [classy] Got parameters {'Omega_m': 0.35190808623443864, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:44,825 [classy] Computing new state
2023-07-02 10:34:44,825 [classy] Setting parameters: {'Omega_m': 0.35190808623443864, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:44,872 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.76549322293175}
2023-07-02 10:34:44,872 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:44,874 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0869104
2023-07-02 10:34:44,874 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4414587224496056, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:44,874 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:44,893 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.72824
2023-07-02 10:34:44,893 [model] Computed derived parameters: {}
2023-07-02 10:34:44,893 [model] Posterior to be computed for parameters {'Omega_m': 0.31252554661154325, 'b1': 0.5678910905830066}
2023-07-02 10:34:44,893 [prior] Evaluating prior at array([0.31252555, 0.56789109])
2023-07-02 10:34:44,893 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:44,894 [model] Got input parameters: {'Omega_m': 0.31252554661154325, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5678910905830066, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:44,894 [classy] Got parameters {'Omega_m': 0.31252554661154325, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:44,894 [classy] Re-using computed results
2023-07-02 10:34:44,894 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.25512583633224}
2023-07-02 10:34:44,894 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:44,894 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5678910905830066, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:44,894 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:44,914 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.49612
2023-07-02 10:34:44,914 [model] Computed derived parameters: {}
2023-07-02 10:34:44,914 [model] Posterior to be computed for parameters {'Omega_m': 0.2527700807802294, 'b1': 0.6177648016656777}
2023-07-02 10:34:44,914 [prior] Evaluating prior at array([0.25277008, 0.6177648 ])
2023-07-02 10:34:44,914 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:44,914 [model] Got input parameters: {'Omega_m': 0.2527700807802294, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6177648016656777, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:44,914 [classy] Got parameters {'Omega_m': 0.2527700807802294, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:44,914 [classy] Computing new state
2023-07-02 10:34:44,914 [classy] Setting parameters: {'Omega_m': 0.2527700807802294, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:44,961 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 155.12351889071076}
2023-07-02 10:34:44,961 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:44,963 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.256257
2023-07-02 10:34:44,963 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6177648016656777, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:44,963 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:44,982 [fs_likelihood.fslikelihood] Computed log-likelihood = -25.5657
2023-07-02 10:34:44,982 [model] Computed derived parameters: {}
2023-07-02 10:34:44,983 [model] Posterior to be computed for parameters {'Omega_m': 0.31252554661154325, 'b1': 0.4693947894357663}
2023-07-02 10:34:44,983 [prior] Evaluating prior at array([0.31252555, 0.46939479])
2023-07-02 10:34:44,983 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:44,983 [model] Got input parameters: {'Omega_m': 0.31252554661154325, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4693947894357663, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:44,983 [classy] Got parameters {'Omega_m': 0.31252554661154325, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:44,983 [classy] Re-using computed results
2023-07-02 10:34:44,983 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.25512583633224}
2023-07-02 10:34:44,983 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:44,983 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4693947894357663, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:44,983 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:45,002 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.37446
2023-07-02 10:34:45,002 [model] Computed derived parameters: {}
2023-07-02 10:34:45,002 [model] Posterior to be computed for parameters {'Omega_m': 0.32048764195944174, 'b1': 0.4973365395589126}
2023-07-02 10:34:45,002 [prior] Evaluating prior at array([0.32048764, 0.49733654])
2023-07-02 10:34:45,003 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:45,003 [model] Got input parameters: {'Omega_m': 0.32048764195944174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4973365395589126, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:45,003 [classy] Got parameters {'Omega_m': 0.32048764195944174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:45,003 [classy] Computing new state
2023-07-02 10:34:45,003 [classy] Setting parameters: {'Omega_m': 0.32048764195944174, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:45,049 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.30789266124245}
2023-07-02 10:34:45,049 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:45,051 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00405327
2023-07-02 10:34:45,051 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4973365395589126, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:45,051 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:45,071 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.6408
2023-07-02 10:34:45,071 [model] Computed derived parameters: {}
2023-07-02 10:34:45,071 [mcmc] New sample, #815:
Omega_m:0.3125255, b1:0.5114963
2023-07-02 10:34:45,071 [model] Posterior to be computed for parameters {'Omega_m': 0.32048764195944174, 'b1': 0.47377498629139825}
2023-07-02 10:34:45,071 [prior] Evaluating prior at array([0.32048764, 0.47377499])
2023-07-02 10:34:45,072 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:45,072 [model] Got input parameters: {'Omega_m': 0.32048764195944174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47377498629139825, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:45,072 [classy] Got parameters {'Omega_m': 0.32048764195944174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:45,072 [classy] Re-using computed results
2023-07-02 10:34:45,072 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.30789266124245}
2023-07-02 10:34:45,072 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:45,072 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47377498629139825, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:45,072 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:45,092 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.03701
2023-07-02 10:34:45,092 [model] Computed derived parameters: {}
2023-07-02 10:34:45,092 [mcmc] New sample, #816:
Omega_m:0.3204876, b1:0.4973365
2023-07-02 10:34:45,092 [model] Posterior to be computed for parameters {'Omega_m': 0.33952668949190945, 'b1': 0.4399161265425179}
2023-07-02 10:34:45,093 [prior] Evaluating prior at array([0.33952669, 0.43991613])
2023-07-02 10:34:45,093 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:45,093 [model] Got input parameters: {'Omega_m': 0.33952668949190945, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4399161265425179, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:45,093 [classy] Got parameters {'Omega_m': 0.33952668949190945, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:45,093 [classy] Computing new state
2023-07-02 10:34:45,093 [classy] Setting parameters: {'Omega_m': 0.33952668949190945, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:45,141 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.12572477990747}
2023-07-02 10:34:45,141 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:45,143 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0421985
2023-07-02 10:34:45,144 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4399161265425179, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:45,144 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:45,164 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.772138
2023-07-02 10:34:45,164 [model] Computed derived parameters: {}
2023-07-02 10:34:45,164 [model] Posterior to be computed for parameters {'Omega_m': 0.32048764195944174, 'b1': 0.4136859348999085}
2023-07-02 10:34:45,164 [prior] Evaluating prior at array([0.32048764, 0.41368593])
2023-07-02 10:34:45,164 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:45,164 [model] Got input parameters: {'Omega_m': 0.32048764195944174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4136859348999085, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:45,164 [classy] Got parameters {'Omega_m': 0.32048764195944174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:45,164 [classy] Re-using computed results
2023-07-02 10:34:45,164 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.30789266124245}
2023-07-02 10:34:45,164 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:45,164 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4136859348999085, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:45,164 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:45,184 [fs_likelihood.fslikelihood] Computed log-likelihood = -11.9729
2023-07-02 10:34:45,184 [model] Computed derived parameters: {}
2023-07-02 10:34:45,184 [model] Posterior to be computed for parameters {'Omega_m': 0.3305533320724319, 'b1': 0.45587425941783843}
2023-07-02 10:34:45,184 [prior] Evaluating prior at array([0.33055333, 0.45587426])
2023-07-02 10:34:45,184 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:45,184 [model] Got input parameters: {'Omega_m': 0.3305533320724319, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45587425941783843, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:45,184 [classy] Got parameters {'Omega_m': 0.3305533320724319, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:45,184 [classy] Computing new state
2023-07-02 10:34:45,184 [classy] Setting parameters: {'Omega_m': 0.3305533320724319, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:45,231 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.1400474048332}
2023-07-02 10:34:45,231 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:45,233 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0193583
2023-07-02 10:34:45,233 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45587425941783843, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:45,233 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:45,252 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.971141
2023-07-02 10:34:45,252 [model] Computed derived parameters: {}
2023-07-02 10:34:45,253 [model] Posterior to be computed for parameters {'Omega_m': 0.32048764195944174, 'b1': 0.4989240005776111}
2023-07-02 10:34:45,253 [prior] Evaluating prior at array([0.32048764, 0.498924 ])
2023-07-02 10:34:45,253 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:45,253 [model] Got input parameters: {'Omega_m': 0.32048764195944174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4989240005776111, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:45,253 [classy] Got parameters {'Omega_m': 0.32048764195944174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:45,253 [classy] Re-using computed results
2023-07-02 10:34:45,253 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.30789266124245}
2023-07-02 10:34:45,253 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:45,253 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4989240005776111, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:45,253 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:45,273 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.57341
2023-07-02 10:34:45,273 [model] Computed derived parameters: {}
2023-07-02 10:34:45,273 [mcmc] New sample, #817:
Omega_m:0.3204876, b1:0.473775
2023-07-02 10:34:45,273 [model] Posterior to be computed for parameters {'Omega_m': 0.3110468065852951, 'b1': 0.5157134917693519}
2023-07-02 10:34:45,274 [prior] Evaluating prior at array([0.31104681, 0.51571349])
2023-07-02 10:34:45,274 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:45,274 [model] Got input parameters: {'Omega_m': 0.3110468065852951, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5157134917693519, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:45,274 [classy] Got parameters {'Omega_m': 0.3110468065852951, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:45,274 [classy] Computing new state
2023-07-02 10:34:45,274 [classy] Setting parameters: {'Omega_m': 0.3110468065852951, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:45,321 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.43341770905127}
2023-07-02 10:34:45,321 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:45,323 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000329491
2023-07-02 10:34:45,323 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5157134917693519, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:45,323 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:45,343 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.64694
2023-07-02 10:34:45,344 [model] Computed derived parameters: {}
2023-07-02 10:34:45,344 [mcmc] New sample, #818:
Omega_m:0.3204876, b1:0.498924
2023-07-02 10:34:45,344 [model] Posterior to be computed for parameters {'Omega_m': 0.3110468065852951, 'b1': 0.503626689582094}
2023-07-02 10:34:45,344 [prior] Evaluating prior at array([0.31104681, 0.50362669])
2023-07-02 10:34:45,344 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:45,344 [model] Got input parameters: {'Omega_m': 0.3110468065852951, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.503626689582094, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:45,344 [classy] Got parameters {'Omega_m': 0.3110468065852951, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:45,344 [classy] Re-using computed results
2023-07-02 10:34:45,344 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.43341770905127}
2023-07-02 10:34:45,344 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:45,344 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.503626689582094, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:45,344 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:45,366 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.78775
2023-07-02 10:34:45,366 [model] Computed derived parameters: {}
2023-07-02 10:34:45,366 [mcmc] New sample, #819:
Omega_m:0.3110468, b1:0.5157135
2023-07-02 10:34:45,366 [model] Posterior to be computed for parameters {'Omega_m': 0.28929336299207714, 'b1': 0.5423128052830974}
2023-07-02 10:34:45,366 [prior] Evaluating prior at array([0.28929336, 0.54231281])
2023-07-02 10:34:45,366 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:45,366 [model] Got input parameters: {'Omega_m': 0.28929336299207714, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5423128052830974, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:45,366 [classy] Got parameters {'Omega_m': 0.28929336299207714, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:45,367 [classy] Computing new state
2023-07-02 10:34:45,367 [classy] Setting parameters: {'Omega_m': 0.28929336299207714, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:45,413 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.1462047965422}
2023-07-02 10:34:45,413 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:45,415 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.035186
2023-07-02 10:34:45,415 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5423128052830974, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:45,415 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:45,436 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.33468
2023-07-02 10:34:45,436 [model] Computed derived parameters: {}
2023-07-02 10:34:45,436 [model] Posterior to be computed for parameters {'Omega_m': 0.3110468065852951, 'b1': 0.5388189108731091}
2023-07-02 10:34:45,436 [prior] Evaluating prior at array([0.31104681, 0.53881891])
2023-07-02 10:34:45,436 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:45,436 [model] Got input parameters: {'Omega_m': 0.3110468065852951, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5388189108731091, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:45,436 [classy] Got parameters {'Omega_m': 0.3110468065852951, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:45,436 [classy] Re-using computed results
2023-07-02 10:34:45,436 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.43341770905127}
2023-07-02 10:34:45,436 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:45,436 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5388189108731091, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:45,436 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:45,456 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.115236
2023-07-02 10:34:45,456 [model] Computed derived parameters: {}
2023-07-02 10:34:45,456 [model] Posterior to be computed for parameters {'Omega_m': 0.3204636799915169, 'b1': 0.4868798121245692}
2023-07-02 10:34:45,456 [prior] Evaluating prior at array([0.32046368, 0.48687981])
2023-07-02 10:34:45,456 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:45,456 [model] Got input parameters: {'Omega_m': 0.3204636799915169, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4868798121245692, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:45,456 [classy] Got parameters {'Omega_m': 0.3204636799915169, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:45,456 [classy] Computing new state
2023-07-02 10:34:45,456 [classy] Setting parameters: {'Omega_m': 0.3204636799915169, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:45,503 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.3107100794703}
2023-07-02 10:34:45,503 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:45,505 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00403051
2023-07-02 10:34:45,505 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4868798121245692, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:45,505 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:45,525 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.73984
2023-07-02 10:34:45,525 [model] Computed derived parameters: {}
2023-07-02 10:34:45,525 [mcmc] New sample, #820:
Omega_m:0.3110468, b1:0.5036267
2023-07-02 10:34:45,525 [model] Posterior to be computed for parameters {'Omega_m': 0.3204636799915169, 'b1': 0.5135692831210197}
2023-07-02 10:34:45,525 [prior] Evaluating prior at array([0.32046368, 0.51356928])
2023-07-02 10:34:45,526 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:45,526 [model] Got input parameters: {'Omega_m': 0.3204636799915169, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5135692831210197, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:45,526 [classy] Got parameters {'Omega_m': 0.3204636799915169, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:45,526 [classy] Re-using computed results
2023-07-02 10:34:45,526 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.3107100794703}
2023-07-02 10:34:45,526 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:45,526 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5135692831210197, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:45,526 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:45,546 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.2892
2023-07-02 10:34:45,546 [model] Computed derived parameters: {}
2023-07-02 10:34:45,547 [model] Posterior to be computed for parameters {'Omega_m': 0.3390098003316239, 'b1': 0.45389756937263087}
2023-07-02 10:34:45,547 [prior] Evaluating prior at array([0.3390098 , 0.45389757])
2023-07-02 10:34:45,547 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:45,547 [model] Got input parameters: {'Omega_m': 0.3390098003316239, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45389756937263087, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:45,547 [classy] Got parameters {'Omega_m': 0.3390098003316239, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:45,547 [classy] Computing new state
2023-07-02 10:34:45,547 [classy] Setting parameters: {'Omega_m': 0.3390098003316239, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:45,594 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.18349014347302}
2023-07-02 10:34:45,594 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:45,596 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0406578
2023-07-02 10:34:45,596 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45389756937263087, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:45,596 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:45,616 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.0190102
2023-07-02 10:34:45,616 [model] Computed derived parameters: {}
2023-07-02 10:34:45,616 [model] Posterior to be computed for parameters {'Omega_m': 0.3204636799915169, 'b1': 0.48218086538620747}
2023-07-02 10:34:45,616 [prior] Evaluating prior at array([0.32046368, 0.48218087])
2023-07-02 10:34:45,616 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:45,616 [model] Got input parameters: {'Omega_m': 0.3204636799915169, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48218086538620747, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:45,616 [classy] Got parameters {'Omega_m': 0.3204636799915169, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:45,616 [classy] Re-using computed results
2023-07-02 10:34:45,616 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.3107100794703}
2023-07-02 10:34:45,616 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:45,616 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48218086538620747, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:45,616 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:45,636 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.59095
2023-07-02 10:34:45,636 [model] Computed derived parameters: {}
2023-07-02 10:34:45,636 [mcmc] New sample, #821:
Omega_m:0.3204637, b1:0.4868798
2023-07-02 10:34:45,636 [model] Posterior to be computed for parameters {'Omega_m': 0.3065134691333626, 'b1': 0.5069897867415467}
2023-07-02 10:34:45,636 [prior] Evaluating prior at array([0.30651347, 0.50698979])
2023-07-02 10:34:45,636 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:45,636 [model] Got input parameters: {'Omega_m': 0.3065134691333626, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5069897867415467, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:45,636 [classy] Got parameters {'Omega_m': 0.3065134691333626, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:45,636 [classy] Computing new state
2023-07-02 10:34:45,636 [classy] Setting parameters: {'Omega_m': 0.3065134691333626, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:45,683 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.9847007998794}
2023-07-02 10:34:45,683 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:45,685 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00242133
2023-07-02 10:34:45,685 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5069897867415467, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:45,685 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:45,705 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.28372
2023-07-02 10:34:45,705 [model] Computed derived parameters: {}
2023-07-02 10:34:45,705 [model] Posterior to be computed for parameters {'Omega_m': 0.3204636799915169, 'b1': 0.5239422943059711}
2023-07-02 10:34:45,705 [prior] Evaluating prior at array([0.32046368, 0.52394229])
2023-07-02 10:34:45,705 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:45,705 [model] Got input parameters: {'Omega_m': 0.3204636799915169, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5239422943059711, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:45,705 [classy] Got parameters {'Omega_m': 0.3204636799915169, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:45,705 [classy] Re-using computed results
2023-07-02 10:34:45,705 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.3107100794703}
2023-07-02 10:34:45,705 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:45,705 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5239422943059711, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:45,705 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:45,725 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.37289
2023-07-02 10:34:45,725 [model] Computed derived parameters: {}
2023-07-02 10:34:45,725 [model] Posterior to be computed for parameters {'Omega_m': 0.32880092626619056, 'b1': 0.46735398647723597}
2023-07-02 10:34:45,725 [prior] Evaluating prior at array([0.32880093, 0.46735399])
2023-07-02 10:34:45,725 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:45,725 [model] Got input parameters: {'Omega_m': 0.32880092626619056, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46735398647723597, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:45,726 [classy] Got parameters {'Omega_m': 0.32880092626619056, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:45,726 [classy] Computing new state
2023-07-02 10:34:45,726 [classy] Setting parameters: {'Omega_m': 0.32880092626619056, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:45,774 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.34103974095072}
2023-07-02 10:34:45,774 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:45,776 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0158891
2023-07-02 10:34:45,776 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46735398647723597, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:45,776 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:45,795 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.77175
2023-07-02 10:34:45,795 [model] Computed derived parameters: {}
2023-07-02 10:34:45,795 [model] Posterior to be computed for parameters {'Omega_m': 0.3204636799915169, 'b1': 0.462676559115909}
2023-07-02 10:34:45,795 [prior] Evaluating prior at array([0.32046368, 0.46267656])
2023-07-02 10:34:45,795 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:45,795 [model] Got input parameters: {'Omega_m': 0.3204636799915169, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.462676559115909, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:45,795 [classy] Got parameters {'Omega_m': 0.3204636799915169, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:45,795 [classy] Re-using computed results
2023-07-02 10:34:45,795 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.3107100794703}
2023-07-02 10:34:45,795 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:45,795 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.462676559115909, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:45,795 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:45,815 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.744115
2023-07-02 10:34:45,815 [model] Computed derived parameters: {}
2023-07-02 10:34:45,815 [model] Posterior to be computed for parameters {'Omega_m': 0.28794603904077964, 'b1': 0.5400099265531533}
2023-07-02 10:34:45,815 [prior] Evaluating prior at array([0.28794604, 0.54000993])
2023-07-02 10:34:45,815 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:45,815 [model] Got input parameters: {'Omega_m': 0.28794603904077964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5400099265531533, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:45,815 [classy] Got parameters {'Omega_m': 0.28794603904077964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:45,815 [classy] Computing new state
2023-07-02 10:34:45,815 [classy] Setting parameters: {'Omega_m': 0.28794603904077964, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:45,862 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.32000792177155}
2023-07-02 10:34:45,862 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:45,864 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0395066
2023-07-02 10:34:45,864 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5400099265531533, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:45,864 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:45,884 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.9829
2023-07-02 10:34:45,884 [model] Computed derived parameters: {}
2023-07-02 10:34:45,884 [model] Posterior to be computed for parameters {'Omega_m': 0.3204636799915169, 'b1': 0.459186532814003}
2023-07-02 10:34:45,884 [prior] Evaluating prior at array([0.32046368, 0.45918653])
2023-07-02 10:34:45,884 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:45,884 [model] Got input parameters: {'Omega_m': 0.3204636799915169, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.459186532814003, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:45,884 [classy] Got parameters {'Omega_m': 0.3204636799915169, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:45,884 [classy] Re-using computed results
2023-07-02 10:34:45,884 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.3107100794703}
2023-07-02 10:34:45,884 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:45,884 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.459186532814003, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:45,884 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:45,903 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.210661
2023-07-02 10:34:45,904 [model] Computed derived parameters: {}
2023-07-02 10:34:45,904 [mcmc] New sample, #822:
Omega_m:0.3204637, b1:0.4821809
2023-07-02 10:34:45,904 [model] Posterior to be computed for parameters {'Omega_m': 0.254984134023796, 'b1': 0.5756347301075192}
2023-07-02 10:34:45,904 [prior] Evaluating prior at array([0.25498413, 0.57563473])
2023-07-02 10:34:45,904 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:45,904 [model] Got input parameters: {'Omega_m': 0.254984134023796, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5756347301075192, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:45,904 [classy] Got parameters {'Omega_m': 0.254984134023796, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:45,904 [classy] Computing new state
2023-07-02 10:34:45,904 [classy] Setting parameters: {'Omega_m': 0.254984134023796, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:45,951 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 154.80508460443411}
2023-07-02 10:34:45,951 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:45,953 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.236149
2023-07-02 10:34:45,953 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5756347301075192, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:45,953 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:45,974 [fs_likelihood.fslikelihood] Computed log-likelihood = -25.8701
2023-07-02 10:34:45,974 [model] Computed derived parameters: {}
2023-07-02 10:34:45,974 [model] Posterior to be computed for parameters {'Omega_m': 0.3204636799915169, 'b1': 0.49537861958575924}
2023-07-02 10:34:45,974 [prior] Evaluating prior at array([0.32046368, 0.49537862])
2023-07-02 10:34:45,974 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:45,974 [model] Got input parameters: {'Omega_m': 0.3204636799915169, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49537861958575924, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:45,974 [classy] Got parameters {'Omega_m': 0.3204636799915169, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:45,974 [classy] Re-using computed results
2023-07-02 10:34:45,974 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.3107100794703}
2023-07-02 10:34:45,974 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:45,974 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49537861958575924, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:45,974 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:45,994 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.70727
2023-07-02 10:34:45,994 [model] Computed derived parameters: {}
2023-07-02 10:34:45,994 [mcmc] New sample, #823:
Omega_m:0.3204637, b1:0.4591865
2023-07-02 10:34:45,994 [model] Posterior to be computed for parameters {'Omega_m': 0.2635018359035426, 'b1': 0.5966790174509006}
2023-07-02 10:34:45,994 [prior] Evaluating prior at array([0.26350184, 0.59667902])
2023-07-02 10:34:45,994 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:45,994 [model] Got input parameters: {'Omega_m': 0.2635018359035426, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5966790174509006, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:45,994 [classy] Got parameters {'Omega_m': 0.2635018359035426, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:45,994 [classy] Computing new state
2023-07-02 10:34:45,994 [classy] Setting parameters: {'Omega_m': 0.2635018359035426, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:46,040 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.60113934414392}
2023-07-02 10:34:46,040 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:46,042 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.167423
2023-07-02 10:34:46,042 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5966790174509006, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:46,042 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:46,062 [fs_likelihood.fslikelihood] Computed log-likelihood = -15.7442
2023-07-02 10:34:46,062 [model] Computed derived parameters: {}
2023-07-02 10:34:46,063 [model] Posterior to be computed for parameters {'Omega_m': 0.3204636799915169, 'b1': 0.46984769903106843}
2023-07-02 10:34:46,063 [prior] Evaluating prior at array([0.32046368, 0.4698477 ])
2023-07-02 10:34:46,063 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:46,063 [model] Got input parameters: {'Omega_m': 0.3204636799915169, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46984769903106843, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:46,063 [classy] Got parameters {'Omega_m': 0.3204636799915169, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:46,063 [classy] Re-using computed results
2023-07-02 10:34:46,063 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.3107100794703}
2023-07-02 10:34:46,063 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:46,063 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46984769903106843, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:46,063 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:46,083 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.64934
2023-07-02 10:34:46,083 [model] Computed derived parameters: {}
2023-07-02 10:34:46,083 [mcmc] New sample, #824:
Omega_m:0.3204637, b1:0.4953786
2023-07-02 10:34:46,083 [model] Posterior to be computed for parameters {'Omega_m': 0.3400290160286764, 'b1': 0.43505289284697796}
2023-07-02 10:34:46,083 [prior] Evaluating prior at array([0.34002902, 0.43505289])
2023-07-02 10:34:46,084 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:46,084 [model] Got input parameters: {'Omega_m': 0.3400290160286764, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.43505289284697796, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:46,084 [classy] Got parameters {'Omega_m': 0.3400290160286764, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:46,084 [classy] Computing new state
2023-07-02 10:34:46,084 [classy] Setting parameters: {'Omega_m': 0.3400290160286764, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:46,131 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.06965962747645}
2023-07-02 10:34:46,131 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:46,133 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0437217
2023-07-02 10:34:46,133 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.43505289284697796, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:46,133 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:46,153 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.27279
2023-07-02 10:34:46,153 [model] Computed derived parameters: {}
2023-07-02 10:34:46,153 [model] Posterior to be computed for parameters {'Omega_m': 0.3204636799915169, 'b1': 0.48421442736241566}
2023-07-02 10:34:46,154 [prior] Evaluating prior at array([0.32046368, 0.48421443])
2023-07-02 10:34:46,154 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:46,154 [model] Got input parameters: {'Omega_m': 0.3204636799915169, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48421442736241566, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:46,154 [classy] Got parameters {'Omega_m': 0.3204636799915169, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:46,154 [classy] Re-using computed results
2023-07-02 10:34:46,154 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.3107100794703}
2023-07-02 10:34:46,154 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:46,154 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48421442736241566, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:46,154 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:46,173 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.66981
2023-07-02 10:34:46,173 [model] Computed derived parameters: {}
2023-07-02 10:34:46,173 [mcmc] New sample, #825:
Omega_m:0.3204637, b1:0.4698477
2023-07-02 10:34:46,173 [model] Posterior to be computed for parameters {'Omega_m': 0.3241984784152171, 'b1': 0.4775724976228761}
2023-07-02 10:34:46,173 [prior] Evaluating prior at array([0.32419848, 0.4775725 ])
2023-07-02 10:34:46,174 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:46,174 [model] Got input parameters: {'Omega_m': 0.3241984784152171, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4775724976228761, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:46,174 [classy] Got parameters {'Omega_m': 0.3241984784152171, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:46,174 [classy] Computing new state
2023-07-02 10:34:46,174 [classy] Setting parameters: {'Omega_m': 0.3241984784152171, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:46,220 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.87357597307204}
2023-07-02 10:34:46,220 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:46,222 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00837782
2023-07-02 10:34:46,222 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4775724976228761, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:46,222 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:46,242 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.38755
2023-07-02 10:34:46,242 [model] Computed derived parameters: {}
2023-07-02 10:34:46,242 [mcmc] New sample, #826:
Omega_m:0.3204637, b1:0.4842144
2023-07-02 10:34:46,242 [model] Posterior to be computed for parameters {'Omega_m': 0.3241984784152171, 'b1': 0.45570863516076787}
2023-07-02 10:34:46,242 [prior] Evaluating prior at array([0.32419848, 0.45570864])
2023-07-02 10:34:46,242 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:46,242 [model] Got input parameters: {'Omega_m': 0.3241984784152171, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45570863516076787, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:46,242 [classy] Got parameters {'Omega_m': 0.3241984784152171, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:46,242 [classy] Re-using computed results
2023-07-02 10:34:46,242 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.87357597307204}
2023-07-02 10:34:46,242 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:46,242 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45570863516076787, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:46,242 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:46,261 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.422848
2023-07-02 10:34:46,261 [model] Computed derived parameters: {}
2023-07-02 10:34:46,262 [model] Posterior to be computed for parameters {'Omega_m': 0.32106700371254754, 'b1': 0.48314148223642067}
2023-07-02 10:34:46,262 [prior] Evaluating prior at array([0.321067 , 0.48314148])
2023-07-02 10:34:46,262 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:46,262 [model] Got input parameters: {'Omega_m': 0.32106700371254754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48314148223642067, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:46,262 [classy] Got parameters {'Omega_m': 0.32106700371254754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:46,262 [classy] Computing new state
2023-07-02 10:34:46,262 [classy] Setting parameters: {'Omega_m': 0.32106700371254754, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:46,308 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.23978869455408}
2023-07-02 10:34:46,308 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:46,310 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00462471
2023-07-02 10:34:46,310 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48314148223642067, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:46,310 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:46,330 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.63397
2023-07-02 10:34:46,330 [model] Computed derived parameters: {}
2023-07-02 10:34:46,330 [mcmc] New sample, #827:
Omega_m:0.3241985, b1:0.4775725
2023-07-02 10:34:46,330 [model] Posterior to be computed for parameters {'Omega_m': 0.32106700371254754, 'b1': 0.4489491550452118}
2023-07-02 10:34:46,330 [prior] Evaluating prior at array([0.321067 , 0.44894916])
2023-07-02 10:34:46,330 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:46,330 [model] Got input parameters: {'Omega_m': 0.32106700371254754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4489491550452118, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:46,330 [classy] Got parameters {'Omega_m': 0.32106700371254754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:46,330 [classy] Re-using computed results
2023-07-02 10:34:46,330 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.23978869455408}
2023-07-02 10:34:46,330 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:46,330 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4489491550452118, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:46,330 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:46,350 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.50803
2023-07-02 10:34:46,350 [model] Computed derived parameters: {}
2023-07-02 10:34:46,350 [model] Posterior to be computed for parameters {'Omega_m': 0.2996137326025542, 'b1': 0.5212937740687329}
2023-07-02 10:34:46,350 [prior] Evaluating prior at array([0.29961373, 0.52129377])
2023-07-02 10:34:46,350 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:46,350 [model] Got input parameters: {'Omega_m': 0.2996137326025542, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5212937740687329, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:46,350 [classy] Got parameters {'Omega_m': 0.2996137326025542, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:46,350 [classy] Computing new state
2023-07-02 10:34:46,350 [classy] Setting parameters: {'Omega_m': 0.2996137326025542, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:46,397 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.83766879806254}
2023-07-02 10:34:46,397 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:46,399 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0106941
2023-07-02 10:34:46,399 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5212937740687329, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:46,399 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:46,418 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.34105
2023-07-02 10:34:46,418 [model] Computed derived parameters: {}
2023-07-02 10:34:46,418 [model] Posterior to be computed for parameters {'Omega_m': 0.32106700371254754, 'b1': 0.46341011972255525}
2023-07-02 10:34:46,418 [prior] Evaluating prior at array([0.321067 , 0.46341012])
2023-07-02 10:34:46,418 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:46,418 [model] Got input parameters: {'Omega_m': 0.32106700371254754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46341011972255525, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:46,418 [classy] Got parameters {'Omega_m': 0.32106700371254754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:46,418 [classy] Re-using computed results
2023-07-02 10:34:46,418 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.23978869455408}
2023-07-02 10:34:46,418 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:46,418 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46341011972255525, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:46,418 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:46,438 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.961935
2023-07-02 10:34:46,438 [model] Computed derived parameters: {}
2023-07-02 10:34:46,438 [model] Posterior to be computed for parameters {'Omega_m': 0.33315208663031154, 'b1': 0.4616494865434446}
2023-07-02 10:34:46,438 [prior] Evaluating prior at array([0.33315209, 0.46164949])
2023-07-02 10:34:46,439 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:46,439 [model] Got input parameters: {'Omega_m': 0.33315208663031154, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4616494865434446, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:46,439 [classy] Got parameters {'Omega_m': 0.33315208663031154, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:46,439 [classy] Computing new state
2023-07-02 10:34:46,439 [classy] Setting parameters: {'Omega_m': 0.33315208663031154, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:46,486 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.8437618458461}
2023-07-02 10:34:46,486 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:46,488 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.025108
2023-07-02 10:34:46,488 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4616494865434446, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:46,488 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:46,507 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.15421
2023-07-02 10:34:46,507 [model] Computed derived parameters: {}
2023-07-02 10:34:46,507 [model] Posterior to be computed for parameters {'Omega_m': 0.32106700371254754, 'b1': 0.49440852914269184}
2023-07-02 10:34:46,507 [prior] Evaluating prior at array([0.321067 , 0.49440853])
2023-07-02 10:34:46,507 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:46,507 [model] Got input parameters: {'Omega_m': 0.32106700371254754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49440852914269184, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:46,507 [classy] Got parameters {'Omega_m': 0.32106700371254754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:46,507 [classy] Re-using computed results
2023-07-02 10:34:46,507 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.23978869455408}
2023-07-02 10:34:46,507 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:46,507 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49440852914269184, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:46,507 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:46,526 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.66734
2023-07-02 10:34:46,527 [model] Computed derived parameters: {}
2023-07-02 10:34:46,527 [mcmc] New sample, #828:
Omega_m:0.321067, b1:0.4831415
2023-07-02 10:34:46,527 [model] Posterior to be computed for parameters {'Omega_m': 0.32331155137075734, 'b1': 0.4904168470887759}
2023-07-02 10:34:46,527 [prior] Evaluating prior at array([0.32331155, 0.49041685])
2023-07-02 10:34:46,527 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:46,527 [model] Got input parameters: {'Omega_m': 0.32331155137075734, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4904168470887759, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:46,527 [classy] Got parameters {'Omega_m': 0.32331155137075734, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:46,527 [classy] Computing new state
2023-07-02 10:34:46,527 [classy] Setting parameters: {'Omega_m': 0.32331155137075734, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:46,574 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.97697715697063}
2023-07-02 10:34:46,574 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:46,575 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00720174
2023-07-02 10:34:46,575 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4904168470887759, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:46,575 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:46,595 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.49612
2023-07-02 10:34:46,595 [model] Computed derived parameters: {}
2023-07-02 10:34:46,595 [mcmc] New sample, #829:
Omega_m:0.321067, b1:0.4944085
2023-07-02 10:34:46,595 [model] Posterior to be computed for parameters {'Omega_m': 0.32331155137075734, 'b1': 0.4764687712503482}
2023-07-02 10:34:46,595 [prior] Evaluating prior at array([0.32331155, 0.47646877])
2023-07-02 10:34:46,595 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:46,595 [model] Got input parameters: {'Omega_m': 0.32331155137075734, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4764687712503482, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:46,596 [classy] Got parameters {'Omega_m': 0.32331155137075734, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:46,596 [classy] Re-using computed results
2023-07-02 10:34:46,596 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.97697715697063}
2023-07-02 10:34:46,596 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:46,596 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4764687712503482, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:46,596 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:46,615 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.36009
2023-07-02 10:34:46,615 [model] Computed derived parameters: {}
2023-07-02 10:34:46,615 [mcmc] New sample, #830:
Omega_m:0.3233116, b1:0.4904168
2023-07-02 10:34:46,615 [model] Posterior to be computed for parameters {'Omega_m': 0.3240329193181236, 'b1': 0.475185897403032}
2023-07-02 10:34:46,615 [prior] Evaluating prior at array([0.32403292, 0.4751859 ])
2023-07-02 10:34:46,615 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:46,615 [model] Got input parameters: {'Omega_m': 0.3240329193181236, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.475185897403032, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:46,615 [classy] Got parameters {'Omega_m': 0.3240329193181236, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:46,615 [classy] Computing new state
2023-07-02 10:34:46,615 [classy] Setting parameters: {'Omega_m': 0.3240329193181236, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:46,661 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.8928590306198}
2023-07-02 10:34:46,661 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:46,663 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00815153
2023-07-02 10:34:46,663 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.475185897403032, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:46,663 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:46,683 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.29596
2023-07-02 10:34:46,683 [model] Computed derived parameters: {}
2023-07-02 10:34:46,683 [mcmc] New sample, #831:
Omega_m:0.3233116, b1:0.4764688
2023-07-02 10:34:46,683 [model] Posterior to be computed for parameters {'Omega_m': 0.3240329193181236, 'b1': 0.4924010266341708}
2023-07-02 10:34:46,683 [prior] Evaluating prior at array([0.32403292, 0.49240103])
2023-07-02 10:34:46,683 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:46,684 [model] Got input parameters: {'Omega_m': 0.3240329193181236, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4924010266341708, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:46,684 [classy] Got parameters {'Omega_m': 0.3240329193181236, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:46,684 [classy] Re-using computed results
2023-07-02 10:34:46,684 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.8928590306198}
2023-07-02 10:34:46,684 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:46,684 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4924010266341708, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:46,684 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:46,703 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.30798
2023-07-02 10:34:46,703 [model] Computed derived parameters: {}
2023-07-02 10:34:46,703 [mcmc] New sample, #832:
Omega_m:0.3240329, b1:0.4751859
2023-07-02 10:34:46,703 [model] Posterior to be computed for parameters {'Omega_m': 0.34032158399284984, 'b1': 0.4634334214124502}
2023-07-02 10:34:46,703 [prior] Evaluating prior at array([0.34032158, 0.46343342])
2023-07-02 10:34:46,703 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:46,703 [model] Got input parameters: {'Omega_m': 0.34032158399284984, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4634334214124502, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:46,703 [classy] Got parameters {'Omega_m': 0.34032158399284984, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:46,703 [classy] Computing new state
2023-07-02 10:34:46,703 [classy] Setting parameters: {'Omega_m': 0.34032158399284984, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:46,750 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.0370433254932}
2023-07-02 10:34:46,750 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:46,752 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0446204
2023-07-02 10:34:46,752 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4634334214124502, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:46,752 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:46,771 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.486859
2023-07-02 10:34:46,771 [model] Computed derived parameters: {}
2023-07-02 10:34:46,771 [model] Posterior to be computed for parameters {'Omega_m': 0.3240329193181236, 'b1': 0.526459826091082}
2023-07-02 10:34:46,772 [prior] Evaluating prior at array([0.32403292, 0.52645983])
2023-07-02 10:34:46,772 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:46,772 [model] Got input parameters: {'Omega_m': 0.3240329193181236, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.526459826091082, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:46,772 [classy] Got parameters {'Omega_m': 0.3240329193181236, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:46,772 [classy] Re-using computed results
2023-07-02 10:34:46,772 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.8928590306198}
2023-07-02 10:34:46,772 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:46,772 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.526459826091082, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:46,772 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:46,792 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.62071
2023-07-02 10:34:46,792 [model] Computed derived parameters: {}
2023-07-02 10:34:46,792 [model] Posterior to be computed for parameters {'Omega_m': 0.2945567422101325, 'b1': 0.5448211776386088}
2023-07-02 10:34:46,792 [prior] Evaluating prior at array([0.29455674, 0.54482118])
2023-07-02 10:34:46,792 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:46,792 [model] Got input parameters: {'Omega_m': 0.2945567422101325, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5448211776386088, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:46,792 [classy] Got parameters {'Omega_m': 0.2945567422101325, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:46,792 [classy] Computing new state
2023-07-02 10:34:46,792 [classy] Setting parameters: {'Omega_m': 0.2945567422101325, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:46,838 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.47387734387172}
2023-07-02 10:34:46,838 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:46,840 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0208254
2023-07-02 10:34:46,840 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5448211776386088, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:46,840 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:46,860 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.171821
2023-07-02 10:34:46,860 [model] Computed derived parameters: {}
2023-07-02 10:34:46,860 [model] Posterior to be computed for parameters {'Omega_m': 0.3240329193181236, 'b1': 0.49649074141397276}
2023-07-02 10:34:46,860 [prior] Evaluating prior at array([0.32403292, 0.49649074])
2023-07-02 10:34:46,860 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:46,860 [model] Got input parameters: {'Omega_m': 0.3240329193181236, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49649074141397276, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:46,860 [classy] Got parameters {'Omega_m': 0.3240329193181236, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:46,860 [classy] Re-using computed results
2023-07-02 10:34:46,860 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.8928590306198}
2023-07-02 10:34:46,860 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:46,860 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49649074141397276, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:46,860 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:46,880 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.07104
2023-07-02 10:34:46,880 [model] Computed derived parameters: {}
2023-07-02 10:34:46,880 [model] Posterior to be computed for parameters {'Omega_m': 0.29740586748778725, 'b1': 0.5397543205377695}
2023-07-02 10:34:46,880 [prior] Evaluating prior at array([0.29740587, 0.53975432])
2023-07-02 10:34:46,880 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:46,880 [model] Got input parameters: {'Omega_m': 0.29740586748778725, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5397543205377695, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:46,880 [classy] Got parameters {'Omega_m': 0.29740586748778725, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:46,880 [classy] Computing new state
2023-07-02 10:34:46,880 [classy] Setting parameters: {'Omega_m': 0.29740586748778725, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:46,927 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.1142772528522}
2023-07-02 10:34:46,927 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:46,928 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0146845
2023-07-02 10:34:46,928 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5397543205377695, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:46,929 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:46,948 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.861591
2023-07-02 10:34:46,948 [model] Computed derived parameters: {}
2023-07-02 10:34:46,948 [model] Posterior to be computed for parameters {'Omega_m': 0.3240329193181236, 'b1': 0.5428104433336355}
2023-07-02 10:34:46,948 [prior] Evaluating prior at array([0.32403292, 0.54281044])
2023-07-02 10:34:46,948 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:46,948 [model] Got input parameters: {'Omega_m': 0.3240329193181236, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5428104433336355, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:46,949 [classy] Got parameters {'Omega_m': 0.3240329193181236, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:46,949 [classy] Re-using computed results
2023-07-02 10:34:46,949 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.8928590306198}
2023-07-02 10:34:46,949 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:46,949 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5428104433336355, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:46,949 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:46,968 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.48262
2023-07-02 10:34:46,969 [model] Computed derived parameters: {}
2023-07-02 10:34:46,969 [model] Posterior to be computed for parameters {'Omega_m': 0.34210341483664924, 'b1': 0.46026463050872723}
2023-07-02 10:34:46,969 [prior] Evaluating prior at array([0.34210341, 0.46026463])
2023-07-02 10:34:46,969 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:46,969 [model] Got input parameters: {'Omega_m': 0.34210341483664924, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46026463050872723, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:46,969 [classy] Got parameters {'Omega_m': 0.34210341483664924, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:46,969 [classy] Computing new state
2023-07-02 10:34:46,969 [classy] Setting parameters: {'Omega_m': 0.34210341483664924, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:47,017 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.8389398909406}
2023-07-02 10:34:47,018 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:47,020 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0502783
2023-07-02 10:34:47,020 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46026463050872723, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:47,020 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:47,041 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.930303
2023-07-02 10:34:47,041 [model] Computed derived parameters: {}
2023-07-02 10:34:47,041 [model] Posterior to be computed for parameters {'Omega_m': 0.3240329193181236, 'b1': 0.47383756776374836}
2023-07-02 10:34:47,041 [prior] Evaluating prior at array([0.32403292, 0.47383757])
2023-07-02 10:34:47,041 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:47,042 [model] Got input parameters: {'Omega_m': 0.3240329193181236, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47383756776374836, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:47,042 [classy] Got parameters {'Omega_m': 0.3240329193181236, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:47,042 [classy] Re-using computed results
2023-07-02 10:34:47,042 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.8928590306198}
2023-07-02 10:34:47,042 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:47,042 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47383756776374836, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:47,042 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:47,061 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.22769
2023-07-02 10:34:47,061 [model] Computed derived parameters: {}
2023-07-02 10:34:47,061 [mcmc] New sample, #833:
Omega_m:0.3240329, b1:0.492401
2023-07-02 10:34:47,061 [model] Posterior to be computed for parameters {'Omega_m': 0.301444991466047, 'b1': 0.5140077222768383}
2023-07-02 10:34:47,062 [prior] Evaluating prior at array([0.30144499, 0.51400772])
2023-07-02 10:34:47,062 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:47,062 [model] Got input parameters: {'Omega_m': 0.301444991466047, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5140077222768383, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:47,062 [classy] Got parameters {'Omega_m': 0.301444991466047, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:47,062 [classy] Computing new state
2023-07-02 10:34:47,062 [classy] Setting parameters: {'Omega_m': 0.301444991466047, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:47,108 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.60960776742837}
2023-07-02 10:34:47,109 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:47,110 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00788493
2023-07-02 10:34:47,111 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5140077222768383, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:47,111 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:47,134 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.4853
2023-07-02 10:34:47,134 [model] Computed derived parameters: {}
2023-07-02 10:34:47,134 [mcmc] New sample, #834:
Omega_m:0.3240329, b1:0.4738376
2023-07-02 10:34:47,134 [model] Posterior to be computed for parameters {'Omega_m': 0.301444991466047, 'b1': 0.5749514980759027}
2023-07-02 10:34:47,134 [prior] Evaluating prior at array([0.30144499, 0.5749515 ])
2023-07-02 10:34:47,135 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:47,135 [model] Got input parameters: {'Omega_m': 0.301444991466047, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5749514980759027, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:47,135 [classy] Got parameters {'Omega_m': 0.301444991466047, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:47,135 [classy] Re-using computed results
2023-07-02 10:34:47,135 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.60960776742837}
2023-07-02 10:34:47,135 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:47,135 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5749514980759027, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:47,135 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:47,156 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.1807
2023-07-02 10:34:47,156 [model] Computed derived parameters: {}
2023-07-02 10:34:47,156 [model] Posterior to be computed for parameters {'Omega_m': 0.28172726617433125, 'b1': 0.5490735360514323}
2023-07-02 10:34:47,156 [prior] Evaluating prior at array([0.28172727, 0.54907354])
2023-07-02 10:34:47,157 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:47,157 [model] Got input parameters: {'Omega_m': 0.28172726617433125, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5490735360514323, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:47,157 [classy] Got parameters {'Omega_m': 0.28172726617433125, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:47,157 [classy] Computing new state
2023-07-02 10:34:47,157 [classy] Setting parameters: {'Omega_m': 0.28172726617433125, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:47,203 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.1314847539365}
2023-07-02 10:34:47,204 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:47,205 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0629719
2023-07-02 10:34:47,205 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5490735360514323, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:47,206 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:47,226 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.66316
2023-07-02 10:34:47,226 [model] Computed derived parameters: {}
2023-07-02 10:34:47,226 [model] Posterior to be computed for parameters {'Omega_m': 0.301444991466047, 'b1': 0.5045257792372396}
2023-07-02 10:34:47,226 [prior] Evaluating prior at array([0.30144499, 0.50452578])
2023-07-02 10:34:47,226 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:47,226 [model] Got input parameters: {'Omega_m': 0.301444991466047, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5045257792372396, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:47,226 [classy] Got parameters {'Omega_m': 0.301444991466047, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:47,226 [classy] Re-using computed results
2023-07-02 10:34:47,226 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.60960776742837}
2023-07-02 10:34:47,226 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:47,226 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5045257792372396, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:47,226 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:47,246 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.712692
2023-07-02 10:34:47,246 [model] Computed derived parameters: {}
2023-07-02 10:34:47,247 [model] Posterior to be computed for parameters {'Omega_m': 0.29679947600017464, 'b1': 0.522269262480044}
2023-07-02 10:34:47,247 [prior] Evaluating prior at array([0.29679948, 0.52226926])
2023-07-02 10:34:47,247 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:47,247 [model] Got input parameters: {'Omega_m': 0.29679947600017464, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.522269262480044, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:47,247 [classy] Got parameters {'Omega_m': 0.29679947600017464, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:47,247 [classy] Computing new state
2023-07-02 10:34:47,247 [classy] Setting parameters: {'Omega_m': 0.29679947600017464, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:47,294 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.19056183055284}
2023-07-02 10:34:47,294 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:47,296 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0158973
2023-07-02 10:34:47,296 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.522269262480044, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:47,296 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:47,316 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.548139
2023-07-02 10:34:47,316 [model] Computed derived parameters: {}
2023-07-02 10:34:47,316 [mcmc] New sample, #835:
Omega_m:0.301445, b1:0.5140077
2023-07-02 10:34:47,316 [model] Posterior to be computed for parameters {'Omega_m': 0.29679947600017464, 'b1': 0.5484701391944216}
2023-07-02 10:34:47,316 [prior] Evaluating prior at array([0.29679948, 0.54847014])
2023-07-02 10:34:47,316 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:47,316 [model] Got input parameters: {'Omega_m': 0.29679947600017464, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5484701391944216, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:47,316 [classy] Got parameters {'Omega_m': 0.29679947600017464, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:47,316 [classy] Re-using computed results
2023-07-02 10:34:47,316 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.19056183055284}
2023-07-02 10:34:47,316 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:47,316 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5484701391944216, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:47,316 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:47,335 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.261447
2023-07-02 10:34:47,336 [model] Computed derived parameters: {}
2023-07-02 10:34:47,336 [mcmc] New sample, #836:
Omega_m:0.2967995, b1:0.5222693
2023-07-02 10:34:47,336 [model] Posterior to be computed for parameters {'Omega_m': 0.28580216197621516, 'b1': 0.5680276571068408}
2023-07-02 10:34:47,336 [prior] Evaluating prior at array([0.28580216, 0.56802766])
2023-07-02 10:34:47,336 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:47,336 [model] Got input parameters: {'Omega_m': 0.28580216197621516, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5680276571068408, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:47,336 [classy] Got parameters {'Omega_m': 0.28580216197621516, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:47,336 [classy] Computing new state
2023-07-02 10:34:47,336 [classy] Setting parameters: {'Omega_m': 0.28580216197621516, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:47,382 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.59802156619912}
2023-07-02 10:34:47,382 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:47,384 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0469356
2023-07-02 10:34:47,384 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5680276571068408, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:47,384 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:47,405 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.14085
2023-07-02 10:34:47,405 [model] Computed derived parameters: {}
2023-07-02 10:34:47,405 [model] Posterior to be computed for parameters {'Omega_m': 0.29679947600017464, 'b1': 0.5195493455265492}
2023-07-02 10:34:47,405 [prior] Evaluating prior at array([0.29679948, 0.51954935])
2023-07-02 10:34:47,406 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:47,406 [model] Got input parameters: {'Omega_m': 0.29679947600017464, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5195493455265492, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:47,406 [classy] Got parameters {'Omega_m': 0.29679947600017464, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:47,406 [classy] Re-using computed results
2023-07-02 10:34:47,406 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.19056183055284}
2023-07-02 10:34:47,406 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:47,406 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5195493455265492, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:47,406 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:47,426 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.371791
2023-07-02 10:34:47,426 [model] Computed derived parameters: {}
2023-07-02 10:34:47,426 [mcmc] New sample, #837:
Omega_m:0.2967995, b1:0.5484701
2023-07-02 10:34:47,426 [model] Posterior to be computed for parameters {'Omega_m': 0.32409833934501886, 'b1': 0.4710013084611083}
2023-07-02 10:34:47,426 [prior] Evaluating prior at array([0.32409834, 0.47100131])
2023-07-02 10:34:47,427 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:47,427 [model] Got input parameters: {'Omega_m': 0.32409833934501886, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4710013084611083, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:47,427 [classy] Got parameters {'Omega_m': 0.32409833934501886, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:47,427 [classy] Computing new state
2023-07-02 10:34:47,427 [classy] Setting parameters: {'Omega_m': 0.32409833934501886, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:47,474 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.88523769549832}
2023-07-02 10:34:47,474 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:47,476 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00824059
2023-07-02 10:34:47,476 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4710013084611083, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:47,476 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:47,495 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.0548
2023-07-02 10:34:47,495 [model] Computed derived parameters: {}
2023-07-02 10:34:47,495 [mcmc] New sample, #838:
Omega_m:0.2967995, b1:0.5195493
2023-07-02 10:34:47,495 [model] Posterior to be computed for parameters {'Omega_m': 0.32409833934501886, 'b1': 0.44928352353592915}
2023-07-02 10:34:47,496 [prior] Evaluating prior at array([0.32409834, 0.44928352])
2023-07-02 10:34:47,496 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:47,496 [model] Got input parameters: {'Omega_m': 0.32409833934501886, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44928352353592915, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:47,496 [classy] Got parameters {'Omega_m': 0.32409833934501886, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:47,496 [classy] Re-using computed results
2023-07-02 10:34:47,496 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.88523769549832}
2023-07-02 10:34:47,496 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:47,496 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44928352353592915, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:47,496 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:47,515 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.637678
2023-07-02 10:34:47,515 [model] Computed derived parameters: {}
2023-07-02 10:34:47,516 [model] Posterior to be computed for parameters {'Omega_m': 0.31904055838382217, 'b1': 0.4799960176719383}
2023-07-02 10:34:47,516 [prior] Evaluating prior at array([0.31904056, 0.47999602])
2023-07-02 10:34:47,516 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:47,516 [model] Got input parameters: {'Omega_m': 0.31904055838382217, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4799960176719383, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:47,516 [classy] Got parameters {'Omega_m': 0.31904055838382217, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:47,516 [classy] Computing new state
2023-07-02 10:34:47,516 [classy] Setting parameters: {'Omega_m': 0.31904055838382217, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:47,562 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.47847580447316}
2023-07-02 10:34:47,562 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:47,564 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00279585
2023-07-02 10:34:47,564 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4799960176719383, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:47,564 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:47,583 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.39214
2023-07-02 10:34:47,583 [model] Computed derived parameters: {}
2023-07-02 10:34:47,583 [mcmc] New sample, #839:
Omega_m:0.3240983, b1:0.4710013
2023-07-02 10:34:47,584 [model] Posterior to be computed for parameters {'Omega_m': 0.31904055838382217, 'b1': 0.46708924711558697}
2023-07-02 10:34:47,584 [prior] Evaluating prior at array([0.31904056, 0.46708925])
2023-07-02 10:34:47,584 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:47,584 [model] Got input parameters: {'Omega_m': 0.31904055838382217, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46708924711558697, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:47,584 [classy] Got parameters {'Omega_m': 0.31904055838382217, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:47,584 [classy] Re-using computed results
2023-07-02 10:34:47,584 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.47847580447316}
2023-07-02 10:34:47,584 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:47,584 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46708924711558697, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:47,584 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:47,604 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.07291
2023-07-02 10:34:47,604 [model] Computed derived parameters: {}
2023-07-02 10:34:47,604 [mcmc] New sample, #840:
Omega_m:0.3190406, b1:0.479996
2023-07-02 10:34:47,604 [model] Posterior to be computed for parameters {'Omega_m': 0.3431241161118568, 'b1': 0.42425927875834646}
2023-07-02 10:34:47,604 [prior] Evaluating prior at array([0.34312412, 0.42425928])
2023-07-02 10:34:47,604 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:47,604 [model] Got input parameters: {'Omega_m': 0.3431241161118568, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42425927875834646, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:47,605 [classy] Got parameters {'Omega_m': 0.3431241161118568, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:47,605 [classy] Computing new state
2023-07-02 10:34:47,605 [classy] Setting parameters: {'Omega_m': 0.3431241161118568, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:47,651 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.72587887103907}
2023-07-02 10:34:47,651 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:47,653 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0536611
2023-07-02 10:34:47,653 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42425927875834646, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:47,653 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:47,672 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.67877
2023-07-02 10:34:47,672 [model] Computed derived parameters: {}
2023-07-02 10:34:47,672 [model] Posterior to be computed for parameters {'Omega_m': 0.31904055838382217, 'b1': 0.5029299393766773}
2023-07-02 10:34:47,672 [prior] Evaluating prior at array([0.31904056, 0.50292994])
2023-07-02 10:34:47,673 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:47,673 [model] Got input parameters: {'Omega_m': 0.31904055838382217, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5029299393766773, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:47,673 [classy] Got parameters {'Omega_m': 0.31904055838382217, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:47,673 [classy] Re-using computed results
2023-07-02 10:34:47,673 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.47847580447316}
2023-07-02 10:34:47,673 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:47,673 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5029299393766773, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:47,673 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:47,692 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.57604
2023-07-02 10:34:47,692 [model] Computed derived parameters: {}
2023-07-02 10:34:47,692 [mcmc] New sample, #841:
Omega_m:0.3190406, b1:0.4670892
2023-07-02 10:34:47,692 [model] Posterior to be computed for parameters {'Omega_m': 0.3859178305625387, 'b1': 0.38399603917892033}
2023-07-02 10:34:47,692 [prior] Evaluating prior at array([0.38591783, 0.38399604])
2023-07-02 10:34:47,693 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:47,693 [model] Got input parameters: {'Omega_m': 0.3859178305625387, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.38399603917892033, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:47,693 [classy] Got parameters {'Omega_m': 0.3859178305625387, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:47,693 [classy] Computing new state
2023-07-02 10:34:47,693 [classy] Setting parameters: {'Omega_m': 0.3859178305625387, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:47,739 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 139.2448833921163}
2023-07-02 10:34:47,739 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:47,741 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.278917
2023-07-02 10:34:47,741 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.38399603917892033, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:47,741 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:47,761 [fs_likelihood.fslikelihood] Computed log-likelihood = -18.1828
2023-07-02 10:34:47,761 [model] Computed derived parameters: {}
2023-07-02 10:34:47,762 [model] Posterior to be computed for parameters {'Omega_m': 0.31904055838382217, 'b1': 0.43592660179220477}
2023-07-02 10:34:47,762 [prior] Evaluating prior at array([0.31904056, 0.4359266 ])
2023-07-02 10:34:47,762 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:47,762 [model] Got input parameters: {'Omega_m': 0.31904055838382217, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.43592660179220477, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:47,762 [classy] Got parameters {'Omega_m': 0.31904055838382217, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:47,762 [classy] Re-using computed results
2023-07-02 10:34:47,762 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.47847580447316}
2023-07-02 10:34:47,762 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:47,762 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.43592660179220477, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:47,762 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:47,782 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.47869
2023-07-02 10:34:47,782 [model] Computed derived parameters: {}
2023-07-02 10:34:47,782 [model] Posterior to be computed for parameters {'Omega_m': 0.32869453131635723, 'b1': 0.48576140639283083}
2023-07-02 10:34:47,782 [prior] Evaluating prior at array([0.32869453, 0.48576141])
2023-07-02 10:34:47,782 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:47,782 [model] Got input parameters: {'Omega_m': 0.32869453131635723, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48576140639283083, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:47,782 [classy] Got parameters {'Omega_m': 0.32869453131635723, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:47,782 [classy] Computing new state
2023-07-02 10:34:47,782 [classy] Setting parameters: {'Omega_m': 0.32869453131635723, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:47,828 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.35327563092815}
2023-07-02 10:34:47,828 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:47,830 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0156891
2023-07-02 10:34:47,830 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48576140639283083, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:47,830 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:47,850 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.66891
2023-07-02 10:34:47,850 [model] Computed derived parameters: {}
2023-07-02 10:34:47,850 [mcmc] New sample, #842:
Omega_m:0.3190406, b1:0.5029299
2023-07-02 10:34:47,850 [model] Posterior to be computed for parameters {'Omega_m': 0.32869453131635723, 'b1': 0.4709479747084497}
2023-07-02 10:34:47,850 [prior] Evaluating prior at array([0.32869453, 0.47094797])
2023-07-02 10:34:47,850 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:47,850 [model] Got input parameters: {'Omega_m': 0.32869453131635723, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4709479747084497, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:47,851 [classy] Got parameters {'Omega_m': 0.32869453131635723, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:47,851 [classy] Re-using computed results
2023-07-02 10:34:47,851 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.35327563092815}
2023-07-02 10:34:47,851 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:47,851 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4709479747084497, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:47,851 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:47,870 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.90187
2023-07-02 10:34:47,870 [model] Computed derived parameters: {}
2023-07-02 10:34:47,870 [mcmc] New sample, #843:
Omega_m:0.3286945, b1:0.4857614
2023-07-02 10:34:47,870 [model] Posterior to be computed for parameters {'Omega_m': 0.3115643998545878, 'b1': 0.5014120364034917}
2023-07-02 10:34:47,870 [prior] Evaluating prior at array([0.3115644 , 0.50141204])
2023-07-02 10:34:47,871 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:47,871 [model] Got input parameters: {'Omega_m': 0.3115643998545878, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5014120364034917, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:47,871 [classy] Got parameters {'Omega_m': 0.3115643998545878, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:47,871 [classy] Computing new state
2023-07-02 10:34:47,871 [classy] Setting parameters: {'Omega_m': 0.3115643998545878, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:47,917 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.37092612240352}
2023-07-02 10:34:47,917 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:47,918 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000254345
2023-07-02 10:34:47,919 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5014120364034917, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:47,919 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:47,938 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.78004
2023-07-02 10:34:47,938 [model] Computed derived parameters: {}
2023-07-02 10:34:47,938 [mcmc] New sample, #844:
Omega_m:0.3286945, b1:0.470948
2023-07-02 10:34:47,938 [model] Posterior to be computed for parameters {'Omega_m': 0.3115643998545878, 'b1': 0.5291632861224524}
2023-07-02 10:34:47,938 [prior] Evaluating prior at array([0.3115644 , 0.52916329])
2023-07-02 10:34:47,938 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:47,938 [model] Got input parameters: {'Omega_m': 0.3115643998545878, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5291632861224524, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:47,938 [classy] Got parameters {'Omega_m': 0.3115643998545878, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:47,938 [classy] Re-using computed results
2023-07-02 10:34:47,938 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.37092612240352}
2023-07-02 10:34:47,939 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:47,939 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5291632861224524, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:47,939 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:47,958 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.45076
2023-07-02 10:34:47,958 [model] Computed derived parameters: {}
2023-07-02 10:34:47,959 [model] Posterior to be computed for parameters {'Omega_m': 0.3104685369835521, 'b1': 0.5033609084356209}
2023-07-02 10:34:47,959 [prior] Evaluating prior at array([0.31046854, 0.50336091])
2023-07-02 10:34:47,959 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:47,959 [model] Got input parameters: {'Omega_m': 0.3104685369835521, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5033609084356209, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:47,959 [classy] Got parameters {'Omega_m': 0.3104685369835521, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:47,959 [classy] Computing new state
2023-07-02 10:34:47,959 [classy] Setting parameters: {'Omega_m': 0.3104685369835521, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:48,005 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.50334483659913}
2023-07-02 10:34:48,005 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:48,007 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000452739
2023-07-02 10:34:48,007 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5033609084356209, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:48,007 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:48,026 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.72615
2023-07-02 10:34:48,026 [model] Computed derived parameters: {}
2023-07-02 10:34:48,026 [mcmc] New sample, #845:
Omega_m:0.3115644, b1:0.501412
2023-07-02 10:34:48,026 [model] Posterior to be computed for parameters {'Omega_m': 0.3104685369835521, 'b1': 0.5501529142575533}
2023-07-02 10:34:48,027 [prior] Evaluating prior at array([0.31046854, 0.55015291])
2023-07-02 10:34:48,027 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:48,027 [model] Got input parameters: {'Omega_m': 0.3104685369835521, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5501529142575533, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:48,027 [classy] Got parameters {'Omega_m': 0.3104685369835521, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:48,027 [classy] Re-using computed results
2023-07-02 10:34:48,027 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.50334483659913}
2023-07-02 10:34:48,027 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:48,027 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5501529142575533, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:48,027 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:48,046 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.03694
2023-07-02 10:34:48,046 [model] Computed derived parameters: {}
2023-07-02 10:34:48,046 [model] Posterior to be computed for parameters {'Omega_m': 0.29074059409736447, 'b1': 0.5384448930823451}
2023-07-02 10:34:48,046 [prior] Evaluating prior at array([0.29074059, 0.53844489])
2023-07-02 10:34:48,046 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:48,047 [model] Got input parameters: {'Omega_m': 0.29074059409736447, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5384448930823451, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:48,047 [classy] Got parameters {'Omega_m': 0.29074059409736447, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:48,047 [classy] Computing new state
2023-07-02 10:34:48,047 [classy] Setting parameters: {'Omega_m': 0.29074059409736447, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:48,093 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.96029194232824}
2023-07-02 10:34:48,093 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:48,095 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0308406
2023-07-02 10:34:48,095 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5384448930823451, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:48,095 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:48,114 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.889967
2023-07-02 10:34:48,114 [model] Computed derived parameters: {}
2023-07-02 10:34:48,115 [model] Posterior to be computed for parameters {'Omega_m': 0.3104685369835521, 'b1': 0.546824643797829}
2023-07-02 10:34:48,115 [prior] Evaluating prior at array([0.31046854, 0.54682464])
2023-07-02 10:34:48,115 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:48,115 [model] Got input parameters: {'Omega_m': 0.3104685369835521, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.546824643797829, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:48,115 [classy] Got parameters {'Omega_m': 0.3104685369835521, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:48,115 [classy] Re-using computed results
2023-07-02 10:34:48,115 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.50334483659913}
2023-07-02 10:34:48,115 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:48,115 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.546824643797829, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:48,115 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:48,136 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.28026
2023-07-02 10:34:48,136 [model] Computed derived parameters: {}
2023-07-02 10:34:48,137 [model] Posterior to be computed for parameters {'Omega_m': 0.31747201728014973, 'b1': 0.49090598616536735}
2023-07-02 10:34:48,137 [prior] Evaluating prior at array([0.31747202, 0.49090599])
2023-07-02 10:34:48,137 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:48,137 [model] Got input parameters: {'Omega_m': 0.31747201728014973, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49090598616536735, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:48,137 [classy] Got parameters {'Omega_m': 0.31747201728014973, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:48,137 [classy] Computing new state
2023-07-02 10:34:48,137 [classy] Setting parameters: {'Omega_m': 0.31747201728014973, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:48,184 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.66415246300454}
2023-07-02 10:34:48,184 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:48,185 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0017093
2023-07-02 10:34:48,186 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49090598616536735, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:48,186 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:48,205 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.83177
2023-07-02 10:34:48,205 [model] Computed derived parameters: {}
2023-07-02 10:34:48,205 [mcmc] New sample, #846:
Omega_m:0.3104685, b1:0.5033609
2023-07-02 10:34:48,205 [model] Posterior to be computed for parameters {'Omega_m': 0.31747201728014973, 'b1': 0.4956267208219138}
2023-07-02 10:34:48,205 [prior] Evaluating prior at array([0.31747202, 0.49562672])
2023-07-02 10:34:48,206 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:48,206 [model] Got input parameters: {'Omega_m': 0.31747201728014973, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4956267208219138, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:48,206 [classy] Got parameters {'Omega_m': 0.31747201728014973, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:48,206 [classy] Re-using computed results
2023-07-02 10:34:48,206 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.66415246300454}
2023-07-02 10:34:48,206 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:48,206 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4956267208219138, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:48,206 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:48,225 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.89763
2023-07-02 10:34:48,225 [model] Computed derived parameters: {}
2023-07-02 10:34:48,225 [mcmc] New sample, #847:
Omega_m:0.317472, b1:0.490906
2023-07-02 10:34:48,225 [model] Posterior to be computed for parameters {'Omega_m': 0.26609426637254247, 'b1': 0.5869964208674137}
2023-07-02 10:34:48,225 [prior] Evaluating prior at array([0.26609427, 0.58699642])
2023-07-02 10:34:48,226 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:48,226 [model] Got input parameters: {'Omega_m': 0.26609426637254247, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5869964208674137, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:48,226 [classy] Got parameters {'Omega_m': 0.26609426637254247, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:48,226 [classy] Computing new state
2023-07-02 10:34:48,226 [classy] Setting parameters: {'Omega_m': 0.26609426637254247, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:48,272 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.24119210357722}
2023-07-02 10:34:48,272 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:48,274 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.149129
2023-07-02 10:34:48,274 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5869964208674137, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:48,274 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:48,294 [fs_likelihood.fslikelihood] Computed log-likelihood = -13.7207
2023-07-02 10:34:48,294 [model] Computed derived parameters: {}
2023-07-02 10:34:48,294 [model] Posterior to be computed for parameters {'Omega_m': 0.31747201728014973, 'b1': 0.5297735251088072}
2023-07-02 10:34:48,294 [prior] Evaluating prior at array([0.31747202, 0.52977353])
2023-07-02 10:34:48,294 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:48,294 [model] Got input parameters: {'Omega_m': 0.31747201728014973, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5297735251088072, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:48,294 [classy] Got parameters {'Omega_m': 0.31747201728014973, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:48,294 [classy] Re-using computed results
2023-07-02 10:34:48,294 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.66415246300454}
2023-07-02 10:34:48,294 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:48,294 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5297735251088072, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:48,294 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:48,314 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.317312
2023-07-02 10:34:48,314 [model] Computed derived parameters: {}
2023-07-02 10:34:48,314 [model] Posterior to be computed for parameters {'Omega_m': 0.3143081785691022, 'b1': 0.5012532612779295}
2023-07-02 10:34:48,314 [prior] Evaluating prior at array([0.31430818, 0.50125326])
2023-07-02 10:34:48,314 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:48,314 [model] Got input parameters: {'Omega_m': 0.3143081785691022, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5012532612779295, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:48,314 [classy] Got parameters {'Omega_m': 0.3143081785691022, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:48,314 [classy] Computing new state
2023-07-02 10:34:48,314 [classy] Setting parameters: {'Omega_m': 0.3143081785691022, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:48,360 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.041180223444}
2023-07-02 10:34:48,360 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:48,362 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000405595
2023-07-02 10:34:48,363 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5012532612779295, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:48,363 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:48,382 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.922
2023-07-02 10:34:48,382 [model] Computed derived parameters: {}
2023-07-02 10:34:48,382 [mcmc] New sample, #848:
Omega_m:0.317472, b1:0.4956267
2023-07-02 10:34:48,382 [model] Posterior to be computed for parameters {'Omega_m': 0.3143081785691022, 'b1': 0.5066477099922623}
2023-07-02 10:34:48,382 [prior] Evaluating prior at array([0.31430818, 0.50664771])
2023-07-02 10:34:48,382 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:48,382 [model] Got input parameters: {'Omega_m': 0.3143081785691022, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5066477099922623, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:48,383 [classy] Got parameters {'Omega_m': 0.3143081785691022, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:48,383 [classy] Re-using computed results
2023-07-02 10:34:48,383 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.041180223444}
2023-07-02 10:34:48,383 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:48,383 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5066477099922623, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:48,383 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:48,402 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.85345
2023-07-02 10:34:48,402 [model] Computed derived parameters: {}
2023-07-02 10:34:48,402 [mcmc] New sample, #849:
Omega_m:0.3143082, b1:0.5012533
2023-07-02 10:34:48,402 [model] Posterior to be computed for parameters {'Omega_m': 0.32723143762514656, 'b1': 0.48366510988420214}
2023-07-02 10:34:48,402 [prior] Evaluating prior at array([0.32723144, 0.48366511])
2023-07-02 10:34:48,402 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:48,402 [model] Got input parameters: {'Omega_m': 0.32723143762514656, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48366510988420214, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:48,402 [classy] Got parameters {'Omega_m': 0.32723143762514656, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:48,402 [classy] Computing new state
2023-07-02 10:34:48,402 [classy] Setting parameters: {'Omega_m': 0.32723143762514656, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:48,448 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.5218862726905}
2023-07-02 10:34:48,449 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:48,450 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0130648
2023-07-02 10:34:48,450 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48366510988420214, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:48,450 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:48,470 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.06921
2023-07-02 10:34:48,470 [model] Computed derived parameters: {}
2023-07-02 10:34:48,471 [model] Posterior to be computed for parameters {'Omega_m': 0.3143081785691022, 'b1': 0.45797125188107785}
2023-07-02 10:34:48,471 [prior] Evaluating prior at array([0.31430818, 0.45797125])
2023-07-02 10:34:48,471 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:48,471 [model] Got input parameters: {'Omega_m': 0.3143081785691022, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45797125188107785, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:48,471 [classy] Got parameters {'Omega_m': 0.3143081785691022, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:48,471 [classy] Re-using computed results
2023-07-02 10:34:48,471 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.041180223444}
2023-07-02 10:34:48,471 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:48,471 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45797125188107785, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:48,471 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:48,490 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.98598
2023-07-02 10:34:48,490 [model] Computed derived parameters: {}
2023-07-02 10:34:48,490 [model] Posterior to be computed for parameters {'Omega_m': 0.35912640677829033, 'b1': 0.42694340227726757}
2023-07-02 10:34:48,491 [prior] Evaluating prior at array([0.35912641, 0.4269434 ])
2023-07-02 10:34:48,491 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:48,491 [model] Got input parameters: {'Omega_m': 0.35912640677829033, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42694340227726757, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:48,491 [classy] Got parameters {'Omega_m': 0.35912640677829033, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:48,491 [classy] Computing new state
2023-07-02 10:34:48,491 [classy] Setting parameters: {'Omega_m': 0.35912640677829033, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:48,537 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.99259201442393}
2023-07-02 10:34:48,537 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:48,539 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.119575
2023-07-02 10:34:48,539 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42694340227726757, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:48,539 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:48,558 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.18388
2023-07-02 10:34:48,558 [model] Computed derived parameters: {}
2023-07-02 10:34:48,559 [model] Posterior to be computed for parameters {'Omega_m': 0.3143081785691022, 'b1': 0.4935075616414551}
2023-07-02 10:34:48,559 [prior] Evaluating prior at array([0.31430818, 0.49350756])
2023-07-02 10:34:48,559 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:48,559 [model] Got input parameters: {'Omega_m': 0.3143081785691022, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4935075616414551, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:48,559 [classy] Got parameters {'Omega_m': 0.3143081785691022, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:48,559 [classy] Re-using computed results
2023-07-02 10:34:48,559 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.041180223444}
2023-07-02 10:34:48,559 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:48,559 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4935075616414551, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:48,559 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:48,579 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.74714
2023-07-02 10:34:48,579 [model] Computed derived parameters: {}
2023-07-02 10:34:48,579 [mcmc] New sample, #850:
Omega_m:0.3143082, b1:0.5066477
2023-07-02 10:34:48,579 [model] Posterior to be computed for parameters {'Omega_m': 0.3035474520177017, 'b1': 0.5126443346590441}
2023-07-02 10:34:48,579 [prior] Evaluating prior at array([0.30354745, 0.51264433])
2023-07-02 10:34:48,579 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:48,579 [model] Got input parameters: {'Omega_m': 0.3035474520177017, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5126443346590441, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:48,579 [classy] Got parameters {'Omega_m': 0.3035474520177017, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:48,579 [classy] Computing new state
2023-07-02 10:34:48,579 [classy] Setting parameters: {'Omega_m': 0.3035474520177017, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:48,625 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.34928096773456}
2023-07-02 10:34:48,625 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:48,627 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00521066
2023-07-02 10:34:48,627 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5126443346590441, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:48,627 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:48,647 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.9351
2023-07-02 10:34:48,647 [model] Computed derived parameters: {}
2023-07-02 10:34:48,647 [mcmc] New sample, #851:
Omega_m:0.3143082, b1:0.4935076
2023-07-02 10:34:48,647 [model] Posterior to be computed for parameters {'Omega_m': 0.3035474520177017, 'b1': 0.5002412882166071}
2023-07-02 10:34:48,647 [prior] Evaluating prior at array([0.30354745, 0.50024129])
2023-07-02 10:34:48,647 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:48,647 [model] Got input parameters: {'Omega_m': 0.3035474520177017, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5002412882166071, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:48,647 [classy] Got parameters {'Omega_m': 0.3035474520177017, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:48,647 [classy] Re-using computed results
2023-07-02 10:34:48,647 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.34928096773456}
2023-07-02 10:34:48,647 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:48,647 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5002412882166071, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:48,647 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:48,667 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.985486
2023-07-02 10:34:48,667 [model] Computed derived parameters: {}
2023-07-02 10:34:48,667 [model] Posterior to be computed for parameters {'Omega_m': 0.2991481277164094, 'b1': 0.520468050853527}
2023-07-02 10:34:48,667 [prior] Evaluating prior at array([0.29914813, 0.52046805])
2023-07-02 10:34:48,668 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:48,668 [model] Got input parameters: {'Omega_m': 0.2991481277164094, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.520468050853527, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:48,668 [classy] Got parameters {'Omega_m': 0.2991481277164094, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:48,668 [classy] Computing new state
2023-07-02 10:34:48,668 [classy] Setting parameters: {'Omega_m': 0.2991481277164094, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:48,714 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.89585662271068}
2023-07-02 10:34:48,714 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:48,716 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0114805
2023-07-02 10:34:48,716 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.520468050853527, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:48,716 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:48,736 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.18113
2023-07-02 10:34:48,736 [model] Computed derived parameters: {}
2023-07-02 10:34:48,736 [mcmc] New sample, #852:
Omega_m:0.3035475, b1:0.5126443
2023-07-02 10:34:48,736 [model] Posterior to be computed for parameters {'Omega_m': 0.2991481277164094, 'b1': 0.4563736950417163}
2023-07-02 10:34:48,736 [prior] Evaluating prior at array([0.29914813, 0.4563737 ])
2023-07-02 10:34:48,736 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:48,736 [model] Got input parameters: {'Omega_m': 0.2991481277164094, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4563736950417163, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:48,736 [classy] Got parameters {'Omega_m': 0.2991481277164094, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:48,736 [classy] Re-using computed results
2023-07-02 10:34:48,736 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.89585662271068}
2023-07-02 10:34:48,736 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:48,736 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4563736950417163, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:48,736 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:48,755 [fs_likelihood.fslikelihood] Computed log-likelihood = -11.6734
2023-07-02 10:34:48,755 [model] Computed derived parameters: {}
2023-07-02 10:34:48,755 [model] Posterior to be computed for parameters {'Omega_m': 0.3077918522839015, 'b1': 0.5050961338844887}
2023-07-02 10:34:48,756 [prior] Evaluating prior at array([0.30779185, 0.50509613])
2023-07-02 10:34:48,756 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:48,756 [model] Got input parameters: {'Omega_m': 0.3077918522839015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5050961338844887, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:48,756 [classy] Got parameters {'Omega_m': 0.3077918522839015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:48,756 [classy] Computing new state
2023-07-02 10:34:48,756 [classy] Setting parameters: {'Omega_m': 0.3077918522839015, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:48,802 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.8285176441322}
2023-07-02 10:34:48,802 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:48,804 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00156845
2023-07-02 10:34:48,804 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5050961338844887, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:48,804 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:48,824 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.42439
2023-07-02 10:34:48,824 [model] Computed derived parameters: {}
2023-07-02 10:34:48,824 [mcmc] New sample, #853:
Omega_m:0.2991481, b1:0.5204681
2023-07-02 10:34:48,824 [model] Posterior to be computed for parameters {'Omega_m': 0.3077918522839015, 'b1': 0.5211063072151036}
2023-07-02 10:34:48,824 [prior] Evaluating prior at array([0.30779185, 0.52110631])
2023-07-02 10:34:48,824 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:48,824 [model] Got input parameters: {'Omega_m': 0.3077918522839015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5211063072151036, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:48,825 [classy] Got parameters {'Omega_m': 0.3077918522839015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:48,825 [classy] Re-using computed results
2023-07-02 10:34:48,825 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.8285176441322}
2023-07-02 10:34:48,825 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:48,825 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5211063072151036, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:48,825 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:48,844 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.45049
2023-07-02 10:34:48,844 [model] Computed derived parameters: {}
2023-07-02 10:34:48,844 [mcmc] New sample, #854:
Omega_m:0.3077919, b1:0.5050961
2023-07-02 10:34:48,844 [model] Posterior to be computed for parameters {'Omega_m': 0.37910410519323506, 'b1': 0.3942852797705202}
2023-07-02 10:34:48,844 [prior] Evaluating prior at array([0.37910411, 0.39428528])
2023-07-02 10:34:48,844 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:48,844 [model] Got input parameters: {'Omega_m': 0.37910410519323506, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.3942852797705202, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:48,844 [classy] Got parameters {'Omega_m': 0.37910410519323506, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:48,844 [classy] Computing new state
2023-07-02 10:34:48,844 [classy] Setting parameters: {'Omega_m': 0.37910410519323506, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:48,891 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 139.92635743321486}
2023-07-02 10:34:48,891 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:48,893 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.23305
2023-07-02 10:34:48,893 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.3942852797705202, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:48,893 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:48,913 [fs_likelihood.fslikelihood] Computed log-likelihood = -14.7838
2023-07-02 10:34:48,913 [model] Computed derived parameters: {}
2023-07-02 10:34:48,913 [model] Posterior to be computed for parameters {'Omega_m': 0.3077918522839015, 'b1': 0.5057991659602125}
2023-07-02 10:34:48,913 [prior] Evaluating prior at array([0.30779185, 0.50579917])
2023-07-02 10:34:48,913 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:48,913 [model] Got input parameters: {'Omega_m': 0.3077918522839015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5057991659602125, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:48,913 [classy] Got parameters {'Omega_m': 0.3077918522839015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:48,913 [classy] Re-using computed results
2023-07-02 10:34:48,913 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.8285176441322}
2023-07-02 10:34:48,913 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:48,913 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5057991659602125, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:48,913 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:48,933 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.4541
2023-07-02 10:34:48,933 [model] Computed derived parameters: {}
2023-07-02 10:34:48,933 [mcmc] New sample, #855:
Omega_m:0.3077919, b1:0.5211063
2023-07-02 10:34:48,933 [model] Posterior to be computed for parameters {'Omega_m': 0.29508295484762087, 'b1': 0.5284005474171428}
2023-07-02 10:34:48,933 [prior] Evaluating prior at array([0.29508295, 0.52840055])
2023-07-02 10:34:48,933 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:48,933 [model] Got input parameters: {'Omega_m': 0.29508295484762087, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5284005474171428, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:48,933 [classy] Got parameters {'Omega_m': 0.29508295484762087, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:48,933 [classy] Computing new state
2023-07-02 10:34:48,933 [classy] Setting parameters: {'Omega_m': 0.29508295484762087, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:48,980 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.40723801759458}
2023-07-02 10:34:48,980 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:48,982 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0196062
2023-07-02 10:34:48,982 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5284005474171428, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:48,982 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:49,001 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.280668
2023-07-02 10:34:49,001 [model] Computed derived parameters: {}
2023-07-02 10:34:49,001 [model] Posterior to be computed for parameters {'Omega_m': 0.3077918522839015, 'b1': 0.4559757099326681}
2023-07-02 10:34:49,001 [prior] Evaluating prior at array([0.30779185, 0.45597571])
2023-07-02 10:34:49,001 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:49,001 [model] Got input parameters: {'Omega_m': 0.3077918522839015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4559757099326681, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:49,001 [classy] Got parameters {'Omega_m': 0.3077918522839015, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:49,001 [classy] Re-using computed results
2023-07-02 10:34:49,001 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.8285176441322}
2023-07-02 10:34:49,002 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:49,002 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4559757099326681, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:49,002 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:49,022 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.73246
2023-07-02 10:34:49,022 [model] Computed derived parameters: {}
2023-07-02 10:34:49,022 [model] Posterior to be computed for parameters {'Omega_m': 0.31343397206962964, 'b1': 0.4957652741814575}
2023-07-02 10:34:49,022 [prior] Evaluating prior at array([0.31343397, 0.49576527])
2023-07-02 10:34:49,022 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:49,022 [model] Got input parameters: {'Omega_m': 0.31343397206962964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4957652741814575, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:49,022 [classy] Got parameters {'Omega_m': 0.31343397206962964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:49,022 [classy] Computing new state
2023-07-02 10:34:49,022 [classy] Setting parameters: {'Omega_m': 0.31343397206962964, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:49,069 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.14596598929367}
2023-07-02 10:34:49,069 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:49,070 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000257606
2023-07-02 10:34:49,071 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4957652741814575, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:49,071 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:49,090 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.76188
2023-07-02 10:34:49,090 [model] Computed derived parameters: {}
2023-07-02 10:34:49,090 [mcmc] New sample, #856:
Omega_m:0.3077919, b1:0.5057992
2023-07-02 10:34:49,090 [model] Posterior to be computed for parameters {'Omega_m': 0.31343397206962964, 'b1': 0.46923495932215875}
2023-07-02 10:34:49,090 [prior] Evaluating prior at array([0.31343397, 0.46923496])
2023-07-02 10:34:49,090 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:49,091 [model] Got input parameters: {'Omega_m': 0.31343397206962964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46923495932215875, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:49,091 [classy] Got parameters {'Omega_m': 0.31343397206962964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:49,091 [classy] Re-using computed results
2023-07-02 10:34:49,091 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.14596598929367}
2023-07-02 10:34:49,091 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:49,091 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46923495932215875, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:49,091 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:49,110 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.0903208
2023-07-02 10:34:49,110 [model] Computed derived parameters: {}
2023-07-02 10:34:49,110 [model] Posterior to be computed for parameters {'Omega_m': 0.2762907563735879, 'b1': 0.5618204131651714}
2023-07-02 10:34:49,110 [prior] Evaluating prior at array([0.27629076, 0.56182041])
2023-07-02 10:34:49,110 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:49,111 [model] Got input parameters: {'Omega_m': 0.2762907563735879, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5618204131651714, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:49,111 [classy] Got parameters {'Omega_m': 0.2762907563735879, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:49,111 [classy] Computing new state
2023-07-02 10:34:49,111 [classy] Setting parameters: {'Omega_m': 0.2762907563735879, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:49,158 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.85357714959466}
2023-07-02 10:34:49,158 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:49,160 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0883891
2023-07-02 10:34:49,160 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5618204131651714, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:49,160 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:49,181 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.27767
2023-07-02 10:34:49,181 [model] Computed derived parameters: {}
2023-07-02 10:34:49,181 [model] Posterior to be computed for parameters {'Omega_m': 0.31343397206962964, 'b1': 0.5104951518761213}
2023-07-02 10:34:49,181 [prior] Evaluating prior at array([0.31343397, 0.51049515])
2023-07-02 10:34:49,181 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:49,181 [model] Got input parameters: {'Omega_m': 0.31343397206962964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5104951518761213, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:49,181 [classy] Got parameters {'Omega_m': 0.31343397206962964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:49,181 [classy] Re-using computed results
2023-07-02 10:34:49,181 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.14596598929367}
2023-07-02 10:34:49,181 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:49,181 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5104951518761213, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:49,182 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:49,201 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.76458
2023-07-02 10:34:49,201 [model] Computed derived parameters: {}
2023-07-02 10:34:49,201 [mcmc] New sample, #857:
Omega_m:0.313434, b1:0.4957653
2023-07-02 10:34:49,201 [model] Posterior to be computed for parameters {'Omega_m': 0.25648385931008455, 'b1': 0.6117746868591633}
2023-07-02 10:34:49,201 [prior] Evaluating prior at array([0.25648386, 0.61177469])
2023-07-02 10:34:49,202 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:49,202 [model] Got input parameters: {'Omega_m': 0.25648385931008455, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6117746868591633, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:49,202 [classy] Got parameters {'Omega_m': 0.25648385931008455, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:49,202 [classy] Computing new state
2023-07-02 10:34:49,202 [classy] Setting parameters: {'Omega_m': 0.25648385931008455, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:49,248 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 154.59068601990776}
2023-07-02 10:34:49,248 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:49,250 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.223064
2023-07-02 10:34:49,250 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6117746868591633, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:49,250 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:49,270 [fs_likelihood.fslikelihood] Computed log-likelihood = -21.9196
2023-07-02 10:34:49,270 [model] Computed derived parameters: {}
2023-07-02 10:34:49,271 [model] Posterior to be computed for parameters {'Omega_m': 0.31343397206962964, 'b1': 0.4263976387719794}
2023-07-02 10:34:49,271 [prior] Evaluating prior at array([0.31343397, 0.42639764])
2023-07-02 10:34:49,271 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:49,271 [model] Got input parameters: {'Omega_m': 0.31343397206962964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4263976387719794, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:49,271 [classy] Got parameters {'Omega_m': 0.31343397206962964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:49,271 [classy] Re-using computed results
2023-07-02 10:34:49,271 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.14596598929367}
2023-07-02 10:34:49,271 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:49,271 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4263976387719794, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:49,271 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:49,290 [fs_likelihood.fslikelihood] Computed log-likelihood = -11.7765
2023-07-02 10:34:49,291 [model] Computed derived parameters: {}
2023-07-02 10:34:49,291 [model] Posterior to be computed for parameters {'Omega_m': 0.2692154022216236, 'b1': 0.5891330329059636}
2023-07-02 10:34:49,291 [prior] Evaluating prior at array([0.2692154 , 0.58913303])
2023-07-02 10:34:49,291 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:49,291 [model] Got input parameters: {'Omega_m': 0.2692154022216236, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5891330329059636, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:49,291 [classy] Got parameters {'Omega_m': 0.2692154022216236, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:49,291 [classy] Computing new state
2023-07-02 10:34:49,291 [classy] Setting parameters: {'Omega_m': 0.2692154022216236, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:49,338 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.811721065736}
2023-07-02 10:34:49,338 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:49,340 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.128665
2023-07-02 10:34:49,340 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5891330329059636, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:49,340 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:49,359 [fs_likelihood.fslikelihood] Computed log-likelihood = -11.5696
2023-07-02 10:34:49,359 [model] Computed derived parameters: {}
2023-07-02 10:34:49,359 [model] Posterior to be computed for parameters {'Omega_m': 0.31343397206962964, 'b1': 0.49831227120806043}
2023-07-02 10:34:49,359 [prior] Evaluating prior at array([0.31343397, 0.49831227])
2023-07-02 10:34:49,360 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:49,360 [model] Got input parameters: {'Omega_m': 0.31343397206962964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49831227120806043, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:49,360 [classy] Got parameters {'Omega_m': 0.31343397206962964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:49,360 [classy] Re-using computed results
2023-07-02 10:34:49,360 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.14596598929367}
2023-07-02 10:34:49,360 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:49,360 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49831227120806043, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:49,360 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:49,382 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.84546
2023-07-02 10:34:49,382 [model] Computed derived parameters: {}
2023-07-02 10:34:49,382 [mcmc] New sample, #858:
Omega_m:0.313434, b1:0.5104952
2023-07-02 10:34:49,382 [model] Posterior to be computed for parameters {'Omega_m': 0.30144081557143426, 'b1': 0.5196407858370766}
2023-07-02 10:34:49,382 [prior] Evaluating prior at array([0.30144082, 0.51964079])
2023-07-02 10:34:49,382 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:49,382 [model] Got input parameters: {'Omega_m': 0.30144081557143426, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5196407858370766, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:49,383 [classy] Got parameters {'Omega_m': 0.30144081557143426, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:49,383 [classy] Computing new state
2023-07-02 10:34:49,383 [classy] Setting parameters: {'Omega_m': 0.30144081557143426, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:49,429 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.61012596652807}
2023-07-02 10:34:49,429 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:49,431 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00789082
2023-07-02 10:34:49,431 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5196407858370766, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:49,431 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:49,451 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.72515
2023-07-02 10:34:49,451 [model] Computed derived parameters: {}
2023-07-02 10:34:49,451 [mcmc] New sample, #859:
Omega_m:0.313434, b1:0.4983123
2023-07-02 10:34:49,451 [model] Posterior to be computed for parameters {'Omega_m': 0.30144081557143426, 'b1': 0.5019421168539557}
2023-07-02 10:34:49,451 [prior] Evaluating prior at array([0.30144082, 0.50194212])
2023-07-02 10:34:49,451 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:49,451 [model] Got input parameters: {'Omega_m': 0.30144081557143426, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5019421168539557, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:49,451 [classy] Got parameters {'Omega_m': 0.30144081557143426, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:49,451 [classy] Re-using computed results
2023-07-02 10:34:49,451 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.61012596652807}
2023-07-02 10:34:49,451 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:49,451 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5019421168539557, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:49,451 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:49,471 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.42211
2023-07-02 10:34:49,471 [model] Computed derived parameters: {}
2023-07-02 10:34:49,471 [model] Posterior to be computed for parameters {'Omega_m': 0.31278804471287586, 'b1': 0.4994609822317079}
2023-07-02 10:34:49,471 [prior] Evaluating prior at array([0.31278804, 0.49946098])
2023-07-02 10:34:49,472 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:49,472 [model] Got input parameters: {'Omega_m': 0.31278804471287586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4994609822317079, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:49,472 [classy] Got parameters {'Omega_m': 0.31278804471287586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:49,472 [classy] Computing new state
2023-07-02 10:34:49,472 [classy] Setting parameters: {'Omega_m': 0.31278804471287586, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:49,518 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.22355480831817}
2023-07-02 10:34:49,518 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:49,520 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000208038
2023-07-02 10:34:49,520 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4994609822317079, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:49,520 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:49,540 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.82955
2023-07-02 10:34:49,540 [model] Computed derived parameters: {}
2023-07-02 10:34:49,540 [mcmc] New sample, #860:
Omega_m:0.3014408, b1:0.5196408
2023-07-02 10:34:49,540 [model] Posterior to be computed for parameters {'Omega_m': 0.31278804471287586, 'b1': 0.5420494118386683}
2023-07-02 10:34:49,540 [prior] Evaluating prior at array([0.31278804, 0.54204941])
2023-07-02 10:34:49,540 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:49,540 [model] Got input parameters: {'Omega_m': 0.31278804471287586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5420494118386683, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:49,540 [classy] Got parameters {'Omega_m': 0.31278804471287586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:49,540 [classy] Re-using computed results
2023-07-02 10:34:49,540 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.22355480831817}
2023-07-02 10:34:49,540 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:49,540 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5420494118386683, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:49,540 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:49,560 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.07295
2023-07-02 10:34:49,560 [model] Computed derived parameters: {}
2023-07-02 10:34:49,560 [model] Posterior to be computed for parameters {'Omega_m': 0.35253862110303025, 'b1': 0.42876893796656346}
2023-07-02 10:34:49,560 [prior] Evaluating prior at array([0.35253862, 0.42876894])
2023-07-02 10:34:49,560 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:49,560 [model] Got input parameters: {'Omega_m': 0.35253862110303025, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42876893796656346, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:49,560 [classy] Got parameters {'Omega_m': 0.35253862110303025, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:49,560 [classy] Computing new state
2023-07-02 10:34:49,560 [classy] Setting parameters: {'Omega_m': 0.35253862110303025, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:49,607 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.69740235943615}
2023-07-02 10:34:49,608 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:49,609 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0895757
2023-07-02 10:34:49,609 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42876893796656346, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:49,610 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:49,629 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.80469
2023-07-02 10:34:49,630 [model] Computed derived parameters: {}
2023-07-02 10:34:49,630 [model] Posterior to be computed for parameters {'Omega_m': 0.31278804471287586, 'b1': 0.5105933358035578}
2023-07-02 10:34:49,630 [prior] Evaluating prior at array([0.31278804, 0.51059334])
2023-07-02 10:34:49,630 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:49,630 [model] Got input parameters: {'Omega_m': 0.31278804471287586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5105933358035578, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:49,630 [classy] Got parameters {'Omega_m': 0.31278804471287586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:49,630 [classy] Re-using computed results
2023-07-02 10:34:49,630 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.22355480831817}
2023-07-02 10:34:49,630 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:49,630 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5105933358035578, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:49,630 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:49,649 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.78888
2023-07-02 10:34:49,649 [model] Computed derived parameters: {}
2023-07-02 10:34:49,649 [mcmc] New sample, #861:
Omega_m:0.312788, b1:0.499461
2023-07-02 10:34:49,649 [model] Posterior to be computed for parameters {'Omega_m': 0.25501858851183784, 'b1': 0.6133299833141233}
2023-07-02 10:34:49,650 [prior] Evaluating prior at array([0.25501859, 0.61332998])
2023-07-02 10:34:49,650 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:49,650 [model] Got input parameters: {'Omega_m': 0.25501858851183784, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6133299833141233, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:49,650 [classy] Got parameters {'Omega_m': 0.25501858851183784, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:49,650 [classy] Computing new state
2023-07-02 10:34:49,650 [classy] Setting parameters: {'Omega_m': 0.25501858851183784, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:49,698 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 154.80014580770938}
2023-07-02 10:34:49,699 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:49,700 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.235843
2023-07-02 10:34:49,701 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6133299833141233, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:49,701 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:49,720 [fs_likelihood.fslikelihood] Computed log-likelihood = -23.2995
2023-07-02 10:34:49,720 [model] Computed derived parameters: {}
2023-07-02 10:34:49,720 [model] Posterior to be computed for parameters {'Omega_m': 0.31278804471287586, 'b1': 0.5016276478959882}
2023-07-02 10:34:49,720 [prior] Evaluating prior at array([0.31278804, 0.50162765])
2023-07-02 10:34:49,720 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:49,720 [model] Got input parameters: {'Omega_m': 0.31278804471287586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5016276478959882, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:49,720 [classy] Got parameters {'Omega_m': 0.31278804471287586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:49,720 [classy] Re-using computed results
2023-07-02 10:34:49,720 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.22355480831817}
2023-07-02 10:34:49,721 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:49,721 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5016276478959882, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:49,721 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:49,741 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.87383
2023-07-02 10:34:49,741 [model] Computed derived parameters: {}
2023-07-02 10:34:49,741 [mcmc] New sample, #862:
Omega_m:0.312788, b1:0.5105933
2023-07-02 10:34:49,741 [model] Posterior to be computed for parameters {'Omega_m': 0.32660753010044036, 'b1': 0.47705120746527296}
2023-07-02 10:34:49,741 [prior] Evaluating prior at array([0.32660753, 0.47705121])
2023-07-02 10:34:49,741 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:49,741 [model] Got input parameters: {'Omega_m': 0.32660753010044036, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47705120746527296, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:49,742 [classy] Got parameters {'Omega_m': 0.32660753010044036, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:49,742 [classy] Computing new state
2023-07-02 10:34:49,742 [classy] Setting parameters: {'Omega_m': 0.32660753010044036, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:49,790 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.5939923405736}
2023-07-02 10:34:49,790 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:49,792 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0120172
2023-07-02 10:34:49,792 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47705120746527296, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:49,792 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:49,811 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.21487
2023-07-02 10:34:49,811 [model] Computed derived parameters: {}
2023-07-02 10:34:49,811 [model] Posterior to be computed for parameters {'Omega_m': 0.31278804471287586, 'b1': 0.512498170869073}
2023-07-02 10:34:49,811 [prior] Evaluating prior at array([0.31278804, 0.51249817])
2023-07-02 10:34:49,812 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:49,812 [model] Got input parameters: {'Omega_m': 0.31278804471287586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.512498170869073, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:49,812 [classy] Got parameters {'Omega_m': 0.31278804471287586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:49,812 [classy] Re-using computed results
2023-07-02 10:34:49,812 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.22355480831817}
2023-07-02 10:34:49,812 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:49,812 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.512498170869073, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:49,812 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:49,831 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.71448
2023-07-02 10:34:49,831 [model] Computed derived parameters: {}
2023-07-02 10:34:49,832 [mcmc] New sample, #863:
Omega_m:0.312788, b1:0.5016276
2023-07-02 10:34:49,832 [model] Posterior to be computed for parameters {'Omega_m': 0.2895232767840174, 'b1': 0.5538720112909825}
2023-07-02 10:34:49,832 [prior] Evaluating prior at array([0.28952328, 0.55387201])
2023-07-02 10:34:49,832 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:49,832 [model] Got input parameters: {'Omega_m': 0.2895232767840174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5538720112909825, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:49,832 [classy] Got parameters {'Omega_m': 0.2895232767840174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:49,832 [classy] Computing new state
2023-07-02 10:34:49,832 [classy] Setting parameters: {'Omega_m': 0.2895232767840174, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:49,878 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.11661649397863}
2023-07-02 10:34:49,878 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:49,880 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0344753
2023-07-02 10:34:49,880 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5538720112909825, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:49,880 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:49,899 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.33972
2023-07-02 10:34:49,899 [model] Computed derived parameters: {}
2023-07-02 10:34:49,900 [model] Posterior to be computed for parameters {'Omega_m': 0.31278804471287586, 'b1': 0.5004772375468736}
2023-07-02 10:34:49,900 [prior] Evaluating prior at array([0.31278804, 0.50047724])
2023-07-02 10:34:49,900 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:49,900 [model] Got input parameters: {'Omega_m': 0.31278804471287586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5004772375468736, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:49,900 [classy] Got parameters {'Omega_m': 0.31278804471287586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:49,900 [classy] Re-using computed results
2023-07-02 10:34:49,900 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.22355480831817}
2023-07-02 10:34:49,900 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:49,900 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5004772375468736, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:49,900 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:49,919 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.85343
2023-07-02 10:34:49,919 [model] Computed derived parameters: {}
2023-07-02 10:34:49,919 [mcmc] New sample, #864:
Omega_m:0.312788, b1:0.5124982
2023-07-02 10:34:49,919 [model] Posterior to be computed for parameters {'Omega_m': 0.3475050559084089, 'b1': 0.4387368374052543}
2023-07-02 10:34:49,919 [prior] Evaluating prior at array([0.34750506, 0.43873684])
2023-07-02 10:34:49,919 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:49,919 [model] Got input parameters: {'Omega_m': 0.3475050559084089, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4387368374052543, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:49,919 [classy] Got parameters {'Omega_m': 0.3475050559084089, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:49,919 [classy] Computing new state
2023-07-02 10:34:49,919 [classy] Setting parameters: {'Omega_m': 0.3475050559084089, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:49,965 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.24411330120034}
2023-07-02 10:34:49,965 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:49,967 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.069328
2023-07-02 10:34:49,967 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4387368374052543, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:49,967 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:49,987 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.21405
2023-07-02 10:34:49,988 [model] Computed derived parameters: {}
2023-07-02 10:34:49,988 [model] Posterior to be computed for parameters {'Omega_m': 0.31278804471287586, 'b1': 0.49367629884032677}
2023-07-02 10:34:49,988 [prior] Evaluating prior at array([0.31278804, 0.4936763 ])
2023-07-02 10:34:49,988 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:49,988 [model] Got input parameters: {'Omega_m': 0.31278804471287586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49367629884032677, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:49,988 [classy] Got parameters {'Omega_m': 0.31278804471287586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:49,988 [classy] Re-using computed results
2023-07-02 10:34:49,988 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.22355480831817}
2023-07-02 10:34:49,988 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:49,988 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49367629884032677, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:49,988 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:50,007 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.58987
2023-07-02 10:34:50,007 [model] Computed derived parameters: {}
2023-07-02 10:34:50,007 [mcmc] New sample, #865:
Omega_m:0.312788, b1:0.5004772
2023-07-02 10:34:50,008 [model] Posterior to be computed for parameters {'Omega_m': 0.27391495127361065, 'b1': 0.5628078358313796}
2023-07-02 10:34:50,008 [prior] Evaluating prior at array([0.27391495, 0.56280784])
2023-07-02 10:34:50,008 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:50,008 [model] Got input parameters: {'Omega_m': 0.27391495127361065, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5628078358313796, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:50,008 [classy] Got parameters {'Omega_m': 0.27391495127361065, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:50,008 [classy] Computing new state
2023-07-02 10:34:50,008 [classy] Setting parameters: {'Omega_m': 0.27391495127361065, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:50,054 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.1729421040516}
2023-07-02 10:34:50,054 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:50,056 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.100986
2023-07-02 10:34:50,056 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5628078358313796, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:50,056 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:50,075 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.82013
2023-07-02 10:34:50,075 [model] Computed derived parameters: {}
2023-07-02 10:34:50,076 [model] Posterior to be computed for parameters {'Omega_m': 0.31278804471287586, 'b1': 0.5304375458353453}
2023-07-02 10:34:50,076 [prior] Evaluating prior at array([0.31278804, 0.53043755])
2023-07-02 10:34:50,076 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:50,076 [model] Got input parameters: {'Omega_m': 0.31278804471287586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5304375458353453, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:50,076 [classy] Got parameters {'Omega_m': 0.31278804471287586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:50,076 [classy] Re-using computed results
2023-07-02 10:34:50,076 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.22355480831817}
2023-07-02 10:34:50,076 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:50,076 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5304375458353453, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:50,076 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:50,096 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.0168
2023-07-02 10:34:50,096 [model] Computed derived parameters: {}
2023-07-02 10:34:50,096 [model] Posterior to be computed for parameters {'Omega_m': 0.2924143879655001, 'b1': 0.5299086148322296}
2023-07-02 10:34:50,096 [prior] Evaluating prior at array([0.29241439, 0.52990861])
2023-07-02 10:34:50,097 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:50,097 [model] Got input parameters: {'Omega_m': 0.2924143879655001, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5299086148322296, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:50,097 [classy] Got parameters {'Omega_m': 0.2924143879655001, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:50,097 [classy] Computing new state
2023-07-02 10:34:50,097 [classy] Setting parameters: {'Omega_m': 0.2924143879655001, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:50,145 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.74627076601556}
2023-07-02 10:34:50,145 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:50,147 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0261923
2023-07-02 10:34:50,147 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5299086148322296, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:50,147 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:50,167 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.623396
2023-07-02 10:34:50,167 [model] Computed derived parameters: {}
2023-07-02 10:34:50,167 [model] Posterior to be computed for parameters {'Omega_m': 0.31278804471287586, 'b1': 0.4649819660309183}
2023-07-02 10:34:50,167 [prior] Evaluating prior at array([0.31278804, 0.46498197])
2023-07-02 10:34:50,167 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:50,167 [model] Got input parameters: {'Omega_m': 0.31278804471287586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4649819660309183, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:50,167 [classy] Got parameters {'Omega_m': 0.31278804471287586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:50,167 [classy] Re-using computed results
2023-07-02 10:34:50,167 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.22355480831817}
2023-07-02 10:34:50,167 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:50,167 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4649819660309183, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:50,167 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:50,187 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.11623
2023-07-02 10:34:50,188 [model] Computed derived parameters: {}
2023-07-02 10:34:50,188 [model] Posterior to be computed for parameters {'Omega_m': 0.32429783700641773, 'b1': 0.4732073944825221}
2023-07-02 10:34:50,188 [prior] Evaluating prior at array([0.32429784, 0.47320739])
2023-07-02 10:34:50,188 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:50,188 [model] Got input parameters: {'Omega_m': 0.32429783700641773, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4732073944825221, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:50,188 [classy] Got parameters {'Omega_m': 0.32429783700641773, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:50,188 [classy] Computing new state
2023-07-02 10:34:50,188 [classy] Setting parameters: {'Omega_m': 0.32429783700641773, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:50,234 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.86200763867814}
2023-07-02 10:34:50,234 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:50,236 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0085151
2023-07-02 10:34:50,236 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4732073944825221, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:50,236 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:50,255 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.19418
2023-07-02 10:34:50,256 [model] Computed derived parameters: {}
2023-07-02 10:34:50,256 [mcmc] New sample, #866:
Omega_m:0.312788, b1:0.4936763
2023-07-02 10:34:50,256 [model] Posterior to be computed for parameters {'Omega_m': 0.32429783700641773, 'b1': 0.44930415750401115}
2023-07-02 10:34:50,256 [prior] Evaluating prior at array([0.32429784, 0.44930416])
2023-07-02 10:34:50,256 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:50,256 [model] Got input parameters: {'Omega_m': 0.32429783700641773, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44930415750401115, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:50,256 [classy] Got parameters {'Omega_m': 0.32429783700641773, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:50,256 [classy] Re-using computed results
2023-07-02 10:34:50,256 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.86200763867814}
2023-07-02 10:34:50,256 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:50,256 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44930415750401115, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:50,256 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:50,276 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.589511
2023-07-02 10:34:50,276 [model] Computed derived parameters: {}
2023-07-02 10:34:50,276 [model] Posterior to be computed for parameters {'Omega_m': 0.3283702970302716, 'b1': 0.46596497058786845}
2023-07-02 10:34:50,276 [prior] Evaluating prior at array([0.3283703 , 0.46596497])
2023-07-02 10:34:50,276 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:50,276 [model] Got input parameters: {'Omega_m': 0.3283702970302716, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46596497058786845, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:50,276 [classy] Got parameters {'Omega_m': 0.3283702970302716, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:50,276 [classy] Computing new state
2023-07-02 10:34:50,276 [classy] Setting parameters: {'Omega_m': 0.3283702970302716, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:50,322 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.39058145608325}
2023-07-02 10:34:50,322 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:50,324 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0150874
2023-07-02 10:34:50,324 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46596497058786845, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:50,324 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:50,344 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.7257
2023-07-02 10:34:50,344 [model] Computed derived parameters: {}
2023-07-02 10:34:50,344 [model] Posterior to be computed for parameters {'Omega_m': 0.32429783700641773, 'b1': 0.4349136595346737}
2023-07-02 10:34:50,345 [prior] Evaluating prior at array([0.32429784, 0.43491366])
2023-07-02 10:34:50,345 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:50,345 [model] Got input parameters: {'Omega_m': 0.32429783700641773, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4349136595346737, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:50,345 [classy] Got parameters {'Omega_m': 0.32429783700641773, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:50,345 [classy] Re-using computed results
2023-07-02 10:34:50,345 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.86200763867814}
2023-07-02 10:34:50,345 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:50,345 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4349136595346737, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:50,345 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:50,364 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.62655
2023-07-02 10:34:50,364 [model] Computed derived parameters: {}
2023-07-02 10:34:50,365 [model] Posterior to be computed for parameters {'Omega_m': 0.37529454787122135, 'b1': 0.3825153323990051}
2023-07-02 10:34:50,365 [prior] Evaluating prior at array([0.37529455, 0.38251533])
2023-07-02 10:34:50,365 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:50,365 [model] Got input parameters: {'Omega_m': 0.37529454787122135, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.3825153323990051, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:50,365 [classy] Got parameters {'Omega_m': 0.37529454787122135, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:50,365 [classy] Computing new state
2023-07-02 10:34:50,365 [classy] Setting parameters: {'Omega_m': 0.37529454787122135, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:50,411 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.3123876785926}
2023-07-02 10:34:50,412 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:50,413 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.208937
2023-07-02 10:34:50,413 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.3825153323990051, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:50,413 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:50,434 [fs_likelihood.fslikelihood] Computed log-likelihood = -13.0468
2023-07-02 10:34:50,434 [model] Computed derived parameters: {}
2023-07-02 10:34:50,434 [model] Posterior to be computed for parameters {'Omega_m': 0.32429783700641773, 'b1': 0.3486853498920322}
2023-07-02 10:34:50,434 [prior] Evaluating prior at array([0.32429784, 0.34868535])
2023-07-02 10:34:50,434 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:50,434 [model] Got input parameters: {'Omega_m': 0.32429783700641773, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.3486853498920322, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:50,434 [classy] Got parameters {'Omega_m': 0.32429783700641773, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:50,434 [classy] Re-using computed results
2023-07-02 10:34:50,434 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.86200763867814}
2023-07-02 10:34:50,434 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:50,434 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.3486853498920322, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:50,434 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:50,454 [fs_likelihood.fslikelihood] Computed log-likelihood = -40.5337
2023-07-02 10:34:50,454 [model] Computed derived parameters: {}
2023-07-02 10:34:50,454 [model] Posterior to be computed for parameters {'Omega_m': 0.3184759319320715, 'b1': 0.48356101469631824}
2023-07-02 10:34:50,454 [prior] Evaluating prior at array([0.31847593, 0.48356101])
2023-07-02 10:34:50,454 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:50,454 [model] Got input parameters: {'Omega_m': 0.3184759319320715, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48356101469631824, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:50,454 [classy] Got parameters {'Omega_m': 0.3184759319320715, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:50,454 [classy] Computing new state
2023-07-02 10:34:50,454 [classy] Setting parameters: {'Omega_m': 0.3184759319320715, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:50,501 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.54522057195416}
2023-07-02 10:34:50,501 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:50,503 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00237144
2023-07-02 10:34:50,503 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48356101469631824, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:50,503 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:50,522 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.5731
2023-07-02 10:34:50,522 [model] Computed derived parameters: {}
2023-07-02 10:34:50,522 [mcmc] New sample, #867:
Omega_m:0.3242978, b1:0.4732074
2023-07-02 10:34:50,522 [model] Posterior to be computed for parameters {'Omega_m': 0.3184759319320715, 'b1': 0.4254161575553489}
2023-07-02 10:34:50,523 [prior] Evaluating prior at array([0.31847593, 0.42541616])
2023-07-02 10:34:50,523 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:50,523 [model] Got input parameters: {'Omega_m': 0.3184759319320715, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4254161575553489, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:50,523 [classy] Got parameters {'Omega_m': 0.3184759319320715, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:50,523 [classy] Re-using computed results
2023-07-02 10:34:50,523 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.54522057195416}
2023-07-02 10:34:50,523 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:50,523 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4254161575553489, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:50,523 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:50,543 [fs_likelihood.fslikelihood] Computed log-likelihood = -9.01279
2023-07-02 10:34:50,543 [model] Computed derived parameters: {}
2023-07-02 10:34:50,543 [model] Posterior to be computed for parameters {'Omega_m': 0.31194231564120145, 'b1': 0.49518033531980626}
2023-07-02 10:34:50,543 [prior] Evaluating prior at array([0.31194232, 0.49518034])
2023-07-02 10:34:50,543 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:50,543 [model] Got input parameters: {'Omega_m': 0.31194231564120145, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49518033531980626, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:50,543 [classy] Got parameters {'Omega_m': 0.31194231564120145, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:50,543 [classy] Computing new state
2023-07-02 10:34:50,543 [classy] Setting parameters: {'Omega_m': 0.31194231564120145, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:50,590 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.32535922724134}
2023-07-02 10:34:50,590 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:50,592 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000220381
2023-07-02 10:34:50,592 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49518033531980626, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:50,592 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:50,611 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.56095
2023-07-02 10:34:50,611 [model] Computed derived parameters: {}
2023-07-02 10:34:50,612 [mcmc] New sample, #868:
Omega_m:0.3184759, b1:0.483561
2023-07-02 10:34:50,612 [model] Posterior to be computed for parameters {'Omega_m': 0.31194231564120145, 'b1': 0.47984393237723777}
2023-07-02 10:34:50,612 [prior] Evaluating prior at array([0.31194232, 0.47984393])
2023-07-02 10:34:50,612 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:50,612 [model] Got input parameters: {'Omega_m': 0.31194231564120145, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47984393237723777, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:50,612 [classy] Got parameters {'Omega_m': 0.31194231564120145, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:50,612 [classy] Re-using computed results
2023-07-02 10:34:50,612 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.32535922724134}
2023-07-02 10:34:50,612 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:50,612 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47984393237723777, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:50,612 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:50,631 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.08874
2023-07-02 10:34:50,631 [model] Computed derived parameters: {}
2023-07-02 10:34:50,631 [model] Posterior to be computed for parameters {'Omega_m': 0.29189744042169186, 'b1': 0.5308279493920852}
2023-07-02 10:34:50,631 [prior] Evaluating prior at array([0.29189744, 0.53082795])
2023-07-02 10:34:50,631 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:50,631 [model] Got input parameters: {'Omega_m': 0.29189744042169186, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5308279493920852, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:50,631 [classy] Got parameters {'Omega_m': 0.29189744042169186, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:50,631 [classy] Computing new state
2023-07-02 10:34:50,631 [classy] Setting parameters: {'Omega_m': 0.29189744042169186, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:50,678 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.81225810598522}
2023-07-02 10:34:50,678 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:50,680 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0275851
2023-07-02 10:34:50,680 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5308279493920852, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:50,680 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:50,700 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.778829
2023-07-02 10:34:50,700 [model] Computed derived parameters: {}
2023-07-02 10:34:50,700 [model] Posterior to be computed for parameters {'Omega_m': 0.31194231564120145, 'b1': 0.5045528280411137}
2023-07-02 10:34:50,700 [prior] Evaluating prior at array([0.31194232, 0.50455283])
2023-07-02 10:34:50,700 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:50,700 [model] Got input parameters: {'Omega_m': 0.31194231564120145, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5045528280411137, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:50,700 [classy] Got parameters {'Omega_m': 0.31194231564120145, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:50,700 [classy] Re-using computed results
2023-07-02 10:34:50,700 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.32535922724134}
2023-07-02 10:34:50,700 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:50,700 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5045528280411137, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:50,700 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:50,720 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.86168
2023-07-02 10:34:50,720 [model] Computed derived parameters: {}
2023-07-02 10:34:50,720 [mcmc] New sample, #869:
Omega_m:0.3119423, b1:0.4951803
2023-07-02 10:34:50,720 [model] Posterior to be computed for parameters {'Omega_m': 0.32034435365527164, 'b1': 0.4896107241234661}
2023-07-02 10:34:50,720 [prior] Evaluating prior at array([0.32034435, 0.48961072])
2023-07-02 10:34:50,720 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:50,720 [model] Got input parameters: {'Omega_m': 0.32034435365527164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4896107241234661, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:50,720 [classy] Got parameters {'Omega_m': 0.32034435365527164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:50,720 [classy] Computing new state
2023-07-02 10:34:50,720 [classy] Setting parameters: {'Omega_m': 0.32034435365527164, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:50,767 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.32475374421782}
2023-07-02 10:34:50,767 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:50,768 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00391791
2023-07-02 10:34:50,768 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4896107241234661, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:50,769 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:50,789 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.77776
2023-07-02 10:34:50,789 [model] Computed derived parameters: {}
2023-07-02 10:34:50,789 [mcmc] New sample, #870:
Omega_m:0.3119423, b1:0.5045528
2023-07-02 10:34:50,789 [model] Posterior to be computed for parameters {'Omega_m': 0.32034435365527164, 'b1': 0.48300111674847046}
2023-07-02 10:34:50,789 [prior] Evaluating prior at array([0.32034435, 0.48300112])
2023-07-02 10:34:50,789 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:50,789 [model] Got input parameters: {'Omega_m': 0.32034435365527164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48300111674847046, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:50,790 [classy] Got parameters {'Omega_m': 0.32034435365527164, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:50,790 [classy] Re-using computed results
2023-07-02 10:34:50,790 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.32475374421782}
2023-07-02 10:34:50,790 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:50,790 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48300111674847046, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:50,790 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:50,809 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.62343
2023-07-02 10:34:50,809 [model] Computed derived parameters: {}
2023-07-02 10:34:50,809 [mcmc] New sample, #871:
Omega_m:0.3203444, b1:0.4896107
2023-07-02 10:34:50,809 [model] Posterior to be computed for parameters {'Omega_m': 0.30646738184714595, 'b1': 0.5076797904788257}
2023-07-02 10:34:50,809 [prior] Evaluating prior at array([0.30646738, 0.50767979])
2023-07-02 10:34:50,809 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:50,809 [model] Got input parameters: {'Omega_m': 0.30646738184714595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5076797904788257, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:50,809 [classy] Got parameters {'Omega_m': 0.30646738184714595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:50,809 [classy] Computing new state
2023-07-02 10:34:50,809 [classy] Setting parameters: {'Omega_m': 0.30646738184714595, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:50,856 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.99034217217354}
2023-07-02 10:34:50,856 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:50,858 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00245598
2023-07-02 10:34:50,858 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5076797904788257, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:50,858 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:50,877 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.30606
2023-07-02 10:34:50,877 [model] Computed derived parameters: {}
2023-07-02 10:34:50,877 [mcmc] New sample, #872:
Omega_m:0.3203444, b1:0.4830011
2023-07-02 10:34:50,877 [model] Posterior to be computed for parameters {'Omega_m': 0.30646738184714595, 'b1': 0.4799370928629178}
2023-07-02 10:34:50,878 [prior] Evaluating prior at array([0.30646738, 0.47993709])
2023-07-02 10:34:50,878 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:50,878 [model] Got input parameters: {'Omega_m': 0.30646738184714595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4799370928629178, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:50,878 [classy] Got parameters {'Omega_m': 0.30646738184714595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:50,878 [classy] Re-using computed results
2023-07-02 10:34:50,878 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.99034217217354}
2023-07-02 10:34:50,878 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:50,878 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4799370928629178, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:50,878 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:50,899 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.84183
2023-07-02 10:34:50,899 [model] Computed derived parameters: {}
2023-07-02 10:34:50,899 [model] Posterior to be computed for parameters {'Omega_m': 0.29940509720019226, 'b1': 0.5202392898424413}
2023-07-02 10:34:50,899 [prior] Evaluating prior at array([0.2994051 , 0.52023929])
2023-07-02 10:34:50,899 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:50,899 [model] Got input parameters: {'Omega_m': 0.29940509720019226, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5202392898424413, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:50,899 [classy] Got parameters {'Omega_m': 0.29940509720019226, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:50,899 [classy] Computing new state
2023-07-02 10:34:50,899 [classy] Setting parameters: {'Omega_m': 0.29940509720019226, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:50,947 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.86373232653347}
2023-07-02 10:34:50,947 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:50,949 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0110428
2023-07-02 10:34:50,949 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5202392898424413, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:50,949 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:50,968 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.24252
2023-07-02 10:34:50,968 [model] Computed derived parameters: {}
2023-07-02 10:34:50,968 [model] Posterior to be computed for parameters {'Omega_m': 0.30646738184714595, 'b1': 0.5230224082872564}
2023-07-02 10:34:50,968 [prior] Evaluating prior at array([0.30646738, 0.52302241])
2023-07-02 10:34:50,968 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:50,968 [model] Got input parameters: {'Omega_m': 0.30646738184714595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5230224082872564, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:50,968 [classy] Got parameters {'Omega_m': 0.30646738184714595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:50,968 [classy] Re-using computed results
2023-07-02 10:34:50,968 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.99034217217354}
2023-07-02 10:34:50,969 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:50,969 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5230224082872564, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:50,969 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:50,988 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.344
2023-07-02 10:34:50,988 [model] Computed derived parameters: {}
2023-07-02 10:34:50,988 [mcmc] New sample, #873:
Omega_m:0.3064674, b1:0.5076798
2023-07-02 10:34:50,988 [model] Posterior to be computed for parameters {'Omega_m': 0.335779528895641, 'b1': 0.4708939667693149}
2023-07-02 10:34:50,988 [prior] Evaluating prior at array([0.33577953, 0.47089397])
2023-07-02 10:34:50,988 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:50,988 [model] Got input parameters: {'Omega_m': 0.335779528895641, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4708939667693149, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:50,989 [classy] Got parameters {'Omega_m': 0.335779528895641, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:50,989 [classy] Computing new state
2023-07-02 10:34:50,989 [classy] Setting parameters: {'Omega_m': 0.335779528895641, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:51,035 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.54631334883643}
2023-07-02 10:34:51,035 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:51,036 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0316446
2023-07-02 10:34:51,036 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4708939667693149, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:51,036 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:51,056 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.556748
2023-07-02 10:34:51,056 [model] Computed derived parameters: {}
2023-07-02 10:34:51,056 [model] Posterior to be computed for parameters {'Omega_m': 0.30646738184714595, 'b1': 0.32869995619410863}
2023-07-02 10:34:51,057 [prior] Evaluating prior at array([0.30646738, 0.32869996])
2023-07-02 10:34:51,057 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:51,057 [model] Got input parameters: {'Omega_m': 0.30646738184714595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.32869995619410863, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:51,057 [classy] Got parameters {'Omega_m': 0.30646738184714595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:51,057 [classy] Re-using computed results
2023-07-02 10:34:51,057 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.99034217217354}
2023-07-02 10:34:51,057 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:51,057 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.32869995619410863, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:51,057 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:51,076 [fs_likelihood.fslikelihood] Computed log-likelihood = -74.769
2023-07-02 10:34:51,076 [model] Computed derived parameters: {}
2023-07-02 10:34:51,076 [model] Posterior to be computed for parameters {'Omega_m': 0.3109183539377421, 'b1': 0.515106842159031}
2023-07-02 10:34:51,077 [prior] Evaluating prior at array([0.31091835, 0.51510684])
2023-07-02 10:34:51,077 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:51,077 [model] Got input parameters: {'Omega_m': 0.3109183539377421, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.515106842159031, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:51,077 [classy] Got parameters {'Omega_m': 0.3109183539377421, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:51,077 [classy] Computing new state
2023-07-02 10:34:51,077 [classy] Setting parameters: {'Omega_m': 0.3109183539377421, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:51,125 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.44894023241665}
2023-07-02 10:34:51,125 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:51,127 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00035328
2023-07-02 10:34:51,127 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.515106842159031, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:51,127 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:51,148 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.67617
2023-07-02 10:34:51,148 [model] Computed derived parameters: {}
2023-07-02 10:34:51,148 [mcmc] New sample, #874:
Omega_m:0.3064674, b1:0.5230224
2023-07-02 10:34:51,148 [model] Posterior to be computed for parameters {'Omega_m': 0.3109183539377421, 'b1': 0.5337541208645746}
2023-07-02 10:34:51,148 [prior] Evaluating prior at array([0.31091835, 0.53375412])
2023-07-02 10:34:51,149 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:51,149 [model] Got input parameters: {'Omega_m': 0.3109183539377421, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5337541208645746, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:51,149 [classy] Got parameters {'Omega_m': 0.3109183539377421, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:51,149 [classy] Re-using computed results
2023-07-02 10:34:51,149 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.44894023241665}
2023-07-02 10:34:51,149 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:51,149 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5337541208645746, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:51,149 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:51,168 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.960011
2023-07-02 10:34:51,168 [model] Computed derived parameters: {}
2023-07-02 10:34:51,168 [model] Posterior to be computed for parameters {'Omega_m': 0.3260733796335274, 'b1': 0.48815528963786536}
2023-07-02 10:34:51,168 [prior] Evaluating prior at array([0.32607338, 0.48815529])
2023-07-02 10:34:51,168 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:51,168 [model] Got input parameters: {'Omega_m': 0.3260733796335274, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48815528963786536, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:51,169 [classy] Got parameters {'Omega_m': 0.3260733796335274, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:51,169 [classy] Computing new state
2023-07-02 10:34:51,169 [classy] Setting parameters: {'Omega_m': 0.3260733796335274, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:51,215 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.6558258426254}
2023-07-02 10:34:51,215 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:51,217 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0111544
2023-07-02 10:34:51,217 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48815528963786536, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:51,217 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:51,237 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.11985
2023-07-02 10:34:51,237 [model] Computed derived parameters: {}
2023-07-02 10:34:51,237 [model] Posterior to be computed for parameters {'Omega_m': 0.3109183539377421, 'b1': 0.5204648931496998}
2023-07-02 10:34:51,237 [prior] Evaluating prior at array([0.31091835, 0.52046489])
2023-07-02 10:34:51,237 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:51,237 [model] Got input parameters: {'Omega_m': 0.3109183539377421, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5204648931496998, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:51,237 [classy] Got parameters {'Omega_m': 0.3109183539377421, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:51,237 [classy] Re-using computed results
2023-07-02 10:34:51,237 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.44894023241665}
2023-07-02 10:34:51,237 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:51,237 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5204648931496998, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:51,237 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:51,257 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.38318
2023-07-02 10:34:51,257 [model] Computed derived parameters: {}
2023-07-02 10:34:51,257 [mcmc] New sample, #875:
Omega_m:0.3109184, b1:0.5151068
2023-07-02 10:34:51,257 [model] Posterior to be computed for parameters {'Omega_m': 0.3317925299787476, 'b1': 0.48334245844068585}
2023-07-02 10:34:51,257 [prior] Evaluating prior at array([0.33179253, 0.48334246])
2023-07-02 10:34:51,258 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:51,258 [model] Got input parameters: {'Omega_m': 0.3317925299787476, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48334245844068585, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:51,258 [classy] Got parameters {'Omega_m': 0.3317925299787476, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:51,258 [classy] Computing new state
2023-07-02 10:34:51,258 [classy] Setting parameters: {'Omega_m': 0.3317925299787476, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:51,304 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.99850419625255}
2023-07-02 10:34:51,304 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:51,306 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0220104
2023-07-02 10:34:51,306 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48334245844068585, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:51,306 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:51,325 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.981671
2023-07-02 10:34:51,325 [model] Computed derived parameters: {}
2023-07-02 10:34:51,325 [model] Posterior to be computed for parameters {'Omega_m': 0.3109183539377421, 'b1': 0.5518290624267989}
2023-07-02 10:34:51,325 [prior] Evaluating prior at array([0.31091835, 0.55182906])
2023-07-02 10:34:51,326 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:51,326 [model] Got input parameters: {'Omega_m': 0.3109183539377421, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5518290624267989, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:51,326 [classy] Got parameters {'Omega_m': 0.3109183539377421, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:51,326 [classy] Re-using computed results
2023-07-02 10:34:51,326 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.44894023241665}
2023-07-02 10:34:51,326 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:51,326 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5518290624267989, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:51,326 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:51,345 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.62673
2023-07-02 10:34:51,345 [model] Computed derived parameters: {}
2023-07-02 10:34:51,345 [model] Posterior to be computed for parameters {'Omega_m': 0.2835587674577083, 'b1': 0.5691209196570699}
2023-07-02 10:34:51,345 [prior] Evaluating prior at array([0.28355877, 0.56912092])
2023-07-02 10:34:51,345 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:51,345 [model] Got input parameters: {'Omega_m': 0.2835587674577083, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5691209196570699, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:51,345 [classy] Got parameters {'Omega_m': 0.2835587674577083, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:51,345 [classy] Computing new state
2023-07-02 10:34:51,345 [classy] Setting parameters: {'Omega_m': 0.2835587674577083, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:51,391 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.890900636314}
2023-07-02 10:34:51,391 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:51,393 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0554505
2023-07-02 10:34:51,393 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5691209196570699, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:51,393 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:51,413 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.86163
2023-07-02 10:34:51,413 [model] Computed derived parameters: {}
2023-07-02 10:34:51,413 [model] Posterior to be computed for parameters {'Omega_m': 0.3109183539377421, 'b1': 0.5367523790998252}
2023-07-02 10:34:51,413 [prior] Evaluating prior at array([0.31091835, 0.53675238])
2023-07-02 10:34:51,413 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:51,413 [model] Got input parameters: {'Omega_m': 0.3109183539377421, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5367523790998252, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:51,413 [classy] Got parameters {'Omega_m': 0.3109183539377421, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:51,413 [classy] Re-using computed results
2023-07-02 10:34:51,413 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.44894023241665}
2023-07-02 10:34:51,413 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:51,413 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5367523790998252, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:51,413 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:51,432 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.498753
2023-07-02 10:34:51,433 [model] Computed derived parameters: {}
2023-07-02 10:34:51,433 [mcmc] New sample, #876:
Omega_m:0.3109184, b1:0.5204649
2023-07-02 10:34:51,433 [model] Posterior to be computed for parameters {'Omega_m': 0.32983433562972986, 'b1': 0.503112378462756}
2023-07-02 10:34:51,433 [prior] Evaluating prior at array([0.32983434, 0.50311238])
2023-07-02 10:34:51,433 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:51,433 [model] Got input parameters: {'Omega_m': 0.32983433562972986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.503112378462756, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:51,433 [classy] Got parameters {'Omega_m': 0.32983433562972986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:51,433 [classy] Computing new state
2023-07-02 10:34:51,433 [classy] Setting parameters: {'Omega_m': 0.32983433562972986, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:51,479 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.22238971413995}
2023-07-02 10:34:51,479 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:51,481 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.017895
2023-07-02 10:34:51,481 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.503112378462756, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:51,481 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:51,501 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.683055
2023-07-02 10:34:51,501 [model] Computed derived parameters: {}
2023-07-02 10:34:51,501 [model] Posterior to be computed for parameters {'Omega_m': 0.3109183539377421, 'b1': 0.5505698677772729}
2023-07-02 10:34:51,501 [prior] Evaluating prior at array([0.31091835, 0.55056987])
2023-07-02 10:34:51,502 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:51,502 [model] Got input parameters: {'Omega_m': 0.3109183539377421, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5505698677772729, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:51,502 [classy] Got parameters {'Omega_m': 0.3109183539377421, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:51,502 [classy] Re-using computed results
2023-07-02 10:34:51,502 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.44894023241665}
2023-07-02 10:34:51,502 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:51,502 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5505698677772729, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:51,502 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:51,521 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.3134
2023-07-02 10:34:51,521 [model] Computed derived parameters: {}
2023-07-02 10:34:51,521 [model] Posterior to be computed for parameters {'Omega_m': 0.3316552063934932, 'b1': 0.49987415933934853}
2023-07-02 10:34:51,521 [prior] Evaluating prior at array([0.33165521, 0.49987416])
2023-07-02 10:34:51,521 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:51,522 [model] Got input parameters: {'Omega_m': 0.3316552063934932, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49987415933934853, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:51,522 [classy] Got parameters {'Omega_m': 0.3316552063934932, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:51,522 [classy] Computing new state
2023-07-02 10:34:51,522 [classy] Setting parameters: {'Omega_m': 0.3316552063934932, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:51,568 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.01416726445314}
2023-07-02 10:34:51,568 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:51,570 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0217084
2023-07-02 10:34:51,570 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49987415933934853, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:51,570 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:51,590 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.9848
2023-07-02 10:34:51,591 [model] Computed derived parameters: {}
2023-07-02 10:34:51,591 [mcmc] New sample, #877:
Omega_m:0.3109184, b1:0.5367524
2023-07-02 10:34:51,591 [model] Posterior to be computed for parameters {'Omega_m': 0.3316552063934932, 'b1': 0.5312188375611868}
2023-07-02 10:34:51,591 [prior] Evaluating prior at array([0.33165521, 0.53121884])
2023-07-02 10:34:51,591 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:51,591 [model] Got input parameters: {'Omega_m': 0.3316552063934932, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5312188375611868, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:51,591 [classy] Got parameters {'Omega_m': 0.3316552063934932, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:51,591 [classy] Re-using computed results
2023-07-02 10:34:51,591 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.01416726445314}
2023-07-02 10:34:51,591 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:51,591 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5312188375611868, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:51,591 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:51,612 [fs_likelihood.fslikelihood] Computed log-likelihood = -9.34238
2023-07-02 10:34:51,612 [model] Computed derived parameters: {}
2023-07-02 10:34:51,612 [model] Posterior to be computed for parameters {'Omega_m': 0.2948252983944829, 'b1': 0.5653721149159651}
2023-07-02 10:34:51,612 [prior] Evaluating prior at array([0.2948253 , 0.56537211])
2023-07-02 10:34:51,612 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:51,612 [model] Got input parameters: {'Omega_m': 0.2948252983944829, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5653721149159651, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:51,612 [classy] Got parameters {'Omega_m': 0.2948252983944829, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:51,612 [classy] Computing new state
2023-07-02 10:34:51,612 [classy] Setting parameters: {'Omega_m': 0.2948252983944829, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:51,660 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.43985515983607}
2023-07-02 10:34:51,660 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:51,662 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0201984
2023-07-02 10:34:51,662 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5653721149159651, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:51,662 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:51,681 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.80343
2023-07-02 10:34:51,681 [model] Computed derived parameters: {}
2023-07-02 10:34:51,682 [mcmc] New sample, #878:
Omega_m:0.3316552, b1:0.4998742
2023-07-02 10:34:51,682 [model] Posterior to be computed for parameters {'Omega_m': 0.2948252983944829, 'b1': 0.5754975114682691}
2023-07-02 10:34:51,682 [prior] Evaluating prior at array([0.2948253 , 0.57549751])
2023-07-02 10:34:51,682 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:51,682 [model] Got input parameters: {'Omega_m': 0.2948252983944829, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5754975114682691, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:51,682 [classy] Got parameters {'Omega_m': 0.2948252983944829, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:51,682 [classy] Re-using computed results
2023-07-02 10:34:51,682 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.43985515983607}
2023-07-02 10:34:51,682 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:51,682 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5754975114682691, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:51,682 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:51,703 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.68344
2023-07-02 10:34:51,703 [model] Computed derived parameters: {}
2023-07-02 10:34:51,703 [mcmc] New sample, #879:
Omega_m:0.2948253, b1:0.5653721
2023-07-02 10:34:51,704 [model] Posterior to be computed for parameters {'Omega_m': 0.2770632919865319, 'b1': 0.6070852935146108}
2023-07-02 10:34:51,704 [prior] Evaluating prior at array([0.27706329, 0.60708529])
2023-07-02 10:34:51,704 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:51,704 [model] Got input parameters: {'Omega_m': 0.2770632919865319, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6070852935146108, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:51,704 [classy] Got parameters {'Omega_m': 0.2770632919865319, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:51,704 [classy] Computing new state
2023-07-02 10:34:51,704 [classy] Setting parameters: {'Omega_m': 0.2770632919865319, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:51,752 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.7502327164867}
2023-07-02 10:34:51,752 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:51,754 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0844906
2023-07-02 10:34:51,754 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6070852935146108, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:51,754 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:51,774 [fs_likelihood.fslikelihood] Computed log-likelihood = -10.5364
2023-07-02 10:34:51,774 [model] Computed derived parameters: {}
2023-07-02 10:34:51,774 [model] Posterior to be computed for parameters {'Omega_m': 0.2948252983944829, 'b1': 0.6087068627802504}
2023-07-02 10:34:51,774 [prior] Evaluating prior at array([0.2948253 , 0.60870686])
2023-07-02 10:34:51,774 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:51,774 [model] Got input parameters: {'Omega_m': 0.2948252983944829, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6087068627802504, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:51,774 [classy] Got parameters {'Omega_m': 0.2948252983944829, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:51,774 [classy] Re-using computed results
2023-07-02 10:34:51,774 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.43985515983607}
2023-07-02 10:34:51,774 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:51,774 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6087068627802504, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:51,774 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:51,794 [fs_likelihood.fslikelihood] Computed log-likelihood = -14.188
2023-07-02 10:34:51,794 [model] Computed derived parameters: {}
2023-07-02 10:34:51,794 [model] Posterior to be computed for parameters {'Omega_m': 0.2967585881085531, 'b1': 0.5720593675605433}
2023-07-02 10:34:51,794 [prior] Evaluating prior at array([0.29675859, 0.57205937])
2023-07-02 10:34:51,794 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:51,794 [model] Got input parameters: {'Omega_m': 0.2967585881085531, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5720593675605433, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:51,794 [classy] Got parameters {'Omega_m': 0.2967585881085531, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:51,794 [classy] Computing new state
2023-07-02 10:34:51,794 [classy] Setting parameters: {'Omega_m': 0.2967585881085531, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:51,840 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.19571116875585}
2023-07-02 10:34:51,840 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:51,842 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0159809
2023-07-02 10:34:51,842 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5720593675605433, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:51,842 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:51,862 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.23095
2023-07-02 10:34:51,862 [model] Computed derived parameters: {}
2023-07-02 10:34:51,862 [mcmc] New sample, #880:
Omega_m:0.2948253, b1:0.5754975
2023-07-02 10:34:51,862 [mcmc] Learn + convergence test @ 880 samples accepted.
2023-07-02 10:34:51,862 [mcmc] Ready to check convergence and learn a new proposal covmat
2023-07-02 10:34:51,867 [mcmc] - Acceptance rate: 0.467
2023-07-02 10:34:51,868 [mcmc] - Condition number = 4.08571
2023-07-02 10:34:51,868 [mcmc] - Eigenvalues = array([0.01281207, 0.05234644])
2023-07-02 10:34:51,868 [mcmc] - Convergence of means: R-1 = 0.052346 after 704 accepted steps
2023-07-02 10:34:51,868 [mcmc] - Updated covariance matrix of proposal pdf.
2023-07-02 10:34:51,868 [mcmc] array([[ 0.00010232, -0.00018647],
[-0.00018647, 0.00051157]])
2023-07-02 10:34:51,878 [mcmc] Dumped checkpoint and progress info, and current covmat.
2023-07-02 10:34:51,878 [model] Posterior to be computed for parameters {'Omega_m': 0.2967585881085531, 'b1': 0.5846613514000003}
2023-07-02 10:34:51,878 [prior] Evaluating prior at array([0.29675859, 0.58466135])
2023-07-02 10:34:51,878 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:51,879 [model] Got input parameters: {'Omega_m': 0.2967585881085531, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5846613514000003, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:51,879 [classy] Got parameters {'Omega_m': 0.2967585881085531, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:51,879 [classy] Re-using computed results
2023-07-02 10:34:51,879 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.19571116875585}
2023-07-02 10:34:51,879 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:51,879 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5846613514000003, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:51,879 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:51,899 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.43016
2023-07-02 10:34:51,899 [model] Computed derived parameters: {}
2023-07-02 10:34:51,899 [model] Posterior to be computed for parameters {'Omega_m': 0.31827729053107595, 'b1': 0.5328427642645573}
2023-07-02 10:34:51,899 [prior] Evaluating prior at array([0.31827729, 0.53284276])
2023-07-02 10:34:51,899 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:51,899 [model] Got input parameters: {'Omega_m': 0.31827729053107595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5328427642645573, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:51,899 [classy] Got parameters {'Omega_m': 0.31827729053107595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:51,899 [classy] Computing new state
2023-07-02 10:34:51,899 [classy] Setting parameters: {'Omega_m': 0.31827729053107595, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:51,946 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.56872841263308}
2023-07-02 10:34:51,946 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:51,948 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00223099
2023-07-02 10:34:51,948 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5328427642645573, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:51,948 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:51,968 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.27948
2023-07-02 10:34:51,968 [model] Computed derived parameters: {}
2023-07-02 10:34:51,969 [mcmc] New sample, #881:
Omega_m:0.2967586, b1:0.5720594
2023-07-02 10:34:51,969 [model] Posterior to be computed for parameters {'Omega_m': 0.31827729053107595, 'b1': 0.5719230546284122}
2023-07-02 10:34:51,969 [prior] Evaluating prior at array([0.31827729, 0.57192305])
2023-07-02 10:34:51,969 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:51,969 [model] Got input parameters: {'Omega_m': 0.31827729053107595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5719230546284122, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:51,969 [classy] Got parameters {'Omega_m': 0.31827729053107595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:51,969 [classy] Re-using computed results
2023-07-02 10:34:51,969 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.56872841263308}
2023-07-02 10:34:51,969 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:51,969 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5719230546284122, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:51,969 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:51,989 [fs_likelihood.fslikelihood] Computed log-likelihood = -14.6806
2023-07-02 10:34:51,989 [model] Computed derived parameters: {}
2023-07-02 10:34:51,990 [model] Posterior to be computed for parameters {'Omega_m': 0.2879182248381604, 'b1': 0.588170423541527}
2023-07-02 10:34:51,990 [prior] Evaluating prior at array([0.28791822, 0.58817042])
2023-07-02 10:34:51,990 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:51,990 [model] Got input parameters: {'Omega_m': 0.2879182248381604, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.588170423541527, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:51,990 [classy] Got parameters {'Omega_m': 0.2879182248381604, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:51,990 [classy] Computing new state
2023-07-02 10:34:51,990 [classy] Setting parameters: {'Omega_m': 0.2879182248381604, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:52,038 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.32360100871247}
2023-07-02 10:34:52,038 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:52,040 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0395984
2023-07-02 10:34:52,040 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.588170423541527, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:52,040 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:52,059 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.83372
2023-07-02 10:34:52,059 [model] Computed derived parameters: {}
2023-07-02 10:34:52,060 [model] Posterior to be computed for parameters {'Omega_m': 0.31827729053107595, 'b1': 0.5387781227804908}
2023-07-02 10:34:52,060 [prior] Evaluating prior at array([0.31827729, 0.53877812])
2023-07-02 10:34:52,060 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:52,060 [model] Got input parameters: {'Omega_m': 0.31827729053107595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5387781227804908, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:52,060 [classy] Got parameters {'Omega_m': 0.31827729053107595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:52,060 [classy] Re-using computed results
2023-07-02 10:34:52,060 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.56872841263308}
2023-07-02 10:34:52,060 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:52,060 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5387781227804908, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:52,060 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:52,079 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.69368
2023-07-02 10:34:52,079 [model] Computed derived parameters: {}
2023-07-02 10:34:52,080 [model] Posterior to be computed for parameters {'Omega_m': 0.3461076069084337, 'b1': 0.48212360585330116}
2023-07-02 10:34:52,080 [prior] Evaluating prior at array([0.34610761, 0.48212361])
2023-07-02 10:34:52,080 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:52,080 [model] Got input parameters: {'Omega_m': 0.3461076069084337, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48212360585330116, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:52,080 [classy] Got parameters {'Omega_m': 0.3461076069084337, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:52,080 [classy] Computing new state
2023-07-02 10:34:52,080 [classy] Setting parameters: {'Omega_m': 0.3461076069084337, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:52,127 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.39717723543535}
2023-07-02 10:34:52,128 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:52,129 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0641302
2023-07-02 10:34:52,130 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48212360585330116, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:52,130 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:52,150 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.948
2023-07-02 10:34:52,150 [model] Computed derived parameters: {}
2023-07-02 10:34:52,150 [model] Posterior to be computed for parameters {'Omega_m': 0.31827729053107595, 'b1': 0.5118301076782446}
2023-07-02 10:34:52,150 [prior] Evaluating prior at array([0.31827729, 0.51183011])
2023-07-02 10:34:52,150 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:52,150 [model] Got input parameters: {'Omega_m': 0.31827729053107595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5118301076782446, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:52,150 [classy] Got parameters {'Omega_m': 0.31827729053107595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:52,151 [classy] Re-using computed results
2023-07-02 10:34:52,151 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.56872841263308}
2023-07-02 10:34:52,151 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:52,151 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5118301076782446, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:52,151 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:52,170 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.03772
2023-07-02 10:34:52,170 [model] Computed derived parameters: {}
2023-07-02 10:34:52,170 [mcmc] New sample, #882:
Omega_m:0.3182773, b1:0.5328428
2023-07-02 10:34:52,171 [model] Posterior to be computed for parameters {'Omega_m': 0.3534531305298964, 'b1': 0.44772415297193446}
2023-07-02 10:34:52,171 [prior] Evaluating prior at array([0.35345313, 0.44772415])
2023-07-02 10:34:52,171 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:52,171 [model] Got input parameters: {'Omega_m': 0.3534531305298964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44772415297193446, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:52,171 [classy] Got parameters {'Omega_m': 0.3534531305298964, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:52,171 [classy] Computing new state
2023-07-02 10:34:52,171 [classy] Setting parameters: {'Omega_m': 0.3534531305298964, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:52,222 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.59884333768574}
2023-07-02 10:34:52,222 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:52,224 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0935062
2023-07-02 10:34:52,224 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44772415297193446, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:52,224 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:52,245 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.86988
2023-07-02 10:34:52,245 [model] Computed derived parameters: {}
2023-07-02 10:34:52,245 [model] Posterior to be computed for parameters {'Omega_m': 0.31827729053107595, 'b1': 0.5500257086953573}
2023-07-02 10:34:52,245 [prior] Evaluating prior at array([0.31827729, 0.55002571])
2023-07-02 10:34:52,245 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:52,245 [model] Got input parameters: {'Omega_m': 0.31827729053107595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5500257086953573, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:52,246 [classy] Got parameters {'Omega_m': 0.31827729053107595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:52,246 [classy] Re-using computed results
2023-07-02 10:34:52,246 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.56872841263308}
2023-07-02 10:34:52,246 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:52,246 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5500257086953573, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:52,246 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:52,265 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.97142
2023-07-02 10:34:52,265 [model] Computed derived parameters: {}
2023-07-02 10:34:52,266 [model] Posterior to be computed for parameters {'Omega_m': 0.35557786077738746, 'b1': 0.4438519537291202}
2023-07-02 10:34:52,266 [prior] Evaluating prior at array([0.35557786, 0.44385195])
2023-07-02 10:34:52,266 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:52,266 [model] Got input parameters: {'Omega_m': 0.35557786077738746, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4438519537291202, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:52,266 [classy] Got parameters {'Omega_m': 0.35557786077738746, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:52,266 [classy] Computing new state
2023-07-02 10:34:52,266 [classy] Setting parameters: {'Omega_m': 0.35557786077738746, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:52,312 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.37075170847373}
2023-07-02 10:34:52,312 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:52,314 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.102932
2023-07-02 10:34:52,314 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4438519537291202, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:52,314 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:52,334 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.59243
2023-07-02 10:34:52,334 [model] Computed derived parameters: {}
2023-07-02 10:34:52,334 [model] Posterior to be computed for parameters {'Omega_m': 0.31827729053107595, 'b1': 0.516352990443558}
2023-07-02 10:34:52,334 [prior] Evaluating prior at array([0.31827729, 0.51635299])
2023-07-02 10:34:52,334 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:52,334 [model] Got input parameters: {'Omega_m': 0.31827729053107595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.516352990443558, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:52,334 [classy] Got parameters {'Omega_m': 0.31827729053107595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:52,334 [classy] Re-using computed results
2023-07-02 10:34:52,334 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.56872841263308}
2023-07-02 10:34:52,334 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:52,334 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.516352990443558, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:52,334 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:52,354 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.54148
2023-07-02 10:34:52,354 [model] Computed derived parameters: {}
2023-07-02 10:34:52,354 [model] Posterior to be computed for parameters {'Omega_m': 0.32501277085589864, 'b1': 0.4995550803685114}
2023-07-02 10:34:52,354 [prior] Evaluating prior at array([0.32501277, 0.49955508])
2023-07-02 10:34:52,354 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:52,354 [model] Got input parameters: {'Omega_m': 0.32501277085589864, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4995550803685114, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:52,354 [classy] Got parameters {'Omega_m': 0.32501277085589864, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:52,354 [classy] Computing new state
2023-07-02 10:34:52,354 [classy] Setting parameters: {'Omega_m': 0.32501277085589864, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:52,400 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.77886749293197}
2023-07-02 10:34:52,400 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:52,402 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00953545
2023-07-02 10:34:52,403 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4995550803685114, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:52,403 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:52,422 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.57091
2023-07-02 10:34:52,422 [model] Computed derived parameters: {}
2023-07-02 10:34:52,423 [model] Posterior to be computed for parameters {'Omega_m': 0.31827729053107595, 'b1': 0.529329728986742}
2023-07-02 10:34:52,423 [prior] Evaluating prior at array([0.31827729, 0.52932973])
2023-07-02 10:34:52,423 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:52,423 [model] Got input parameters: {'Omega_m': 0.31827729053107595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.529329728986742, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:52,423 [classy] Got parameters {'Omega_m': 0.31827729053107595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:52,423 [classy] Re-using computed results
2023-07-02 10:34:52,423 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.56872841263308}
2023-07-02 10:34:52,423 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:52,423 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.529329728986742, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:52,423 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:52,442 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.543121
2023-07-02 10:34:52,443 [model] Computed derived parameters: {}
2023-07-02 10:34:52,443 [model] Posterior to be computed for parameters {'Omega_m': 0.33286101012784636, 'b1': 0.48525211357912873}
2023-07-02 10:34:52,443 [prior] Evaluating prior at array([0.33286101, 0.48525211])
2023-07-02 10:34:52,443 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:52,443 [model] Got input parameters: {'Omega_m': 0.33286101012784636, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48525211357912873, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:52,443 [classy] Got parameters {'Omega_m': 0.33286101012784636, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:52,443 [classy] Computing new state
2023-07-02 10:34:52,443 [classy] Setting parameters: {'Omega_m': 0.33286101012784636, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:52,490 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.87684153923635}
2023-07-02 10:34:52,490 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:52,492 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0244285
2023-07-02 10:34:52,492 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48525211357912873, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:52,492 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:52,511 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.465894
2023-07-02 10:34:52,511 [model] Computed derived parameters: {}
2023-07-02 10:34:52,511 [model] Posterior to be computed for parameters {'Omega_m': 0.31827729053107595, 'b1': 0.5282730126817755}
2023-07-02 10:34:52,511 [prior] Evaluating prior at array([0.31827729, 0.52827301])
2023-07-02 10:34:52,512 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:52,512 [model] Got input parameters: {'Omega_m': 0.31827729053107595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5282730126817755, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:52,512 [classy] Got parameters {'Omega_m': 0.31827729053107595, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:52,512 [classy] Re-using computed results
2023-07-02 10:34:52,512 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.56872841263308}
2023-07-02 10:34:52,512 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:52,512 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5282730126817755, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:52,512 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:52,531 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.336129
2023-07-02 10:34:52,532 [model] Computed derived parameters: {}
2023-07-02 10:34:52,532 [model] Posterior to be computed for parameters {'Omega_m': 0.31513467306041426, 'b1': 0.5175573481148695}
2023-07-02 10:34:52,532 [prior] Evaluating prior at array([0.31513467, 0.51755735])
2023-07-02 10:34:52,532 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:52,532 [model] Got input parameters: {'Omega_m': 0.31513467306041426, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5175573481148695, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:52,532 [classy] Got parameters {'Omega_m': 0.31513467306041426, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:52,532 [classy] Computing new state
2023-07-02 10:34:52,532 [classy] Setting parameters: {'Omega_m': 0.31513467306041426, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:52,578 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.94235968761083}
2023-07-02 10:34:52,578 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:52,580 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000630508
2023-07-02 10:34:52,580 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5175573481148695, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:52,580 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:52,600 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.09083
2023-07-02 10:34:52,600 [model] Computed derived parameters: {}
2023-07-02 10:34:52,600 [mcmc] New sample, #883:
Omega_m:0.3182773, b1:0.5118301
2023-07-02 10:34:52,600 [model] Posterior to be computed for parameters {'Omega_m': 0.31513467306041426, 'b1': 0.5200357271667242}
2023-07-02 10:34:52,600 [prior] Evaluating prior at array([0.31513467, 0.52003573])
2023-07-02 10:34:52,600 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:52,600 [model] Got input parameters: {'Omega_m': 0.31513467306041426, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5200357271667242, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:52,600 [classy] Got parameters {'Omega_m': 0.31513467306041426, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:52,600 [classy] Re-using computed results
2023-07-02 10:34:52,600 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.94235968761083}
2023-07-02 10:34:52,600 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:52,601 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5200357271667242, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:52,601 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:52,620 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.83389
2023-07-02 10:34:52,620 [model] Computed derived parameters: {}
2023-07-02 10:34:52,620 [model] Posterior to be computed for parameters {'Omega_m': 0.32928631502455363, 'b1': 0.49176679076631846}
2023-07-02 10:34:52,620 [prior] Evaluating prior at array([0.32928632, 0.49176679])
2023-07-02 10:34:52,620 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:52,621 [model] Got input parameters: {'Omega_m': 0.32928631502455363, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49176679076631846, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:52,621 [classy] Got parameters {'Omega_m': 0.32928631502455363, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:52,621 [classy] Computing new state
2023-07-02 10:34:52,621 [classy] Setting parameters: {'Omega_m': 0.32928631502455363, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:52,667 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.28526770007363}
2023-07-02 10:34:52,667 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:52,669 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0168169
2023-07-02 10:34:52,669 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49176679076631846, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:52,669 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:52,688 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.04037
2023-07-02 10:34:52,688 [model] Computed derived parameters: {}
2023-07-02 10:34:52,688 [mcmc] New sample, #884:
Omega_m:0.3151347, b1:0.5175573
2023-07-02 10:34:52,688 [model] Posterior to be computed for parameters {'Omega_m': 0.32928631502455363, 'b1': 0.517138542474353}
2023-07-02 10:34:52,688 [prior] Evaluating prior at array([0.32928632, 0.51713854])
2023-07-02 10:34:52,688 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:52,688 [model] Got input parameters: {'Omega_m': 0.32928631502455363, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.517138542474353, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:52,688 [classy] Got parameters {'Omega_m': 0.32928631502455363, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:52,688 [classy] Re-using computed results
2023-07-02 10:34:52,688 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.28526770007363}
2023-07-02 10:34:52,688 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:52,688 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.517138542474353, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:52,689 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:52,708 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.32211
2023-07-02 10:34:52,708 [model] Computed derived parameters: {}
2023-07-02 10:34:52,708 [model] Posterior to be computed for parameters {'Omega_m': 0.35305904080371037, 'b1': 0.44844235893767537}
2023-07-02 10:34:52,708 [prior] Evaluating prior at array([0.35305904, 0.44844236])
2023-07-02 10:34:52,708 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:52,708 [model] Got input parameters: {'Omega_m': 0.35305904080371037, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44844235893767537, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:52,708 [classy] Got parameters {'Omega_m': 0.35305904080371037, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:52,708 [classy] Computing new state
2023-07-02 10:34:52,708 [classy] Setting parameters: {'Omega_m': 0.35305904080371037, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:52,754 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.64128631289478}
2023-07-02 10:34:52,755 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:52,757 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0918031
2023-07-02 10:34:52,757 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44844235893767537, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:52,757 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:52,776 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.73904
2023-07-02 10:34:52,777 [model] Computed derived parameters: {}
2023-07-02 10:34:52,777 [model] Posterior to be computed for parameters {'Omega_m': 0.32928631502455363, 'b1': 0.5646594716317532}
2023-07-02 10:34:52,777 [prior] Evaluating prior at array([0.32928632, 0.56465947])
2023-07-02 10:34:52,777 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:52,777 [model] Got input parameters: {'Omega_m': 0.32928631502455363, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5646594716317532, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:52,777 [classy] Got parameters {'Omega_m': 0.32928631502455363, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:52,777 [classy] Re-using computed results
2023-07-02 10:34:52,777 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.28526770007363}
2023-07-02 10:34:52,777 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:52,777 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5646594716317532, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:52,777 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:52,797 [fs_likelihood.fslikelihood] Computed log-likelihood = -22.4467
2023-07-02 10:34:52,797 [model] Computed derived parameters: {}
2023-07-02 10:34:52,797 [model] Posterior to be computed for parameters {'Omega_m': 0.30300023980964963, 'b1': 0.5396716580613085}
2023-07-02 10:34:52,797 [prior] Evaluating prior at array([0.30300024, 0.53967166])
2023-07-02 10:34:52,797 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:52,797 [model] Got input parameters: {'Omega_m': 0.30300023980964963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5396716580613085, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:52,797 [classy] Got parameters {'Omega_m': 0.30300023980964963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:52,797 [classy] Computing new state
2023-07-02 10:34:52,797 [classy] Setting parameters: {'Omega_m': 0.30300023980964963, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:52,843 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.4168833327912}
2023-07-02 10:34:52,843 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:52,845 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00585052
2023-07-02 10:34:52,845 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5396716580613085, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:52,845 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:52,865 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.21389
2023-07-02 10:34:52,865 [model] Computed derived parameters: {}
2023-07-02 10:34:52,865 [mcmc] New sample, #885:
Omega_m:0.3292863, b1:0.4917668
2023-07-02 10:34:52,865 [model] Posterior to be computed for parameters {'Omega_m': 0.30300023980964963, 'b1': 0.5140877743960656}
2023-07-02 10:34:52,865 [prior] Evaluating prior at array([0.30300024, 0.51408777])
2023-07-02 10:34:52,865 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:52,865 [model] Got input parameters: {'Omega_m': 0.30300023980964963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5140877743960656, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:52,865 [classy] Got parameters {'Omega_m': 0.30300023980964963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:52,865 [classy] Re-using computed results
2023-07-02 10:34:52,865 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.4168833327912}
2023-07-02 10:34:52,866 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:52,866 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5140877743960656, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:52,866 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:52,885 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.87577
2023-07-02 10:34:52,885 [model] Computed derived parameters: {}
2023-07-02 10:34:52,885 [mcmc] New sample, #886:
Omega_m:0.3030002, b1:0.5396717
2023-07-02 10:34:52,885 [model] Posterior to be computed for parameters {'Omega_m': 0.2643787637607842, 'b1': 0.5844732035531925}
2023-07-02 10:34:52,886 [prior] Evaluating prior at array([0.26437876, 0.5844732 ])
2023-07-02 10:34:52,886 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:52,886 [model] Got input parameters: {'Omega_m': 0.2643787637607842, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5844732035531925, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:52,886 [classy] Got parameters {'Omega_m': 0.2643787637607842, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:52,886 [classy] Computing new state
2023-07-02 10:34:52,886 [classy] Setting parameters: {'Omega_m': 0.2643787637607842, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:52,932 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.47905080522912}
2023-07-02 10:34:52,932 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:52,934 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.161101
2023-07-02 10:34:52,934 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5844732035531925, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:52,934 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:52,954 [fs_likelihood.fslikelihood] Computed log-likelihood = -15.1574
2023-07-02 10:34:52,954 [model] Computed derived parameters: {}
2023-07-02 10:34:52,954 [model] Posterior to be computed for parameters {'Omega_m': 0.30300023980964963, 'b1': 0.4963902373089941}
2023-07-02 10:34:52,954 [prior] Evaluating prior at array([0.30300024, 0.49639024])
2023-07-02 10:34:52,954 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:52,954 [model] Got input parameters: {'Omega_m': 0.30300023980964963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4963902373089941, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:52,954 [classy] Got parameters {'Omega_m': 0.30300023980964963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:52,954 [classy] Re-using computed results
2023-07-02 10:34:52,954 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.4168833327912}
2023-07-02 10:34:52,954 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:52,954 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4963902373089941, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:52,954 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:52,974 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.325885
2023-07-02 10:34:52,974 [model] Computed derived parameters: {}
2023-07-02 10:34:52,974 [model] Posterior to be computed for parameters {'Omega_m': 0.24727221154979387, 'b1': 0.6156489156685435}
2023-07-02 10:34:52,974 [prior] Evaluating prior at array([0.24727221, 0.61564892])
2023-07-02 10:34:52,974 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:52,974 [model] Got input parameters: {'Omega_m': 0.24727221154979387, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6156489156685435, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:52,974 [classy] Got parameters {'Omega_m': 0.24727221154979387, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:52,974 [classy] Computing new state
2023-07-02 10:34:52,975 [classy] Setting parameters: {'Omega_m': 0.24727221154979387, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:53,021 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 155.9243010727541}
2023-07-02 10:34:53,021 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:53,023 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.310367
2023-07-02 10:34:53,023 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6156489156685435, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:53,023 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:53,042 [fs_likelihood.fslikelihood] Computed log-likelihood = -31.5804
2023-07-02 10:34:53,042 [model] Computed derived parameters: {}
2023-07-02 10:34:53,043 [model] Posterior to be computed for parameters {'Omega_m': 0.30300023980964963, 'b1': 0.5146332111412649}
2023-07-02 10:34:53,043 [prior] Evaluating prior at array([0.30300024, 0.51463321])
2023-07-02 10:34:53,043 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:53,043 [model] Got input parameters: {'Omega_m': 0.30300023980964963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5146332111412649, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:53,043 [classy] Got parameters {'Omega_m': 0.30300023980964963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:53,043 [classy] Re-using computed results
2023-07-02 10:34:53,043 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.4168833327912}
2023-07-02 10:34:53,043 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:53,043 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5146332111412649, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:53,043 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:53,062 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.89811
2023-07-02 10:34:53,062 [model] Computed derived parameters: {}
2023-07-02 10:34:53,062 [mcmc] New sample, #887:
Omega_m:0.3030002, b1:0.5140878
2023-07-02 10:34:53,062 [model] Posterior to be computed for parameters {'Omega_m': 0.3296837857955315, 'b1': 0.46600397611995353}
2023-07-02 10:34:53,062 [prior] Evaluating prior at array([0.32968379, 0.46600398])
2023-07-02 10:34:53,063 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:53,063 [model] Got input parameters: {'Omega_m': 0.3296837857955315, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46600397611995353, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:53,063 [classy] Got parameters {'Omega_m': 0.3296837857955315, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:53,063 [classy] Computing new state
2023-07-02 10:34:53,063 [classy] Setting parameters: {'Omega_m': 0.3296837857955315, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:53,109 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.23965231583597}
2023-07-02 10:34:53,109 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:53,111 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0175957
2023-07-02 10:34:53,111 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46600397611995353, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:53,111 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:53,133 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.65461
2023-07-02 10:34:53,133 [model] Computed derived parameters: {}
2023-07-02 10:34:53,133 [mcmc] New sample, #888:
Omega_m:0.3030002, b1:0.5146332
2023-07-02 10:34:53,133 [model] Posterior to be computed for parameters {'Omega_m': 0.3296837857955315, 'b1': 0.5375794630807906}
2023-07-02 10:34:53,133 [prior] Evaluating prior at array([0.32968379, 0.53757946])
2023-07-02 10:34:53,134 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:53,134 [model] Got input parameters: {'Omega_m': 0.3296837857955315, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5375794630807906, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:53,134 [classy] Got parameters {'Omega_m': 0.3296837857955315, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:53,134 [classy] Re-using computed results
2023-07-02 10:34:53,134 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.23965231583597}
2023-07-02 10:34:53,134 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:53,134 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5375794630807906, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:53,134 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:53,154 [fs_likelihood.fslikelihood] Computed log-likelihood = -10.0594
2023-07-02 10:34:53,154 [model] Computed derived parameters: {}
2023-07-02 10:34:53,154 [model] Posterior to be computed for parameters {'Omega_m': 0.31858624224638055, 'b1': 0.4862286139434434}
2023-07-02 10:34:53,154 [prior] Evaluating prior at array([0.31858624, 0.48622861])
2023-07-02 10:34:53,154 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:53,154 [model] Got input parameters: {'Omega_m': 0.31858624224638055, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4862286139434434, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:53,154 [classy] Got parameters {'Omega_m': 0.31858624224638055, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:53,154 [classy] Computing new state
2023-07-02 10:34:53,154 [classy] Setting parameters: {'Omega_m': 0.31858624224638055, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:53,200 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.53217150926403}
2023-07-02 10:34:53,200 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:53,202 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00245144
2023-07-02 10:34:53,202 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4862286139434434, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:53,202 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:53,222 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.70741
2023-07-02 10:34:53,222 [model] Computed derived parameters: {}
2023-07-02 10:34:53,222 [mcmc] New sample, #889:
Omega_m:0.3296838, b1:0.466004
2023-07-02 10:34:53,222 [model] Posterior to be computed for parameters {'Omega_m': 0.31858624224638055, 'b1': 0.4379675114368804}
2023-07-02 10:34:53,222 [prior] Evaluating prior at array([0.31858624, 0.43796751])
2023-07-02 10:34:53,222 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:53,223 [model] Got input parameters: {'Omega_m': 0.31858624224638055, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4379675114368804, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:53,223 [classy] Got parameters {'Omega_m': 0.31858624224638055, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:53,223 [classy] Re-using computed results
2023-07-02 10:34:53,223 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.53217150926403}
2023-07-02 10:34:53,223 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:53,223 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4379675114368804, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:53,223 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:53,243 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.11633
2023-07-02 10:34:53,243 [model] Computed derived parameters: {}
2023-07-02 10:34:53,243 [model] Posterior to be computed for parameters {'Omega_m': 0.3056127811406604, 'b1': 0.5098720041241828}
2023-07-02 10:34:53,243 [prior] Evaluating prior at array([0.30561278, 0.509872 ])
2023-07-02 10:34:53,243 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:53,243 [model] Got input parameters: {'Omega_m': 0.3056127811406604, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5098720041241828, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:53,243 [classy] Got parameters {'Omega_m': 0.3056127811406604, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:53,243 [classy] Computing new state
2023-07-02 10:34:53,243 [classy] Setting parameters: {'Omega_m': 0.3056127811406604, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:53,290 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.09508473847453}
2023-07-02 10:34:53,290 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:53,291 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00314795
2023-07-02 10:34:53,292 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5098720041241828, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:53,292 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:53,311 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.23957
2023-07-02 10:34:53,311 [model] Computed derived parameters: {}
2023-07-02 10:34:53,311 [mcmc] New sample, #890:
Omega_m:0.3185862, b1:0.4862286
2023-07-02 10:34:53,311 [model] Posterior to be computed for parameters {'Omega_m': 0.3056127811406604, 'b1': 0.5066862696651205}
2023-07-02 10:34:53,311 [prior] Evaluating prior at array([0.30561278, 0.50668627])
2023-07-02 10:34:53,312 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:53,312 [model] Got input parameters: {'Omega_m': 0.3056127811406604, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5066862696651205, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:53,312 [classy] Got parameters {'Omega_m': 0.3056127811406604, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:53,312 [classy] Re-using computed results
2023-07-02 10:34:53,312 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.09508473847453}
2023-07-02 10:34:53,312 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:53,312 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5066862696651205, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:53,312 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:53,331 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.08655
2023-07-02 10:34:53,332 [model] Computed derived parameters: {}
2023-07-02 10:34:53,332 [mcmc] New sample, #891:
Omega_m:0.3056128, b1:0.509872
2023-07-02 10:34:53,332 [model] Posterior to be computed for parameters {'Omega_m': 0.32905622959646474, 'b1': 0.4639619269083333}
2023-07-02 10:34:53,332 [prior] Evaluating prior at array([0.32905623, 0.46396193])
2023-07-02 10:34:53,332 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:53,332 [model] Got input parameters: {'Omega_m': 0.32905622959646474, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4639619269083333, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:53,332 [classy] Got parameters {'Omega_m': 0.32905622959646474, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:53,332 [classy] Computing new state
2023-07-02 10:34:53,332 [classy] Setting parameters: {'Omega_m': 0.32905622959646474, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:53,378 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.31169902973238}
2023-07-02 10:34:53,378 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:53,380 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0163738
2023-07-02 10:34:53,380 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4639619269083333, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:53,380 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:53,400 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.58684
2023-07-02 10:34:53,400 [model] Computed derived parameters: {}
2023-07-02 10:34:53,400 [mcmc] New sample, #892:
Omega_m:0.3056128, b1:0.5066863
2023-07-02 10:34:53,400 [model] Posterior to be computed for parameters {'Omega_m': 0.32905622959646474, 'b1': 0.473784508892149}
2023-07-02 10:34:53,400 [prior] Evaluating prior at array([0.32905623, 0.47378451])
2023-07-02 10:34:53,400 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:53,400 [model] Got input parameters: {'Omega_m': 0.32905622959646474, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.473784508892149, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:53,400 [classy] Got parameters {'Omega_m': 0.32905622959646474, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:53,400 [classy] Re-using computed results
2023-07-02 10:34:53,400 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.31169902973238}
2023-07-02 10:34:53,400 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:53,400 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.473784508892149, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:53,400 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:53,419 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.90436
2023-07-02 10:34:53,419 [model] Computed derived parameters: {}
2023-07-02 10:34:53,419 [mcmc] New sample, #893:
Omega_m:0.3290562, b1:0.4639619
2023-07-02 10:34:53,419 [model] Posterior to be computed for parameters {'Omega_m': 0.3139198367804066, 'b1': 0.5013697182948436}
2023-07-02 10:34:53,419 [prior] Evaluating prior at array([0.31391984, 0.50136972])
2023-07-02 10:34:53,420 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:53,420 [model] Got input parameters: {'Omega_m': 0.3139198367804066, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5013697182948436, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:53,420 [classy] Got parameters {'Omega_m': 0.3139198367804066, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:53,420 [classy] Computing new state
2023-07-02 10:34:53,420 [classy] Setting parameters: {'Omega_m': 0.3139198367804066, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:53,466 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.08769832156304}
2023-07-02 10:34:53,466 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:53,468 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00032839
2023-07-02 10:34:53,468 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5013697182948436, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:53,468 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:53,488 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.91522
2023-07-02 10:34:53,488 [model] Computed derived parameters: {}
2023-07-02 10:34:53,488 [mcmc] New sample, #894:
Omega_m:0.3290562, b1:0.4737845
2023-07-02 10:34:53,488 [model] Posterior to be computed for parameters {'Omega_m': 0.3139198367804066, 'b1': 0.5578296340790643}
2023-07-02 10:34:53,488 [prior] Evaluating prior at array([0.31391984, 0.55782963])
2023-07-02 10:34:53,488 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:53,488 [model] Got input parameters: {'Omega_m': 0.3139198367804066, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5578296340790643, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:53,488 [classy] Got parameters {'Omega_m': 0.3139198367804066, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:53,488 [classy] Re-using computed results
2023-07-02 10:34:53,488 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.08769832156304}
2023-07-02 10:34:53,488 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:53,488 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5578296340790643, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:53,488 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:53,508 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.85562
2023-07-02 10:34:53,508 [model] Computed derived parameters: {}
2023-07-02 10:34:53,508 [model] Posterior to be computed for parameters {'Omega_m': 0.28452823166769897, 'b1': 0.5549342360480563}
2023-07-02 10:34:53,508 [prior] Evaluating prior at array([0.28452823, 0.55493424])
2023-07-02 10:34:53,508 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:53,508 [model] Got input parameters: {'Omega_m': 0.28452823166769897, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5549342360480563, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:53,508 [classy] Got parameters {'Omega_m': 0.28452823166769897, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:53,508 [classy] Computing new state
2023-07-02 10:34:53,508 [classy] Setting parameters: {'Omega_m': 0.28452823166769897, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:53,554 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.76409211092061}
2023-07-02 10:34:53,554 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:53,556 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0516772
2023-07-02 10:34:53,556 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5549342360480563, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:53,556 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:53,576 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.08642
2023-07-02 10:34:53,576 [model] Computed derived parameters: {}
2023-07-02 10:34:53,576 [model] Posterior to be computed for parameters {'Omega_m': 0.3139198367804066, 'b1': 0.4759995916658736}
2023-07-02 10:34:53,576 [prior] Evaluating prior at array([0.31391984, 0.47599959])
2023-07-02 10:34:53,576 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:53,576 [model] Got input parameters: {'Omega_m': 0.3139198367804066, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4759995916658736, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:53,576 [classy] Got parameters {'Omega_m': 0.3139198367804066, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:53,576 [classy] Re-using computed results
2023-07-02 10:34:53,576 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.08769832156304}
2023-07-02 10:34:53,576 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:53,576 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4759995916658736, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:53,576 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:53,596 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.10207
2023-07-02 10:34:53,596 [model] Computed derived parameters: {}
2023-07-02 10:34:53,596 [model] Posterior to be computed for parameters {'Omega_m': 0.34631065426367624, 'b1': 0.4423393076905062}
2023-07-02 10:34:53,596 [prior] Evaluating prior at array([0.34631065, 0.44233931])
2023-07-02 10:34:53,597 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:53,597 [model] Got input parameters: {'Omega_m': 0.34631065426367624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4423393076905062, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:53,597 [classy] Got parameters {'Omega_m': 0.34631065426367624, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:53,597 [classy] Computing new state
2023-07-02 10:34:53,597 [classy] Setting parameters: {'Omega_m': 0.34631065426367624, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:53,643 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.37490245731038}
2023-07-02 10:34:53,643 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:53,645 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0648738
2023-07-02 10:34:53,645 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4423393076905062, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:53,645 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:53,664 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.84992
2023-07-02 10:34:53,664 [model] Computed derived parameters: {}
2023-07-02 10:34:53,664 [model] Posterior to be computed for parameters {'Omega_m': 0.3139198367804066, 'b1': 0.4987065745251715}
2023-07-02 10:34:53,664 [prior] Evaluating prior at array([0.31391984, 0.49870657])
2023-07-02 10:34:53,664 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:53,664 [model] Got input parameters: {'Omega_m': 0.3139198367804066, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4987065745251715, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:53,664 [classy] Got parameters {'Omega_m': 0.3139198367804066, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:53,664 [classy] Re-using computed results
2023-07-02 10:34:53,664 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.08769832156304}
2023-07-02 10:34:53,664 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:53,664 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4987065745251715, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:53,664 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:53,684 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.88276
2023-07-02 10:34:53,684 [model] Computed derived parameters: {}
2023-07-02 10:34:53,684 [model] Posterior to be computed for parameters {'Omega_m': 0.26310100910495493, 'b1': 0.5939841225364915}
2023-07-02 10:34:53,684 [prior] Evaluating prior at array([0.26310101, 0.59398412])
2023-07-02 10:34:53,685 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:53,685 [model] Got input parameters: {'Omega_m': 0.26310100910495493, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5939841225364915, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:53,685 [classy] Got parameters {'Omega_m': 0.26310100910495493, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:53,685 [classy] Computing new state
2023-07-02 10:34:53,685 [classy] Setting parameters: {'Omega_m': 0.26310100910495493, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:53,731 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.65705904754364}
2023-07-02 10:34:53,731 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:53,733 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.170358
2023-07-02 10:34:53,733 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5939841225364915, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:53,733 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:53,753 [fs_likelihood.fslikelihood] Computed log-likelihood = -16.0373
2023-07-02 10:34:53,753 [model] Computed derived parameters: {}
2023-07-02 10:34:53,753 [model] Posterior to be computed for parameters {'Omega_m': 0.3139198367804066, 'b1': 0.4195690469399737}
2023-07-02 10:34:53,753 [prior] Evaluating prior at array([0.31391984, 0.41956905])
2023-07-02 10:34:53,753 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:53,753 [model] Got input parameters: {'Omega_m': 0.3139198367804066, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4195690469399737, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:53,753 [classy] Got parameters {'Omega_m': 0.3139198367804066, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:53,753 [classy] Re-using computed results
2023-07-02 10:34:53,753 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.08769832156304}
2023-07-02 10:34:53,753 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:53,753 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4195690469399737, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:53,753 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:53,772 [fs_likelihood.fslikelihood] Computed log-likelihood = -14.0344
2023-07-02 10:34:53,772 [model] Computed derived parameters: {}
2023-07-02 10:34:53,772 [model] Posterior to be computed for parameters {'Omega_m': 0.37229384129555476, 'b1': 0.3949864367698106}
2023-07-02 10:34:53,773 [prior] Evaluating prior at array([0.37229384, 0.39498644])
2023-07-02 10:34:53,773 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:53,773 [model] Got input parameters: {'Omega_m': 0.37229384129555476, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.3949864367698106, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:53,773 [classy] Got parameters {'Omega_m': 0.37229384129555476, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:53,773 [classy] Computing new state
2023-07-02 10:34:53,773 [classy] Setting parameters: {'Omega_m': 0.37229384129555476, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:53,819 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.61907819088873}
2023-07-02 10:34:53,819 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:53,821 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.190736
2023-07-02 10:34:53,821 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.3949864367698106, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:53,821 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:53,841 [fs_likelihood.fslikelihood] Computed log-likelihood = -11.4615
2023-07-02 10:34:53,841 [model] Computed derived parameters: {}
2023-07-02 10:34:53,841 [model] Posterior to be computed for parameters {'Omega_m': 0.3139198367804066, 'b1': 0.5111506359698931}
2023-07-02 10:34:53,841 [prior] Evaluating prior at array([0.31391984, 0.51115064])
2023-07-02 10:34:53,842 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:53,842 [model] Got input parameters: {'Omega_m': 0.3139198367804066, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5111506359698931, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:53,842 [classy] Got parameters {'Omega_m': 0.3139198367804066, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:53,842 [classy] Re-using computed results
2023-07-02 10:34:53,842 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.08769832156304}
2023-07-02 10:34:53,842 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:53,842 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5111506359698931, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:53,842 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:53,861 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.70519
2023-07-02 10:34:53,861 [model] Computed derived parameters: {}
2023-07-02 10:34:53,861 [mcmc] New sample, #895:
Omega_m:0.3139198, b1:0.5013697
2023-07-02 10:34:53,862 [model] Posterior to be computed for parameters {'Omega_m': 0.320694595379495, 'b1': 0.49880402625385184}
2023-07-02 10:34:53,862 [prior] Evaluating prior at array([0.3206946 , 0.49880403])
2023-07-02 10:34:53,862 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:53,862 [model] Got input parameters: {'Omega_m': 0.320694595379495, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49880402625385184, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:53,862 [classy] Got parameters {'Omega_m': 0.320694595379495, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:53,862 [classy] Computing new state
2023-07-02 10:34:53,862 [classy] Setting parameters: {'Omega_m': 0.320694595379495, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:53,908 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.28355388400675}
2023-07-02 10:34:53,908 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:53,910 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00425293
2023-07-02 10:34:53,910 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49880402625385184, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:53,910 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:53,929 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.54908
2023-07-02 10:34:53,929 [model] Computed derived parameters: {}
2023-07-02 10:34:53,929 [model] Posterior to be computed for parameters {'Omega_m': 0.3139198367804066, 'b1': 0.5305763960350792}
2023-07-02 10:34:53,930 [prior] Evaluating prior at array([0.31391984, 0.5305764 ])
2023-07-02 10:34:53,930 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:53,930 [model] Got input parameters: {'Omega_m': 0.3139198367804066, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5305763960350792, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:53,930 [classy] Got parameters {'Omega_m': 0.3139198367804066, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:53,930 [classy] Re-using computed results
2023-07-02 10:34:53,930 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.08769832156304}
2023-07-02 10:34:53,930 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:53,930 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5305763960350792, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:53,930 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:53,950 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.703992
2023-07-02 10:34:53,950 [model] Computed derived parameters: {}
2023-07-02 10:34:53,950 [model] Posterior to be computed for parameters {'Omega_m': 0.32316158850125043, 'b1': 0.4943080725160212}
2023-07-02 10:34:53,950 [prior] Evaluating prior at array([0.32316159, 0.49430807])
2023-07-02 10:34:53,950 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:53,950 [model] Got input parameters: {'Omega_m': 0.32316158850125043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4943080725160212, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:53,950 [classy] Got parameters {'Omega_m': 0.32316158850125043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:53,950 [classy] Computing new state
2023-07-02 10:34:53,950 [classy] Setting parameters: {'Omega_m': 0.32316158850125043, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:53,996 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.99448764125827}
2023-07-02 10:34:53,996 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:53,998 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00701161
2023-07-02 10:34:53,998 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4943080725160212, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:53,998 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:54,018 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.3707
2023-07-02 10:34:54,018 [model] Computed derived parameters: {}
2023-07-02 10:34:54,018 [mcmc] New sample, #896:
Omega_m:0.3139198, b1:0.5111506
2023-07-02 10:34:54,018 [model] Posterior to be computed for parameters {'Omega_m': 0.32316158850125043, 'b1': 0.4340575227027353}
2023-07-02 10:34:54,018 [prior] Evaluating prior at array([0.32316159, 0.43405752])
2023-07-02 10:34:54,018 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:54,018 [model] Got input parameters: {'Omega_m': 0.32316158850125043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4340575227027353, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:54,018 [classy] Got parameters {'Omega_m': 0.32316158850125043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:54,018 [classy] Re-using computed results
2023-07-02 10:34:54,018 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.99448764125827}
2023-07-02 10:34:54,018 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:54,018 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4340575227027353, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:54,018 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:54,038 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.25121
2023-07-02 10:34:54,038 [model] Computed derived parameters: {}
2023-07-02 10:34:54,038 [model] Posterior to be computed for parameters {'Omega_m': 0.28731423267394973, 'b1': 0.5596378263778474}
2023-07-02 10:34:54,038 [prior] Evaluating prior at array([0.28731423, 0.55963783])
2023-07-02 10:34:54,039 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:54,039 [model] Got input parameters: {'Omega_m': 0.28731423267394973, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5596378263778474, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:54,039 [classy] Got parameters {'Omega_m': 0.28731423267394973, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:54,039 [classy] Computing new state
2023-07-02 10:34:54,039 [classy] Setting parameters: {'Omega_m': 0.28731423267394973, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:54,085 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.4017510319698}
2023-07-02 10:34:54,085 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:54,087 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0416247
2023-07-02 10:34:54,087 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5596378263778474, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:54,087 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:54,107 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.20178
2023-07-02 10:34:54,107 [model] Computed derived parameters: {}
2023-07-02 10:34:54,107 [model] Posterior to be computed for parameters {'Omega_m': 0.32316158850125043, 'b1': 0.5223480446800762}
2023-07-02 10:34:54,107 [prior] Evaluating prior at array([0.32316159, 0.52234804])
2023-07-02 10:34:54,107 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:54,107 [model] Got input parameters: {'Omega_m': 0.32316158850125043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5223480446800762, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:54,107 [classy] Got parameters {'Omega_m': 0.32316158850125043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:54,107 [classy] Re-using computed results
2023-07-02 10:34:54,107 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.99448764125827}
2023-07-02 10:34:54,107 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:54,107 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5223480446800762, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:54,107 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:54,128 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.23739
2023-07-02 10:34:54,128 [model] Computed derived parameters: {}
2023-07-02 10:34:54,129 [model] Posterior to be computed for parameters {'Omega_m': 0.2809208083190558, 'b1': 0.5712894762638713}
2023-07-02 10:34:54,129 [prior] Evaluating prior at array([0.28092081, 0.57128948])
2023-07-02 10:34:54,129 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:54,129 [model] Got input parameters: {'Omega_m': 0.2809208083190558, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5712894762638713, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:54,129 [classy] Got parameters {'Omega_m': 0.2809208083190558, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:54,129 [classy] Computing new state
2023-07-02 10:34:54,129 [classy] Setting parameters: {'Omega_m': 0.2809208083190558, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:54,175 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.23784758103838}
2023-07-02 10:34:54,176 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:54,177 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0664483
2023-07-02 10:34:54,177 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5712894762638713, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:54,177 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:54,198 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.9169
2023-07-02 10:34:54,198 [model] Computed derived parameters: {}
2023-07-02 10:34:54,198 [model] Posterior to be computed for parameters {'Omega_m': 0.32316158850125043, 'b1': 0.5244624795738022}
2023-07-02 10:34:54,198 [prior] Evaluating prior at array([0.32316159, 0.52446248])
2023-07-02 10:34:54,198 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:54,198 [model] Got input parameters: {'Omega_m': 0.32316158850125043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5244624795738022, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:54,198 [classy] Got parameters {'Omega_m': 0.32316158850125043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:54,198 [classy] Re-using computed results
2023-07-02 10:34:54,198 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.99448764125827}
2023-07-02 10:34:54,198 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:54,198 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5244624795738022, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:54,198 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:54,217 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.69773
2023-07-02 10:34:54,217 [model] Computed derived parameters: {}
2023-07-02 10:34:54,218 [model] Posterior to be computed for parameters {'Omega_m': 0.2668085005144599, 'b1': 0.5970083493583949}
2023-07-02 10:34:54,218 [prior] Evaluating prior at array([0.2668085 , 0.59700835])
2023-07-02 10:34:54,218 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:54,218 [model] Got input parameters: {'Omega_m': 0.2668085005144599, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5970083493583949, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:54,218 [classy] Got parameters {'Omega_m': 0.2668085005144599, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:54,218 [classy] Computing new state
2023-07-02 10:34:54,218 [classy] Setting parameters: {'Omega_m': 0.2668085005144599, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:54,264 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.14253734802193}
2023-07-02 10:34:54,264 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:54,266 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.144296
2023-07-02 10:34:54,266 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5970083493583949, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:54,266 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:54,285 [fs_likelihood.fslikelihood] Computed log-likelihood = -13.4201
2023-07-02 10:34:54,285 [model] Computed derived parameters: {}
2023-07-02 10:34:54,286 [model] Posterior to be computed for parameters {'Omega_m': 0.32316158850125043, 'b1': 0.4991548333232292}
2023-07-02 10:34:54,286 [prior] Evaluating prior at array([0.32316159, 0.49915483])
2023-07-02 10:34:54,286 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:54,286 [model] Got input parameters: {'Omega_m': 0.32316158850125043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4991548333232292, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:54,286 [classy] Got parameters {'Omega_m': 0.32316158850125043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:54,286 [classy] Re-using computed results
2023-07-02 10:34:54,286 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.99448764125827}
2023-07-02 10:34:54,286 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:54,286 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4991548333232292, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:54,286 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:54,306 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.07089
2023-07-02 10:34:54,306 [model] Computed derived parameters: {}
2023-07-02 10:34:54,306 [mcmc] New sample, #897:
Omega_m:0.3231616, b1:0.4943081
2023-07-02 10:34:54,306 [model] Posterior to be computed for parameters {'Omega_m': 0.35100722015888947, 'b1': 0.4484077636904055}
2023-07-02 10:34:54,306 [prior] Evaluating prior at array([0.35100722, 0.44840776])
2023-07-02 10:34:54,307 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:54,307 [model] Got input parameters: {'Omega_m': 0.35100722015888947, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4484077636904055, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:54,307 [classy] Got parameters {'Omega_m': 0.35100722015888947, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:54,307 [classy] Computing new state
2023-07-02 10:34:54,307 [classy] Setting parameters: {'Omega_m': 0.35100722015888947, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:54,353 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.8629718663464}
2023-07-02 10:34:54,353 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:54,355 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0831659
2023-07-02 10:34:54,355 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4484077636904055, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:54,355 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:54,375 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.75233
2023-07-02 10:34:54,375 [model] Computed derived parameters: {}
2023-07-02 10:34:54,375 [model] Posterior to be computed for parameters {'Omega_m': 0.32316158850125043, 'b1': 0.4483250823189745}
2023-07-02 10:34:54,375 [prior] Evaluating prior at array([0.32316159, 0.44832508])
2023-07-02 10:34:54,375 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:54,375 [model] Got input parameters: {'Omega_m': 0.32316158850125043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4483250823189745, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:54,375 [classy] Got parameters {'Omega_m': 0.32316158850125043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:54,375 [classy] Re-using computed results
2023-07-02 10:34:54,375 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.99448764125827}
2023-07-02 10:34:54,375 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:54,375 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4483250823189745, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:54,375 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:54,395 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.0412
2023-07-02 10:34:54,395 [model] Computed derived parameters: {}
2023-07-02 10:34:54,396 [model] Posterior to be computed for parameters {'Omega_m': 0.24839646289155248, 'b1': 0.6354099947097832}
2023-07-02 10:34:54,396 [prior] Evaluating prior at array([0.24839646, 0.63540999])
2023-07-02 10:34:54,396 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:54,396 [model] Got input parameters: {'Omega_m': 0.24839646289155248, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6354099947097832, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:54,396 [classy] Got parameters {'Omega_m': 0.24839646289155248, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:54,396 [classy] Computing new state
2023-07-02 10:34:54,396 [classy] Setting parameters: {'Omega_m': 0.24839646289155248, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:54,442 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 155.75936900976455}
2023-07-02 10:34:54,442 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:54,444 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.298809
2023-07-02 10:34:54,444 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6354099947097832, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:54,444 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:54,463 [fs_likelihood.fslikelihood] Computed log-likelihood = -30.8041
2023-07-02 10:34:54,463 [model] Computed derived parameters: {}
2023-07-02 10:34:54,463 [model] Posterior to be computed for parameters {'Omega_m': 0.32316158850125043, 'b1': 0.5188334423060758}
2023-07-02 10:34:54,464 [prior] Evaluating prior at array([0.32316159, 0.51883344])
2023-07-02 10:34:54,464 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:54,464 [model] Got input parameters: {'Omega_m': 0.32316158850125043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5188334423060758, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:54,464 [classy] Got parameters {'Omega_m': 0.32316158850125043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:54,464 [classy] Re-using computed results
2023-07-02 10:34:54,464 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.99448764125827}
2023-07-02 10:34:54,464 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:54,464 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5188334423060758, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:54,464 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:54,483 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.532012
2023-07-02 10:34:54,483 [model] Computed derived parameters: {}
2023-07-02 10:34:54,483 [model] Posterior to be computed for parameters {'Omega_m': 0.3765601740626795, 'b1': 0.4018389680163371}
2023-07-02 10:34:54,483 [prior] Evaluating prior at array([0.37656017, 0.40183897])
2023-07-02 10:34:54,483 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:54,483 [model] Got input parameters: {'Omega_m': 0.3765601740626795, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4018389680163371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:54,483 [classy] Got parameters {'Omega_m': 0.3765601740626795, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:54,483 [classy] Computing new state
2023-07-02 10:34:54,483 [classy] Setting parameters: {'Omega_m': 0.3765601740626795, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:54,529 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.18373389293097}
2023-07-02 10:34:54,530 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:54,532 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.216824
2023-07-02 10:34:54,532 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4018389680163371, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:54,532 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:54,551 [fs_likelihood.fslikelihood] Computed log-likelihood = -13.782
2023-07-02 10:34:54,551 [model] Computed derived parameters: {}
2023-07-02 10:34:54,552 [model] Posterior to be computed for parameters {'Omega_m': 0.32316158850125043, 'b1': 0.4913492916866584}
2023-07-02 10:34:54,552 [prior] Evaluating prior at array([0.32316159, 0.49134929])
2023-07-02 10:34:54,552 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:54,552 [model] Got input parameters: {'Omega_m': 0.32316158850125043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4913492916866584, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:54,552 [classy] Got parameters {'Omega_m': 0.32316158850125043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:54,552 [classy] Re-using computed results
2023-07-02 10:34:54,552 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.99448764125827}
2023-07-02 10:34:54,552 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:54,552 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4913492916866584, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:54,552 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:54,571 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.48919
2023-07-02 10:34:54,571 [model] Computed derived parameters: {}
2023-07-02 10:34:54,571 [mcmc] New sample, #898:
Omega_m:0.3231616, b1:0.4991548
2023-07-02 10:34:54,572 [model] Posterior to be computed for parameters {'Omega_m': 0.35690214456083547, 'b1': 0.42985905979471195}
2023-07-02 10:34:54,572 [prior] Evaluating prior at array([0.35690214, 0.42985906])
2023-07-02 10:34:54,572 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:54,572 [model] Got input parameters: {'Omega_m': 0.35690214456083547, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42985905979471195, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:54,572 [classy] Got parameters {'Omega_m': 0.35690214456083547, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:54,572 [classy] Computing new state
2023-07-02 10:34:54,572 [classy] Setting parameters: {'Omega_m': 0.35690214456083547, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:54,618 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.22922151754042}
2023-07-02 10:34:54,618 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:54,620 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.109012
2023-07-02 10:34:54,620 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42985905979471195, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:54,620 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:54,639 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.33931
2023-07-02 10:34:54,639 [model] Computed derived parameters: {}
2023-07-02 10:34:54,640 [model] Posterior to be computed for parameters {'Omega_m': 0.32316158850125043, 'b1': 0.4841769850395403}
2023-07-02 10:34:54,640 [prior] Evaluating prior at array([0.32316159, 0.48417699])
2023-07-02 10:34:54,640 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:54,640 [model] Got input parameters: {'Omega_m': 0.32316158850125043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4841769850395403, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:54,640 [classy] Got parameters {'Omega_m': 0.32316158850125043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:54,640 [classy] Re-using computed results
2023-07-02 10:34:54,640 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.99448764125827}
2023-07-02 10:34:54,640 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:54,640 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4841769850395403, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:54,640 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:54,660 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.5764
2023-07-02 10:34:54,660 [model] Computed derived parameters: {}
2023-07-02 10:34:54,660 [mcmc] New sample, #899:
Omega_m:0.3231616, b1:0.4913493
2023-07-02 10:34:54,660 [model] Posterior to be computed for parameters {'Omega_m': 0.302682446325695, 'b1': 0.5214990492965492}
2023-07-02 10:34:54,660 [prior] Evaluating prior at array([0.30268245, 0.52149905])
2023-07-02 10:34:54,660 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:54,660 [model] Got input parameters: {'Omega_m': 0.302682446325695, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5214990492965492, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:54,660 [classy] Got parameters {'Omega_m': 0.302682446325695, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:54,660 [classy] Computing new state
2023-07-02 10:34:54,660 [classy] Setting parameters: {'Omega_m': 0.302682446325695, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:54,707 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.4561925742721}
2023-07-02 10:34:54,707 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:54,709 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0062402
2023-07-02 10:34:54,709 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5214990492965492, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:54,709 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:54,728 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.99544
2023-07-02 10:34:54,728 [model] Computed derived parameters: {}
2023-07-02 10:34:54,729 [model] Posterior to be computed for parameters {'Omega_m': 0.32316158850125043, 'b1': 0.4803420982604379}
2023-07-02 10:34:54,729 [prior] Evaluating prior at array([0.32316159, 0.4803421 ])
2023-07-02 10:34:54,729 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:54,729 [model] Got input parameters: {'Omega_m': 0.32316158850125043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4803420982604379, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:54,729 [classy] Got parameters {'Omega_m': 0.32316158850125043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:54,729 [classy] Re-using computed results
2023-07-02 10:34:54,729 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.99448764125827}
2023-07-02 10:34:54,729 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:54,729 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4803420982604379, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:54,729 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:54,749 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.50845
2023-07-02 10:34:54,749 [model] Computed derived parameters: {}
2023-07-02 10:34:54,749 [mcmc] New sample, #900:
Omega_m:0.3231616, b1:0.484177
2023-07-02 10:34:54,749 [model] Posterior to be computed for parameters {'Omega_m': 0.3898986620957532, 'b1': 0.3587176020941959}
2023-07-02 10:34:54,749 [prior] Evaluating prior at array([0.38989866, 0.3587176 ])
2023-07-02 10:34:54,749 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:54,749 [model] Got input parameters: {'Omega_m': 0.3898986620957532, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.3587176020941959, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:54,749 [classy] Got parameters {'Omega_m': 0.3898986620957532, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:54,749 [classy] Computing new state
2023-07-02 10:34:54,749 [classy] Setting parameters: {'Omega_m': 0.3898986620957532, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:54,795 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 138.85194644592906}
2023-07-02 10:34:54,795 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:54,797 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.307287
2023-07-02 10:34:54,797 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.3587176020941959, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:54,797 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:54,817 [fs_likelihood.fslikelihood] Computed log-likelihood = -20.0417
2023-07-02 10:34:54,817 [model] Computed derived parameters: {}
2023-07-02 10:34:54,817 [model] Posterior to be computed for parameters {'Omega_m': 0.32316158850125043, 'b1': 0.4372556356827902}
2023-07-02 10:34:54,817 [prior] Evaluating prior at array([0.32316159, 0.43725564])
2023-07-02 10:34:54,817 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:54,817 [model] Got input parameters: {'Omega_m': 0.32316158850125043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4372556356827902, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:54,817 [classy] Got parameters {'Omega_m': 0.32316158850125043, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:54,817 [classy] Re-using computed results
2023-07-02 10:34:54,818 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.99448764125827}
2023-07-02 10:34:54,818 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:54,818 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4372556356827902, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:54,818 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:54,837 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.44835
2023-07-02 10:34:54,837 [model] Computed derived parameters: {}
2023-07-02 10:34:54,837 [model] Posterior to be computed for parameters {'Omega_m': 0.3075160781289959, 'b1': 0.5088551452641338}
2023-07-02 10:34:54,837 [prior] Evaluating prior at array([0.30751608, 0.50885515])
2023-07-02 10:34:54,837 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:54,837 [model] Got input parameters: {'Omega_m': 0.3075160781289959, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5088551452641338, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:54,837 [classy] Got parameters {'Omega_m': 0.3075160781289959, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:54,837 [classy] Computing new state
2023-07-02 10:34:54,837 [classy] Setting parameters: {'Omega_m': 0.3075160781289959, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:54,883 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.8621621289191}
2023-07-02 10:34:54,883 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:54,885 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00173482
2023-07-02 10:34:54,885 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5088551452641338, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:54,885 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:54,905 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.51579
2023-07-02 10:34:54,906 [model] Computed derived parameters: {}
2023-07-02 10:34:54,906 [mcmc] New sample, #901:
Omega_m:0.3231616, b1:0.4803421
2023-07-02 10:34:54,906 [model] Posterior to be computed for parameters {'Omega_m': 0.3075160781289959, 'b1': 0.5375629126592832}
2023-07-02 10:34:54,906 [prior] Evaluating prior at array([0.30751608, 0.53756291])
2023-07-02 10:34:54,906 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:54,906 [model] Got input parameters: {'Omega_m': 0.3075160781289959, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5375629126592832, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:54,906 [classy] Got parameters {'Omega_m': 0.3075160781289959, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:54,906 [classy] Re-using computed results
2023-07-02 10:34:54,906 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.8621621289191}
2023-07-02 10:34:54,906 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:54,906 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5375629126592832, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:54,906 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:54,925 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.05544
2023-07-02 10:34:54,925 [model] Computed derived parameters: {}
2023-07-02 10:34:54,926 [model] Posterior to be computed for parameters {'Omega_m': 0.31751148301416177, 'b1': 0.4906390920622441}
2023-07-02 10:34:54,926 [prior] Evaluating prior at array([0.31751148, 0.49063909])
2023-07-02 10:34:54,926 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:54,926 [model] Got input parameters: {'Omega_m': 0.31751148301416177, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4906390920622441, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:54,926 [classy] Got parameters {'Omega_m': 0.31751148301416177, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:54,926 [classy] Computing new state
2023-07-02 10:34:54,926 [classy] Setting parameters: {'Omega_m': 0.31751148301416177, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:54,972 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.6594737090078}
2023-07-02 10:34:54,972 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:54,974 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00173304
2023-07-02 10:34:54,974 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4906390920622441, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:54,974 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:54,993 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.82547
2023-07-02 10:34:54,993 [model] Computed derived parameters: {}
2023-07-02 10:34:54,993 [mcmc] New sample, #902:
Omega_m:0.3075161, b1:0.5088551
2023-07-02 10:34:54,993 [model] Posterior to be computed for parameters {'Omega_m': 0.31751148301416177, 'b1': 0.5076868045154612}
2023-07-02 10:34:54,993 [prior] Evaluating prior at array([0.31751148, 0.5076868 ])
2023-07-02 10:34:54,993 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:54,994 [model] Got input parameters: {'Omega_m': 0.31751148301416177, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5076868045154612, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:54,994 [classy] Got parameters {'Omega_m': 0.31751148301416177, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:54,994 [classy] Re-using computed results
2023-07-02 10:34:54,994 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.6594737090078}
2023-07-02 10:34:54,994 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:54,994 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5076868045154612, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:54,994 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:55,014 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.50963
2023-07-02 10:34:55,014 [model] Computed derived parameters: {}
2023-07-02 10:34:55,014 [mcmc] New sample, #903:
Omega_m:0.3175115, b1:0.4906391
2023-07-02 10:34:55,014 [model] Posterior to be computed for parameters {'Omega_m': 0.3301572005833629, 'b1': 0.4846407081678777}
2023-07-02 10:34:55,014 [prior] Evaluating prior at array([0.3301572 , 0.48464071])
2023-07-02 10:34:55,014 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:55,014 [model] Got input parameters: {'Omega_m': 0.3301572005833629, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4846407081678777, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:55,014 [classy] Got parameters {'Omega_m': 0.3301572005833629, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:55,014 [classy] Computing new state
2023-07-02 10:34:55,014 [classy] Setting parameters: {'Omega_m': 0.3301572005833629, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:55,060 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.1853929244177}
2023-07-02 10:34:55,061 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:55,062 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0185453
2023-07-02 10:34:55,063 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4846407081678777, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:55,063 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:55,082 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.36134
2023-07-02 10:34:55,082 [model] Computed derived parameters: {}
2023-07-02 10:34:55,082 [model] Posterior to be computed for parameters {'Omega_m': 0.31751148301416177, 'b1': 0.5479424325480224}
2023-07-02 10:34:55,082 [prior] Evaluating prior at array([0.31751148, 0.54794243])
2023-07-02 10:34:55,082 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:55,082 [model] Got input parameters: {'Omega_m': 0.31751148301416177, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5479424325480224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:55,082 [classy] Got parameters {'Omega_m': 0.31751148301416177, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:55,082 [classy] Re-using computed results
2023-07-02 10:34:55,082 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.6594737090078}
2023-07-02 10:34:55,082 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:55,082 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5479424325480224, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:55,082 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:55,102 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.84612
2023-07-02 10:34:55,102 [model] Computed derived parameters: {}
2023-07-02 10:34:55,102 [model] Posterior to be computed for parameters {'Omega_m': 0.34114739825032037, 'b1': 0.464611702069516}
2023-07-02 10:34:55,103 [prior] Evaluating prior at array([0.3411474, 0.4646117])
2023-07-02 10:34:55,103 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:55,103 [model] Got input parameters: {'Omega_m': 0.34114739825032037, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.464611702069516, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:55,103 [classy] Got parameters {'Omega_m': 0.34114739825032037, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:55,103 [classy] Computing new state
2023-07-02 10:34:55,103 [classy] Setting parameters: {'Omega_m': 0.34114739825032037, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:55,152 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.94511168486792}
2023-07-02 10:34:55,152 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:55,153 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0472034
2023-07-02 10:34:55,153 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.464611702069516, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:55,154 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:55,173 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.841575
2023-07-02 10:34:55,173 [model] Computed derived parameters: {}
2023-07-02 10:34:55,173 [model] Posterior to be computed for parameters {'Omega_m': 0.31751148301416177, 'b1': 0.5122688047876915}
2023-07-02 10:34:55,173 [prior] Evaluating prior at array([0.31751148, 0.5122688 ])
2023-07-02 10:34:55,173 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:55,173 [model] Got input parameters: {'Omega_m': 0.31751148301416177, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5122688047876915, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:55,173 [classy] Got parameters {'Omega_m': 0.31751148301416177, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:55,173 [classy] Re-using computed results
2023-07-02 10:34:55,173 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.6594737090078}
2023-07-02 10:34:55,173 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:55,173 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5122688047876915, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:55,173 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:55,193 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.15061
2023-07-02 10:34:55,193 [model] Computed derived parameters: {}
2023-07-02 10:34:55,193 [mcmc] New sample, #904:
Omega_m:0.3175115, b1:0.5076868
2023-07-02 10:34:55,193 [model] Posterior to be computed for parameters {'Omega_m': 0.32916183906328406, 'b1': 0.4910366978295503}
2023-07-02 10:34:55,193 [prior] Evaluating prior at array([0.32916184, 0.4910367 ])
2023-07-02 10:34:55,193 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:55,193 [model] Got input parameters: {'Omega_m': 0.32916183906328406, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4910366978295503, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:55,193 [classy] Got parameters {'Omega_m': 0.32916183906328406, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:55,193 [classy] Computing new state
2023-07-02 10:34:55,193 [classy] Setting parameters: {'Omega_m': 0.32916183906328406, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:55,239 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.29956203614816}
2023-07-02 10:34:55,239 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:55,241 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0165765
2023-07-02 10:34:55,241 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4910366978295503, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:55,241 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:55,261 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.14858
2023-07-02 10:34:55,261 [model] Computed derived parameters: {}
2023-07-02 10:34:55,261 [mcmc] New sample, #905:
Omega_m:0.3175115, b1:0.5122688
2023-07-02 10:34:55,261 [model] Posterior to be computed for parameters {'Omega_m': 0.32916183906328406, 'b1': 0.5443345915555996}
2023-07-02 10:34:55,261 [prior] Evaluating prior at array([0.32916184, 0.54433459])
2023-07-02 10:34:55,262 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:55,262 [model] Got input parameters: {'Omega_m': 0.32916183906328406, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5443345915555996, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:55,262 [classy] Got parameters {'Omega_m': 0.32916183906328406, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:55,262 [classy] Re-using computed results
2023-07-02 10:34:55,262 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.29956203614816}
2023-07-02 10:34:55,262 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:55,262 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5443345915555996, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:55,262 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:55,281 [fs_likelihood.fslikelihood] Computed log-likelihood = -12.3177
2023-07-02 10:34:55,281 [model] Computed derived parameters: {}
2023-07-02 10:34:55,282 [model] Posterior to be computed for parameters {'Omega_m': 0.2847884494375359, 'b1': 0.5719046602039826}
2023-07-02 10:34:55,282 [prior] Evaluating prior at array([0.28478845, 0.57190466])
2023-07-02 10:34:55,282 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:55,282 [model] Got input parameters: {'Omega_m': 0.2847884494375359, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5719046602039826, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:55,282 [classy] Got parameters {'Omega_m': 0.2847884494375359, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:55,282 [classy] Computing new state
2023-07-02 10:34:55,282 [classy] Setting parameters: {'Omega_m': 0.2847884494375359, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:55,328 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.73011776671558}
2023-07-02 10:34:55,328 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:55,330 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0506887
2023-07-02 10:34:55,330 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5719046602039826, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:55,330 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:55,349 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.72246
2023-07-02 10:34:55,349 [model] Computed derived parameters: {}
2023-07-02 10:34:55,350 [model] Posterior to be computed for parameters {'Omega_m': 0.32916183906328406, 'b1': 0.48785865146903673}
2023-07-02 10:34:55,350 [prior] Evaluating prior at array([0.32916184, 0.48785865])
2023-07-02 10:34:55,350 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:55,350 [model] Got input parameters: {'Omega_m': 0.32916183906328406, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48785865146903673, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:55,350 [classy] Got parameters {'Omega_m': 0.32916183906328406, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:55,350 [classy] Re-using computed results
2023-07-02 10:34:55,350 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.29956203614816}
2023-07-02 10:34:55,350 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:55,350 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48785865146903673, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:55,350 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:55,370 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.41091
2023-07-02 10:34:55,370 [model] Computed derived parameters: {}
2023-07-02 10:34:55,370 [mcmc] New sample, #906:
Omega_m:0.3291618, b1:0.4910367
2023-07-02 10:34:55,370 [model] Posterior to be computed for parameters {'Omega_m': 0.34790604443429046, 'b1': 0.4536984102193664}
2023-07-02 10:34:55,370 [prior] Evaluating prior at array([0.34790604, 0.45369841])
2023-07-02 10:34:55,371 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:55,371 [model] Got input parameters: {'Omega_m': 0.34790604443429046, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4536984102193664, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:55,371 [classy] Got parameters {'Omega_m': 0.34790604443429046, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:55,371 [classy] Computing new state
2023-07-02 10:34:55,371 [classy] Setting parameters: {'Omega_m': 0.34790604443429046, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:55,417 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.20029672892326}
2023-07-02 10:34:55,417 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:55,419 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0708538
2023-07-02 10:34:55,419 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4536984102193664, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:55,419 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:55,438 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.77364
2023-07-02 10:34:55,439 [model] Computed derived parameters: {}
2023-07-02 10:34:55,439 [model] Posterior to be computed for parameters {'Omega_m': 0.32916183906328406, 'b1': 0.4474653825408857}
2023-07-02 10:34:55,439 [prior] Evaluating prior at array([0.32916184, 0.44746538])
2023-07-02 10:34:55,439 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:55,439 [model] Got input parameters: {'Omega_m': 0.32916183906328406, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4474653825408857, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:55,439 [classy] Got parameters {'Omega_m': 0.32916183906328406, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:55,439 [classy] Re-using computed results
2023-07-02 10:34:55,439 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.29956203614816}
2023-07-02 10:34:55,439 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:55,439 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4474653825408857, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:55,439 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:55,459 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.0731776
2023-07-02 10:34:55,459 [model] Computed derived parameters: {}
2023-07-02 10:34:55,459 [model] Posterior to be computed for parameters {'Omega_m': 0.286397779034629, 'b1': 0.5657937027811537}
2023-07-02 10:34:55,459 [prior] Evaluating prior at array([0.28639778, 0.5657937 ])
2023-07-02 10:34:55,460 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:55,460 [model] Got input parameters: {'Omega_m': 0.286397779034629, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5657937027811537, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:55,460 [classy] Got parameters {'Omega_m': 0.286397779034629, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:55,460 [classy] Computing new state
2023-07-02 10:34:55,460 [classy] Setting parameters: {'Omega_m': 0.286397779034629, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:55,506 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.52059627145061}
2023-07-02 10:34:55,506 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:55,508 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0448025
2023-07-02 10:34:55,508 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5657937027811537, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:55,508 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:55,527 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.82043
2023-07-02 10:34:55,527 [model] Computed derived parameters: {}
2023-07-02 10:34:55,528 [model] Posterior to be computed for parameters {'Omega_m': 0.32916183906328406, 'b1': 0.46087636653479624}
2023-07-02 10:34:55,528 [prior] Evaluating prior at array([0.32916184, 0.46087637])
2023-07-02 10:34:55,528 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:55,528 [model] Got input parameters: {'Omega_m': 0.32916183906328406, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46087636653479624, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:55,528 [classy] Got parameters {'Omega_m': 0.32916183906328406, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:55,528 [classy] Re-using computed results
2023-07-02 10:34:55,528 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.29956203614816}
2023-07-02 10:34:55,528 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:55,528 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46087636653479624, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:55,528 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:55,547 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.38021
2023-07-02 10:34:55,547 [model] Computed derived parameters: {}
2023-07-02 10:34:55,547 [mcmc] New sample, #907:
Omega_m:0.3291618, b1:0.4878587
2023-07-02 10:34:55,547 [model] Posterior to be computed for parameters {'Omega_m': 0.3194474710915174, 'b1': 0.4785802460503782}
2023-07-02 10:34:55,547 [prior] Evaluating prior at array([0.31944747, 0.47858025])
2023-07-02 10:34:55,548 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:55,548 [model] Got input parameters: {'Omega_m': 0.3194474710915174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4785802460503782, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:55,548 [classy] Got parameters {'Omega_m': 0.3194474710915174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:55,548 [classy] Computing new state
2023-07-02 10:34:55,548 [classy] Setting parameters: {'Omega_m': 0.3194474710915174, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:55,594 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.43043765266833}
2023-07-02 10:34:55,594 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:55,596 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00312485
2023-07-02 10:34:55,596 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4785802460503782, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:55,596 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:55,616 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.32589
2023-07-02 10:34:55,617 [model] Computed derived parameters: {}
2023-07-02 10:34:55,617 [mcmc] New sample, #908:
Omega_m:0.3291618, b1:0.4608764
2023-07-02 10:34:55,617 [model] Posterior to be computed for parameters {'Omega_m': 0.3194474710915174, 'b1': 0.48137026732973026}
2023-07-02 10:34:55,617 [prior] Evaluating prior at array([0.31944747, 0.48137027])
2023-07-02 10:34:55,617 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:55,617 [model] Got input parameters: {'Omega_m': 0.3194474710915174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48137026732973026, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:55,617 [classy] Got parameters {'Omega_m': 0.3194474710915174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:55,617 [classy] Re-using computed results
2023-07-02 10:34:55,617 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.43043765266833}
2023-07-02 10:34:55,617 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:55,617 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48137026732973026, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:55,617 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:55,636 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.50826
2023-07-02 10:34:55,636 [model] Computed derived parameters: {}
2023-07-02 10:34:55,636 [mcmc] New sample, #909:
Omega_m:0.3194475, b1:0.4785802
2023-07-02 10:34:55,636 [model] Posterior to be computed for parameters {'Omega_m': 0.4270028793938878, 'b1': 0.28535669286266263}
2023-07-02 10:34:55,637 [prior] Evaluating prior at array([0.42700288, 0.28535669])
2023-07-02 10:34:55,637 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:55,637 [model] Got input parameters: {'Omega_m': 0.4270028793938878, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.28535669286266263, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:55,637 [classy] Got parameters {'Omega_m': 0.4270028793938878, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:55,637 [classy] Computing new state
2023-07-02 10:34:55,637 [classy] Setting parameters: {'Omega_m': 0.4270028793938878, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:55,683 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 135.36312836889343}
2023-07-02 10:34:55,683 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:55,685 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.621731
2023-07-02 10:34:55,685 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.28535669286266263, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:55,685 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:55,705 [fs_likelihood.fslikelihood] Computed log-likelihood = -41.4071
2023-07-02 10:34:55,705 [model] Computed derived parameters: {}
2023-07-02 10:34:55,705 [model] Posterior to be computed for parameters {'Omega_m': 0.3194474710915174, 'b1': 0.4502241680571882}
2023-07-02 10:34:55,705 [prior] Evaluating prior at array([0.31944747, 0.45022417])
2023-07-02 10:34:55,705 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:55,705 [model] Got input parameters: {'Omega_m': 0.3194474710915174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4502241680571882, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:55,705 [classy] Got parameters {'Omega_m': 0.3194474710915174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:55,705 [classy] Re-using computed results
2023-07-02 10:34:55,705 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.43043765266833}
2023-07-02 10:34:55,705 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:55,705 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4502241680571882, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:55,705 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:55,725 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.76115
2023-07-02 10:34:55,725 [model] Computed derived parameters: {}
2023-07-02 10:34:55,725 [model] Posterior to be computed for parameters {'Omega_m': 0.4178323817123093, 'b1': 0.3020693999090134}
2023-07-02 10:34:55,725 [prior] Evaluating prior at array([0.41783238, 0.3020694 ])
2023-07-02 10:34:55,725 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:55,725 [model] Got input parameters: {'Omega_m': 0.4178323817123093, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.3020693999090134, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:55,725 [classy] Got parameters {'Omega_m': 0.4178323817123093, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:55,725 [classy] Computing new state
2023-07-02 10:34:55,725 [classy] Setting parameters: {'Omega_m': 0.4178323817123093, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:55,772 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 136.19754578874188}
2023-07-02 10:34:55,772 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:55,774 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.536191
2023-07-02 10:34:55,774 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.3020693999090134, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:55,774 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:55,794 [fs_likelihood.fslikelihood] Computed log-likelihood = -35.9468
2023-07-02 10:34:55,794 [model] Computed derived parameters: {}
2023-07-02 10:34:55,795 [model] Posterior to be computed for parameters {'Omega_m': 0.3194474710915174, 'b1': 0.4774971435705008}
2023-07-02 10:34:55,795 [prior] Evaluating prior at array([0.31944747, 0.47749714])
2023-07-02 10:34:55,795 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:55,795 [model] Got input parameters: {'Omega_m': 0.3194474710915174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4774971435705008, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:55,795 [classy] Got parameters {'Omega_m': 0.3194474710915174, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:55,795 [classy] Re-using computed results
2023-07-02 10:34:55,795 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.43043765266833}
2023-07-02 10:34:55,795 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:55,795 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4774971435705008, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:55,795 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:55,816 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.24418
2023-07-02 10:34:55,816 [model] Computed derived parameters: {}
2023-07-02 10:34:55,816 [mcmc] New sample, #910:
Omega_m:0.3194475, b1:0.4813703
2023-07-02 10:34:55,816 [model] Posterior to be computed for parameters {'Omega_m': 0.3233776317108762, 'b1': 0.4703346508294152}
2023-07-02 10:34:55,816 [prior] Evaluating prior at array([0.32337763, 0.47033465])
2023-07-02 10:34:55,816 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:55,816 [model] Got input parameters: {'Omega_m': 0.3233776317108762, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4703346508294152, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:55,817 [classy] Got parameters {'Omega_m': 0.3233776317108762, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:55,817 [classy] Computing new state
2023-07-02 10:34:55,817 [classy] Setting parameters: {'Omega_m': 0.3233776317108762, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:55,864 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.9692645057659}
2023-07-02 10:34:55,864 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:55,866 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0072863
2023-07-02 10:34:55,867 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4703346508294152, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:55,867 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:55,887 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.97551
2023-07-02 10:34:55,887 [model] Computed derived parameters: {}
2023-07-02 10:34:55,887 [mcmc] New sample, #911:
Omega_m:0.3194475, b1:0.4774971
2023-07-02 10:34:55,887 [model] Posterior to be computed for parameters {'Omega_m': 0.3233776317108762, 'b1': 0.47382944431498963}
2023-07-02 10:34:55,887 [prior] Evaluating prior at array([0.32337763, 0.47382944])
2023-07-02 10:34:55,888 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:55,888 [model] Got input parameters: {'Omega_m': 0.3233776317108762, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47382944431498963, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:55,888 [classy] Got parameters {'Omega_m': 0.3233776317108762, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:55,888 [classy] Re-using computed results
2023-07-02 10:34:55,888 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.9692645057659}
2023-07-02 10:34:55,888 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:55,888 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47382944431498963, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:55,888 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:55,908 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.21872
2023-07-02 10:34:55,908 [model] Computed derived parameters: {}
2023-07-02 10:34:55,908 [mcmc] New sample, #912:
Omega_m:0.3233776, b1:0.4703347
2023-07-02 10:34:55,908 [model] Posterior to be computed for parameters {'Omega_m': 0.3131703737439316, 'b1': 0.49243158763058675}
2023-07-02 10:34:55,908 [prior] Evaluating prior at array([0.31317037, 0.49243159])
2023-07-02 10:34:55,908 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:55,908 [model] Got input parameters: {'Omega_m': 0.3131703737439316, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49243158763058675, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:55,908 [classy] Got parameters {'Omega_m': 0.3131703737439316, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:55,908 [classy] Computing new state
2023-07-02 10:34:55,908 [classy] Setting parameters: {'Omega_m': 0.3131703737439316, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:55,955 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.17761318028408}
2023-07-02 10:34:55,955 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:55,956 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000231222
2023-07-02 10:34:55,956 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49243158763058675, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:55,957 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:55,976 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.56746
2023-07-02 10:34:55,976 [model] Computed derived parameters: {}
2023-07-02 10:34:55,976 [mcmc] New sample, #913:
Omega_m:0.3233776, b1:0.4738294
2023-07-02 10:34:55,976 [model] Posterior to be computed for parameters {'Omega_m': 0.3131703737439316, 'b1': 0.5131003884334429}
2023-07-02 10:34:55,976 [prior] Evaluating prior at array([0.31317037, 0.51310039])
2023-07-02 10:34:55,977 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:55,977 [model] Got input parameters: {'Omega_m': 0.3131703737439316, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5131003884334429, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:55,977 [classy] Got parameters {'Omega_m': 0.3131703737439316, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:55,977 [classy] Re-using computed results
2023-07-02 10:34:55,977 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.17761318028408}
2023-07-02 10:34:55,977 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:55,977 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5131003884334429, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:55,977 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:55,996 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.66196
2023-07-02 10:34:55,996 [model] Computed derived parameters: {}
2023-07-02 10:34:55,996 [mcmc] New sample, #914:
Omega_m:0.3131704, b1:0.4924316
2023-07-02 10:34:55,996 [model] Posterior to be computed for parameters {'Omega_m': 0.33702001684498883, 'b1': 0.4696357791888788}
2023-07-02 10:34:55,996 [prior] Evaluating prior at array([0.33702002, 0.46963578])
2023-07-02 10:34:55,996 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:55,997 [model] Got input parameters: {'Omega_m': 0.33702001684498883, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4696357791888788, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:55,997 [classy] Got parameters {'Omega_m': 0.33702001684498883, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:55,997 [classy] Computing new state
2023-07-02 10:34:55,997 [classy] Setting parameters: {'Omega_m': 0.33702001684498883, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:56,043 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.40661016458202}
2023-07-02 10:34:56,043 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:56,045 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0349796
2023-07-02 10:34:56,045 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4696357791888788, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:56,045 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:56,065 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.250856
2023-07-02 10:34:56,065 [model] Computed derived parameters: {}
2023-07-02 10:34:56,065 [model] Posterior to be computed for parameters {'Omega_m': 0.3131703737439316, 'b1': 0.49876108865180324}
2023-07-02 10:34:56,065 [prior] Evaluating prior at array([0.31317037, 0.49876109])
2023-07-02 10:34:56,065 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:56,065 [model] Got input parameters: {'Omega_m': 0.3131703737439316, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49876108865180324, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:56,065 [classy] Got parameters {'Omega_m': 0.3131703737439316, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:56,065 [classy] Re-using computed results
2023-07-02 10:34:56,065 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.17761318028408}
2023-07-02 10:34:56,066 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:56,066 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49876108865180324, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:56,066 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:56,085 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.83903
2023-07-02 10:34:56,085 [model] Computed derived parameters: {}
2023-07-02 10:34:56,085 [mcmc] New sample, #915:
Omega_m:0.3131704, b1:0.5131004
2023-07-02 10:34:56,085 [model] Posterior to be computed for parameters {'Omega_m': 0.299357160852926, 'b1': 0.5239348783884269}
2023-07-02 10:34:56,085 [prior] Evaluating prior at array([0.29935716, 0.52393488])
2023-07-02 10:34:56,085 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:56,085 [model] Got input parameters: {'Omega_m': 0.299357160852926, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5239348783884269, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:56,085 [classy] Got parameters {'Omega_m': 0.299357160852926, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:56,085 [classy] Computing new state
2023-07-02 10:34:56,085 [classy] Setting parameters: {'Omega_m': 0.299357160852926, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:56,133 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.86972364516754}
2023-07-02 10:34:56,133 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:56,135 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0111238
2023-07-02 10:34:56,135 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5239348783884269, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:56,135 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:56,155 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.35865
2023-07-02 10:34:56,155 [model] Computed derived parameters: {}
2023-07-02 10:34:56,156 [model] Posterior to be computed for parameters {'Omega_m': 0.3131703737439316, 'b1': 0.5134732519716683}
2023-07-02 10:34:56,156 [prior] Evaluating prior at array([0.31317037, 0.51347325])
2023-07-02 10:34:56,156 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:56,156 [model] Got input parameters: {'Omega_m': 0.3131703737439316, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5134732519716683, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:56,156 [classy] Got parameters {'Omega_m': 0.3131703737439316, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:56,156 [classy] Re-using computed results
2023-07-02 10:34:56,156 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.17761318028408}
2023-07-02 10:34:56,156 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:56,156 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5134732519716683, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:56,156 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:56,176 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.64238
2023-07-02 10:34:56,176 [model] Computed derived parameters: {}
2023-07-02 10:34:56,176 [mcmc] New sample, #916:
Omega_m:0.3131704, b1:0.4987611
2023-07-02 10:34:56,176 [model] Posterior to be computed for parameters {'Omega_m': 0.3455157443127441, 'b1': 0.45452566576725506}
2023-07-02 10:34:56,176 [prior] Evaluating prior at array([0.34551574, 0.45452567])
2023-07-02 10:34:56,176 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:56,176 [model] Got input parameters: {'Omega_m': 0.3455157443127441, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45452566576725506, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:56,176 [classy] Got parameters {'Omega_m': 0.3455157443127441, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:56,177 [classy] Computing new state
2023-07-02 10:34:56,177 [classy] Setting parameters: {'Omega_m': 0.3455157443127441, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:56,223 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.46217280870752}
2023-07-02 10:34:56,223 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:56,225 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0619852
2023-07-02 10:34:56,225 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45452566576725506, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:56,225 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:56,244 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.86472
2023-07-02 10:34:56,245 [model] Computed derived parameters: {}
2023-07-02 10:34:56,245 [model] Posterior to be computed for parameters {'Omega_m': 0.3131703737439316, 'b1': 0.5745134283309952}
2023-07-02 10:34:56,245 [prior] Evaluating prior at array([0.31317037, 0.57451343])
2023-07-02 10:34:56,245 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:56,245 [model] Got input parameters: {'Omega_m': 0.3131703737439316, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5745134283309952, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:56,245 [classy] Got parameters {'Omega_m': 0.3131703737439316, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:56,245 [classy] Re-using computed results
2023-07-02 10:34:56,245 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.17761318028408}
2023-07-02 10:34:56,245 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:56,245 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5745134283309952, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:56,245 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:56,265 [fs_likelihood.fslikelihood] Computed log-likelihood = -11.5864
2023-07-02 10:34:56,265 [model] Computed derived parameters: {}
2023-07-02 10:34:56,265 [model] Posterior to be computed for parameters {'Omega_m': 0.31671288668477177, 'b1': 0.5070172249332341}
2023-07-02 10:34:56,265 [prior] Evaluating prior at array([0.31671289, 0.50701722])
2023-07-02 10:34:56,265 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:56,266 [model] Got input parameters: {'Omega_m': 0.31671288668477177, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5070172249332341, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:56,266 [classy] Got parameters {'Omega_m': 0.31671288668477177, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:56,266 [classy] Computing new state
2023-07-02 10:34:56,266 [classy] Setting parameters: {'Omega_m': 0.31671288668477177, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:56,311 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.75431042843647}
2023-07-02 10:34:56,311 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:56,313 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00128759
2023-07-02 10:34:56,313 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5070172249332341, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:56,313 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:56,333 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.65304
2023-07-02 10:34:56,333 [model] Computed derived parameters: {}
2023-07-02 10:34:56,333 [mcmc] New sample, #917:
Omega_m:0.3131704, b1:0.5134733
2023-07-02 10:34:56,333 [model] Posterior to be computed for parameters {'Omega_m': 0.31671288668477177, 'b1': 0.5432245468325416}
2023-07-02 10:34:56,334 [prior] Evaluating prior at array([0.31671289, 0.54322455])
2023-07-02 10:34:56,334 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:56,334 [model] Got input parameters: {'Omega_m': 0.31671288668477177, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5432245468325416, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:56,334 [classy] Got parameters {'Omega_m': 0.31671288668477177, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:56,334 [classy] Re-using computed results
2023-07-02 10:34:56,334 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.75431042843647}
2023-07-02 10:34:56,334 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:56,334 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5432245468325416, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:56,334 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:56,353 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.06484
2023-07-02 10:34:56,353 [model] Computed derived parameters: {}
2023-07-02 10:34:56,353 [model] Posterior to be computed for parameters {'Omega_m': 0.36311208312968063, 'b1': 0.42245734560110565}
2023-07-02 10:34:56,353 [prior] Evaluating prior at array([0.36311208, 0.42245735])
2023-07-02 10:34:56,353 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:56,353 [model] Got input parameters: {'Omega_m': 0.36311208312968063, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42245734560110565, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:56,353 [classy] Got parameters {'Omega_m': 0.36311208312968063, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:56,353 [classy] Computing new state
2023-07-02 10:34:56,353 [classy] Setting parameters: {'Omega_m': 0.36311208312968063, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:56,399 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.57198232053008}
2023-07-02 10:34:56,400 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:56,401 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.139576
2023-07-02 10:34:56,401 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42245734560110565, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:56,402 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:56,422 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.82122
2023-07-02 10:34:56,422 [model] Computed derived parameters: {}
2023-07-02 10:34:56,422 [model] Posterior to be computed for parameters {'Omega_m': 0.31671288668477177, 'b1': 0.4504389790432229}
2023-07-02 10:34:56,422 [prior] Evaluating prior at array([0.31671289, 0.45043898])
2023-07-02 10:34:56,422 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:56,422 [model] Got input parameters: {'Omega_m': 0.31671288668477177, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4504389790432229, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:56,422 [classy] Got parameters {'Omega_m': 0.31671288668477177, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:56,423 [classy] Re-using computed results
2023-07-02 10:34:56,423 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.75431042843647}
2023-07-02 10:34:56,423 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:56,423 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4504389790432229, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:56,423 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:56,442 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.72716
2023-07-02 10:34:56,442 [model] Computed derived parameters: {}
2023-07-02 10:34:56,442 [model] Posterior to be computed for parameters {'Omega_m': 0.3075183982714138, 'b1': 0.523773653714869}
2023-07-02 10:34:56,442 [prior] Evaluating prior at array([0.3075184 , 0.52377365])
2023-07-02 10:34:56,442 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:56,442 [model] Got input parameters: {'Omega_m': 0.3075183982714138, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.523773653714869, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:56,442 [classy] Got parameters {'Omega_m': 0.3075183982714138, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:56,442 [classy] Computing new state
2023-07-02 10:34:56,442 [classy] Setting parameters: {'Omega_m': 0.3075183982714138, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:56,489 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.86187867552863}
2023-07-02 10:34:56,489 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:56,491 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00173337
2023-07-02 10:34:56,491 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.523773653714869, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:56,491 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:56,510 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.32318
2023-07-02 10:34:56,510 [model] Computed derived parameters: {}
2023-07-02 10:34:56,511 [mcmc] New sample, #918:
Omega_m:0.3167129, b1:0.5070172
2023-07-02 10:34:56,511 [model] Posterior to be computed for parameters {'Omega_m': 0.3075183982714138, 'b1': 0.5509308600416843}
2023-07-02 10:34:56,511 [prior] Evaluating prior at array([0.3075184 , 0.55093086])
2023-07-02 10:34:56,511 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:56,511 [model] Got input parameters: {'Omega_m': 0.3075183982714138, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5509308600416843, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:56,511 [classy] Got parameters {'Omega_m': 0.3075183982714138, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:56,511 [classy] Re-using computed results
2023-07-02 10:34:56,511 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.86187867552863}
2023-07-02 10:34:56,511 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:56,511 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5509308600416843, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:56,511 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:56,531 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.21539
2023-07-02 10:34:56,531 [model] Computed derived parameters: {}
2023-07-02 10:34:56,531 [model] Posterior to be computed for parameters {'Omega_m': 0.3210362825164551, 'b1': 0.4991380835290022}
2023-07-02 10:34:56,531 [prior] Evaluating prior at array([0.32103628, 0.49913808])
2023-07-02 10:34:56,531 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:56,531 [model] Got input parameters: {'Omega_m': 0.3210362825164551, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4991380835290022, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:56,531 [classy] Got parameters {'Omega_m': 0.3210362825164551, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:56,531 [classy] Computing new state
2023-07-02 10:34:56,531 [classy] Setting parameters: {'Omega_m': 0.3210362825164551, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:56,577 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.2433976362402}
2023-07-02 10:34:56,578 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:56,579 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00459343
2023-07-02 10:34:56,579 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4991380835290022, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:56,579 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:56,599 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.47937
2023-07-02 10:34:56,599 [model] Computed derived parameters: {}
2023-07-02 10:34:56,599 [mcmc] New sample, #919:
Omega_m:0.3075184, b1:0.5237737
2023-07-02 10:34:56,599 [model] Posterior to be computed for parameters {'Omega_m': 0.3210362825164551, 'b1': 0.4716483679978067}
2023-07-02 10:34:56,599 [prior] Evaluating prior at array([0.32103628, 0.47164837])
2023-07-02 10:34:56,599 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:56,599 [model] Got input parameters: {'Omega_m': 0.3210362825164551, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4716483679978067, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:56,599 [classy] Got parameters {'Omega_m': 0.3210362825164551, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:56,599 [classy] Re-using computed results
2023-07-02 10:34:56,599 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.2433976362402}
2023-07-02 10:34:56,599 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:56,599 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4716483679978067, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:56,599 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:56,619 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.9008
2023-07-02 10:34:56,619 [model] Computed derived parameters: {}
2023-07-02 10:34:56,619 [mcmc] New sample, #920:
Omega_m:0.3210363, b1:0.4991381
2023-07-02 10:34:56,620 [model] Posterior to be computed for parameters {'Omega_m': 0.2874320088290671, 'b1': 0.5328902330681043}
2023-07-02 10:34:56,620 [prior] Evaluating prior at array([0.28743201, 0.53289023])
2023-07-02 10:34:56,620 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:56,620 [model] Got input parameters: {'Omega_m': 0.2874320088290671, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5328902330681043, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:56,620 [classy] Got parameters {'Omega_m': 0.2874320088290671, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:56,620 [classy] Computing new state
2023-07-02 10:34:56,620 [classy] Setting parameters: {'Omega_m': 0.2874320088290671, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:56,666 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.38649934654646}
2023-07-02 10:34:56,666 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:56,668 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0412253
2023-07-02 10:34:56,668 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5328902330681043, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:56,668 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:56,688 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.7265
2023-07-02 10:34:56,688 [model] Computed derived parameters: {}
2023-07-02 10:34:56,688 [model] Posterior to be computed for parameters {'Omega_m': 0.3210362825164551, 'b1': 0.6537912007354751}
2023-07-02 10:34:56,688 [prior] Evaluating prior at array([0.32103628, 0.6537912 ])
2023-07-02 10:34:56,689 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:56,689 [model] Got input parameters: {'Omega_m': 0.3210362825164551, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6537912007354751, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:56,689 [classy] Got parameters {'Omega_m': 0.3210362825164551, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:56,689 [classy] Re-using computed results
2023-07-02 10:34:56,689 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.2433976362402}
2023-07-02 10:34:56,689 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:56,689 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6537912007354751, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:56,689 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:56,708 [fs_likelihood.fslikelihood] Computed log-likelihood = -83.3729
2023-07-02 10:34:56,708 [model] Computed derived parameters: {}
2023-07-02 10:34:56,708 [model] Posterior to be computed for parameters {'Omega_m': 0.32177666221248546, 'b1': 0.4702990683858917}
2023-07-02 10:34:56,708 [prior] Evaluating prior at array([0.32177666, 0.47029907])
2023-07-02 10:34:56,708 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:56,708 [model] Got input parameters: {'Omega_m': 0.32177666221248546, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4702990683858917, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:56,709 [classy] Got parameters {'Omega_m': 0.32177666221248546, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:56,709 [classy] Computing new state
2023-07-02 10:34:56,709 [classy] Setting parameters: {'Omega_m': 0.32177666221248546, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:56,755 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.1565201693537}
2023-07-02 10:34:56,755 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:56,757 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00537722
2023-07-02 10:34:56,757 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4702990683858917, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:56,757 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:56,777 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.84991
2023-07-02 10:34:56,777 [model] Computed derived parameters: {}
2023-07-02 10:34:56,777 [mcmc] New sample, #921:
Omega_m:0.3210363, b1:0.4716484
2023-07-02 10:34:56,777 [model] Posterior to be computed for parameters {'Omega_m': 0.32177666221248546, 'b1': 0.4928257359088519}
2023-07-02 10:34:56,777 [prior] Evaluating prior at array([0.32177666, 0.49282574])
2023-07-02 10:34:56,777 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:56,777 [model] Got input parameters: {'Omega_m': 0.32177666221248546, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4928257359088519, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:56,777 [classy] Got parameters {'Omega_m': 0.32177666221248546, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:56,777 [classy] Re-using computed results
2023-07-02 10:34:56,777 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.1565201693537}
2023-07-02 10:34:56,777 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:56,777 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4928257359088519, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:56,777 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:56,797 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.62746
2023-07-02 10:34:56,797 [model] Computed derived parameters: {}
2023-07-02 10:34:56,797 [mcmc] New sample, #922:
Omega_m:0.3217767, b1:0.4702991
2023-07-02 10:34:56,797 [model] Posterior to be computed for parameters {'Omega_m': 0.34726388892606674, 'b1': 0.44637672427629144}
2023-07-02 10:34:56,797 [prior] Evaluating prior at array([0.34726389, 0.44637672])
2023-07-02 10:34:56,797 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:56,797 [model] Got input parameters: {'Omega_m': 0.34726388892606674, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44637672427629144, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:56,797 [classy] Got parameters {'Omega_m': 0.34726388892606674, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:56,797 [classy] Computing new state
2023-07-02 10:34:56,797 [classy] Setting parameters: {'Omega_m': 0.34726388892606674, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:56,844 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.27048819684398}
2023-07-02 10:34:56,844 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:56,846 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0684177
2023-07-02 10:34:56,846 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44637672427629144, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:56,846 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:56,865 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.17388
2023-07-02 10:34:56,865 [model] Computed derived parameters: {}
2023-07-02 10:34:56,866 [model] Posterior to be computed for parameters {'Omega_m': 0.32177666221248546, 'b1': 0.525821282634184}
2023-07-02 10:34:56,866 [prior] Evaluating prior at array([0.32177666, 0.52582128])
2023-07-02 10:34:56,866 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:56,866 [model] Got input parameters: {'Omega_m': 0.32177666221248546, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.525821282634184, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:56,866 [classy] Got parameters {'Omega_m': 0.32177666221248546, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:56,866 [classy] Re-using computed results
2023-07-02 10:34:56,866 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.1565201693537}
2023-07-02 10:34:56,866 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:56,866 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.525821282634184, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:56,866 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:56,886 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.33012
2023-07-02 10:34:56,886 [model] Computed derived parameters: {}
2023-07-02 10:34:56,886 [model] Posterior to be computed for parameters {'Omega_m': 0.3111087875675871, 'b1': 0.5122673267513558}
2023-07-02 10:34:56,886 [prior] Evaluating prior at array([0.31110879, 0.51226733])
2023-07-02 10:34:56,886 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:56,886 [model] Got input parameters: {'Omega_m': 0.3111087875675871, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5122673267513558, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:56,886 [classy] Got parameters {'Omega_m': 0.3111087875675871, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:56,886 [classy] Computing new state
2023-07-02 10:34:56,886 [classy] Setting parameters: {'Omega_m': 0.3111087875675871, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:56,933 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.4259284886849}
2023-07-02 10:34:56,933 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:56,935 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000318744
2023-07-02 10:34:56,935 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5122673267513558, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:56,935 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:56,955 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.76781
2023-07-02 10:34:56,955 [model] Computed derived parameters: {}
2023-07-02 10:34:56,955 [mcmc] New sample, #923:
Omega_m:0.3217767, b1:0.4928257
2023-07-02 10:34:56,955 [model] Posterior to be computed for parameters {'Omega_m': 0.3111087875675871, 'b1': 0.5083165022283158}
2023-07-02 10:34:56,955 [prior] Evaluating prior at array([0.31110879, 0.5083165 ])
2023-07-02 10:34:56,955 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:56,955 [model] Got input parameters: {'Omega_m': 0.3111087875675871, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5083165022283158, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:56,955 [classy] Got parameters {'Omega_m': 0.3111087875675871, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:56,955 [classy] Re-using computed results
2023-07-02 10:34:56,955 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.4259284886849}
2023-07-02 10:34:56,955 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:56,955 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5083165022283158, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:56,955 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:56,975 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.82919
2023-07-02 10:34:56,975 [model] Computed derived parameters: {}
2023-07-02 10:34:56,975 [mcmc] New sample, #924:
Omega_m:0.3111088, b1:0.5122673
2023-07-02 10:34:56,976 [model] Posterior to be computed for parameters {'Omega_m': 0.3273160466727496, 'b1': 0.4787797003170091}
2023-07-02 10:34:56,976 [prior] Evaluating prior at array([0.32731605, 0.4787797 ])
2023-07-02 10:34:56,976 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:56,976 [model] Got input parameters: {'Omega_m': 0.3273160466727496, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4787797003170091, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:56,976 [classy] Got parameters {'Omega_m': 0.3273160466727496, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:56,976 [classy] Computing new state
2023-07-02 10:34:56,976 [classy] Setting parameters: {'Omega_m': 0.3273160466727496, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:57,028 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.51211724486345}
2023-07-02 10:34:57,028 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:57,030 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0132101
2023-07-02 10:34:57,030 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4787797003170091, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:57,030 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:57,049 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.13993
2023-07-02 10:34:57,049 [model] Computed derived parameters: {}
2023-07-02 10:34:57,050 [model] Posterior to be computed for parameters {'Omega_m': 0.3111087875675871, 'b1': 0.48023407527945655}
2023-07-02 10:34:57,050 [prior] Evaluating prior at array([0.31110879, 0.48023408])
2023-07-02 10:34:57,050 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:57,050 [model] Got input parameters: {'Omega_m': 0.3111087875675871, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48023407527945655, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:57,050 [classy] Got parameters {'Omega_m': 0.3111087875675871, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:57,050 [classy] Re-using computed results
2023-07-02 10:34:57,050 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.4259284886849}
2023-07-02 10:34:57,050 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:57,050 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48023407527945655, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:57,050 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:57,069 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.900694
2023-07-02 10:34:57,069 [model] Computed derived parameters: {}
2023-07-02 10:34:57,070 [model] Posterior to be computed for parameters {'Omega_m': 0.30596232428952824, 'b1': 0.5176956369358876}
2023-07-02 10:34:57,070 [prior] Evaluating prior at array([0.30596232, 0.51769564])
2023-07-02 10:34:57,070 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:57,070 [model] Got input parameters: {'Omega_m': 0.30596232428952824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5176956369358876, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:57,070 [classy] Got parameters {'Omega_m': 0.30596232428952824, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:57,070 [classy] Computing new state
2023-07-02 10:34:57,070 [classy] Setting parameters: {'Omega_m': 0.30596232428952824, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:57,116 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.05221140572525}
2023-07-02 10:34:57,117 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:57,118 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00285355
2023-07-02 10:34:57,118 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5176956369358876, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:57,118 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:57,141 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.42649
2023-07-02 10:34:57,141 [model] Computed derived parameters: {}
2023-07-02 10:34:57,141 [model] Posterior to be computed for parameters {'Omega_m': 0.3111087875675871, 'b1': 0.465672419384173}
2023-07-02 10:34:57,141 [prior] Evaluating prior at array([0.31110879, 0.46567242])
2023-07-02 10:34:57,141 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:57,141 [model] Got input parameters: {'Omega_m': 0.3111087875675871, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.465672419384173, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:57,141 [classy] Got parameters {'Omega_m': 0.3111087875675871, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:57,141 [classy] Re-using computed results
2023-07-02 10:34:57,141 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.4259284886849}
2023-07-02 10:34:57,141 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:57,142 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.465672419384173, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:57,142 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:57,161 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.65561
2023-07-02 10:34:57,161 [model] Computed derived parameters: {}
2023-07-02 10:34:57,161 [model] Posterior to be computed for parameters {'Omega_m': 0.312579494523662, 'b1': 0.5056362229936037}
2023-07-02 10:34:57,161 [prior] Evaluating prior at array([0.31257949, 0.50563622])
2023-07-02 10:34:57,161 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:57,161 [model] Got input parameters: {'Omega_m': 0.312579494523662, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5056362229936037, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:57,161 [classy] Got parameters {'Omega_m': 0.312579494523662, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:57,161 [classy] Computing new state
2023-07-02 10:34:57,161 [classy] Setting parameters: {'Omega_m': 0.312579494523662, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:57,207 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.24863826729924}
2023-07-02 10:34:57,207 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:57,209 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000202923
2023-07-02 10:34:57,209 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5056362229936037, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:57,209 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:57,229 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.8858
2023-07-02 10:34:57,229 [model] Computed derived parameters: {}
2023-07-02 10:34:57,229 [mcmc] New sample, #925:
Omega_m:0.3111088, b1:0.5083165
2023-07-02 10:34:57,230 [model] Posterior to be computed for parameters {'Omega_m': 0.312579494523662, 'b1': 0.49739319626336265}
2023-07-02 10:34:57,230 [prior] Evaluating prior at array([0.31257949, 0.4973932 ])
2023-07-02 10:34:57,230 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:57,230 [model] Got input parameters: {'Omega_m': 0.312579494523662, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49739319626336265, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:57,230 [classy] Got parameters {'Omega_m': 0.312579494523662, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:57,230 [classy] Re-using computed results
2023-07-02 10:34:57,230 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.24863826729924}
2023-07-02 10:34:57,230 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:57,230 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49739319626336265, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:57,230 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:57,249 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.74371
2023-07-02 10:34:57,249 [model] Computed derived parameters: {}
2023-07-02 10:34:57,249 [mcmc] New sample, #926:
Omega_m:0.3125795, b1:0.5056362
2023-07-02 10:34:57,249 [model] Posterior to be computed for parameters {'Omega_m': 0.323987510682703, 'b1': 0.47660273988179913}
2023-07-02 10:34:57,250 [prior] Evaluating prior at array([0.32398751, 0.47660274])
2023-07-02 10:34:57,250 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:57,250 [model] Got input parameters: {'Omega_m': 0.323987510682703, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47660273988179913, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:57,250 [classy] Got parameters {'Omega_m': 0.323987510682703, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:57,250 [classy] Computing new state
2023-07-02 10:34:57,250 [classy] Setting parameters: {'Omega_m': 0.323987510682703, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:57,296 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.8981486757012}
2023-07-02 10:34:57,296 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:57,298 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00809002
2023-07-02 10:34:57,298 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47660273988179913, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:57,298 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:57,317 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.35832
2023-07-02 10:34:57,317 [model] Computed derived parameters: {}
2023-07-02 10:34:57,317 [model] Posterior to be computed for parameters {'Omega_m': 0.312579494523662, 'b1': 0.5345294591771685}
2023-07-02 10:34:57,317 [prior] Evaluating prior at array([0.31257949, 0.53452946])
2023-07-02 10:34:57,318 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:57,318 [model] Got input parameters: {'Omega_m': 0.312579494523662, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5345294591771685, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:57,318 [classy] Got parameters {'Omega_m': 0.312579494523662, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:57,318 [classy] Re-using computed results
2023-07-02 10:34:57,318 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.24863826729924}
2023-07-02 10:34:57,318 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:57,318 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5345294591771685, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:57,318 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:57,338 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.429543
2023-07-02 10:34:57,338 [model] Computed derived parameters: {}
2023-07-02 10:34:57,338 [model] Posterior to be computed for parameters {'Omega_m': 0.2956572121328211, 'b1': 0.5282330871802822}
2023-07-02 10:34:57,338 [prior] Evaluating prior at array([0.29565721, 0.52823309])
2023-07-02 10:34:57,338 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:57,338 [model] Got input parameters: {'Omega_m': 0.2956572121328211, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5282330871802822, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:57,338 [classy] Got parameters {'Omega_m': 0.2956572121328211, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:57,338 [classy] Computing new state
2023-07-02 10:34:57,338 [classy] Setting parameters: {'Omega_m': 0.2956572121328211, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:57,384 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.3346270775292}
2023-07-02 10:34:57,385 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:57,386 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0183198
2023-07-02 10:34:57,387 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5282330871802822, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:57,387 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:57,406 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.46046
2023-07-02 10:34:57,406 [model] Computed derived parameters: {}
2023-07-02 10:34:57,406 [model] Posterior to be computed for parameters {'Omega_m': 0.312579494523662, 'b1': 0.49649976779902005}
2023-07-02 10:34:57,406 [prior] Evaluating prior at array([0.31257949, 0.49649977])
2023-07-02 10:34:57,406 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:57,406 [model] Got input parameters: {'Omega_m': 0.312579494523662, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49649976779902005, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:57,406 [classy] Got parameters {'Omega_m': 0.312579494523662, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:57,406 [classy] Re-using computed results
2023-07-02 10:34:57,407 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.24863826729924}
2023-07-02 10:34:57,407 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:57,407 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49649976779902005, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:57,407 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:57,426 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.70667
2023-07-02 10:34:57,426 [model] Computed derived parameters: {}
2023-07-02 10:34:57,427 [mcmc] New sample, #927:
Omega_m:0.3125795, b1:0.4973932
2023-07-02 10:34:57,427 [model] Posterior to be computed for parameters {'Omega_m': 0.319789746535691, 'b1': 0.4833594962683414}
2023-07-02 10:34:57,427 [prior] Evaluating prior at array([0.31978975, 0.4833595 ])
2023-07-02 10:34:57,427 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:57,427 [model] Got input parameters: {'Omega_m': 0.319789746535691, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4833594962683414, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:57,427 [classy] Got parameters {'Omega_m': 0.319789746535691, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:57,427 [classy] Computing new state
2023-07-02 10:34:57,427 [classy] Setting parameters: {'Omega_m': 0.319789746535691, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:57,473 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.39007672916026}
2023-07-02 10:34:57,473 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:57,475 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00341644
2023-07-02 10:34:57,475 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4833594962683414, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:57,475 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:57,495 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.62536
2023-07-02 10:34:57,495 [model] Computed derived parameters: {}
2023-07-02 10:34:57,495 [mcmc] New sample, #928:
Omega_m:0.3125795, b1:0.4964998
2023-07-02 10:34:57,495 [model] Posterior to be computed for parameters {'Omega_m': 0.319789746535691, 'b1': 0.5118434622868515}
2023-07-02 10:34:57,495 [prior] Evaluating prior at array([0.31978975, 0.51184346])
2023-07-02 10:34:57,495 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:57,495 [model] Got input parameters: {'Omega_m': 0.319789746535691, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5118434622868515, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:57,495 [classy] Got parameters {'Omega_m': 0.319789746535691, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:57,495 [classy] Re-using computed results
2023-07-02 10:34:57,496 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.39007672916026}
2023-07-02 10:34:57,496 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:57,496 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5118434622868515, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:57,496 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:57,515 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.68377
2023-07-02 10:34:57,515 [model] Computed derived parameters: {}
2023-07-02 10:34:57,515 [model] Posterior to be computed for parameters {'Omega_m': 0.31251311961006467, 'b1': 0.4966207322793239}
2023-07-02 10:34:57,515 [prior] Evaluating prior at array([0.31251312, 0.49662073])
2023-07-02 10:34:57,515 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:57,515 [model] Got input parameters: {'Omega_m': 0.31251311961006467, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4966207322793239, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:57,515 [classy] Got parameters {'Omega_m': 0.31251311961006467, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:57,515 [classy] Computing new state
2023-07-02 10:34:57,515 [classy] Setting parameters: {'Omega_m': 0.31251311961006467, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:57,562 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.25661983431277}
2023-07-02 10:34:57,562 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:57,563 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000202426
2023-07-02 10:34:57,563 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4966207322793239, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:57,564 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:57,583 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.7047
2023-07-02 10:34:57,583 [model] Computed derived parameters: {}
2023-07-02 10:34:57,584 [mcmc] New sample, #929:
Omega_m:0.3197897, b1:0.4833595
2023-07-02 10:34:57,584 [model] Posterior to be computed for parameters {'Omega_m': 0.31251311961006467, 'b1': 0.6164771075552855}
2023-07-02 10:34:57,584 [prior] Evaluating prior at array([0.31251312, 0.61647711])
2023-07-02 10:34:57,584 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:57,584 [model] Got input parameters: {'Omega_m': 0.31251311961006467, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6164771075552855, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:57,584 [classy] Got parameters {'Omega_m': 0.31251311961006467, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:57,584 [classy] Re-using computed results
2023-07-02 10:34:57,584 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.25661983431277}
2023-07-02 10:34:57,584 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:57,584 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6164771075552855, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:57,584 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:57,604 [fs_likelihood.fslikelihood] Computed log-likelihood = -34.5128
2023-07-02 10:34:57,604 [model] Computed derived parameters: {}
2023-07-02 10:34:57,604 [model] Posterior to be computed for parameters {'Omega_m': 0.28254430332141295, 'b1': 0.551237184357411}
2023-07-02 10:34:57,604 [prior] Evaluating prior at array([0.2825443 , 0.55123718])
2023-07-02 10:34:57,604 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:57,604 [model] Got input parameters: {'Omega_m': 0.28254430332141295, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.551237184357411, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:57,604 [classy] Got parameters {'Omega_m': 0.28254430332141295, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:57,604 [classy] Computing new state
2023-07-02 10:34:57,604 [classy] Setting parameters: {'Omega_m': 0.28254430332141295, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:57,650 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.02399761996173}
2023-07-02 10:34:57,650 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:57,652 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.059553
2023-07-02 10:34:57,652 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.551237184357411, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:57,652 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:57,672 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.10833
2023-07-02 10:34:57,672 [model] Computed derived parameters: {}
2023-07-02 10:34:57,672 [model] Posterior to be computed for parameters {'Omega_m': 0.31251311961006467, 'b1': 0.47333212420387244}
2023-07-02 10:34:57,672 [prior] Evaluating prior at array([0.31251312, 0.47333212])
2023-07-02 10:34:57,672 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:57,672 [model] Got input parameters: {'Omega_m': 0.31251311961006467, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47333212420387244, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:57,672 [classy] Got parameters {'Omega_m': 0.31251311961006467, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:57,672 [classy] Re-using computed results
2023-07-02 10:34:57,672 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.25661983431277}
2023-07-02 10:34:57,672 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:57,672 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47333212420387244, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:57,672 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:57,692 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.295426
2023-07-02 10:34:57,692 [model] Computed derived parameters: {}
2023-07-02 10:34:57,692 [mcmc] New sample, #930:
Omega_m:0.3125131, b1:0.4966207
2023-07-02 10:34:57,692 [model] Posterior to be computed for parameters {'Omega_m': 0.24658207735023285, 'b1': 0.5934876744050994}
2023-07-02 10:34:57,692 [prior] Evaluating prior at array([0.24658208, 0.59348767])
2023-07-02 10:34:57,692 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:57,692 [model] Got input parameters: {'Omega_m': 0.24658207735023285, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5934876744050994, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:57,693 [classy] Got parameters {'Omega_m': 0.24658207735023285, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:57,693 [classy] Computing new state
2023-07-02 10:34:57,693 [classy] Setting parameters: {'Omega_m': 0.24658207735023285, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:57,738 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 156.02585195259576}
2023-07-02 10:34:57,738 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:57,740 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.31759
2023-07-02 10:34:57,740 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5934876744050994, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:57,740 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:57,760 [fs_likelihood.fslikelihood] Computed log-likelihood = -34.3861
2023-07-02 10:34:57,760 [model] Computed derived parameters: {}
2023-07-02 10:34:57,760 [model] Posterior to be computed for parameters {'Omega_m': 0.31251311961006467, 'b1': 0.4687440869847858}
2023-07-02 10:34:57,760 [prior] Evaluating prior at array([0.31251312, 0.46874409])
2023-07-02 10:34:57,760 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:57,760 [model] Got input parameters: {'Omega_m': 0.31251311961006467, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4687440869847858, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:57,760 [classy] Got parameters {'Omega_m': 0.31251311961006467, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:57,760 [classy] Re-using computed results
2023-07-02 10:34:57,760 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.25661983431277}
2023-07-02 10:34:57,760 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:57,760 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4687440869847858, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:57,761 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:57,779 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.497538
2023-07-02 10:34:57,780 [model] Computed derived parameters: {}
2023-07-02 10:34:57,780 [model] Posterior to be computed for parameters {'Omega_m': 0.3151508786660436, 'b1': 0.4685249593266609}
2023-07-02 10:34:57,780 [prior] Evaluating prior at array([0.31515088, 0.46852496])
2023-07-02 10:34:57,780 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:57,780 [model] Got input parameters: {'Omega_m': 0.3151508786660436, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4685249593266609, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:57,780 [classy] Got parameters {'Omega_m': 0.3151508786660436, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:57,780 [classy] Computing new state
2023-07-02 10:34:57,780 [classy] Setting parameters: {'Omega_m': 0.3151508786660436, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:57,827 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.94042574594374}
2023-07-02 10:34:57,827 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:57,829 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000635729
2023-07-02 10:34:57,829 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4685249593266609, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:57,829 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:57,848 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.326878
2023-07-02 10:34:57,849 [model] Computed derived parameters: {}
2023-07-02 10:34:57,849 [mcmc] New sample, #931:
Omega_m:0.3125131, b1:0.4733321
2023-07-02 10:34:57,849 [model] Posterior to be computed for parameters {'Omega_m': 0.3151508786660436, 'b1': 0.4288110351036298}
2023-07-02 10:34:57,849 [prior] Evaluating prior at array([0.31515088, 0.42881104])
2023-07-02 10:34:57,849 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:57,849 [model] Got input parameters: {'Omega_m': 0.3151508786660436, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4288110351036298, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:57,849 [classy] Got parameters {'Omega_m': 0.3151508786660436, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:57,849 [classy] Re-using computed results
2023-07-02 10:34:57,849 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.94042574594374}
2023-07-02 10:34:57,849 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:57,849 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4288110351036298, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:57,849 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:57,868 [fs_likelihood.fslikelihood] Computed log-likelihood = -9.8119
2023-07-02 10:34:57,868 [model] Computed derived parameters: {}
2023-07-02 10:34:57,869 [model] Posterior to be computed for parameters {'Omega_m': 0.29069197469304864, 'b1': 0.5130999116323167}
2023-07-02 10:34:57,869 [prior] Evaluating prior at array([0.29069197, 0.51309991])
2023-07-02 10:34:57,869 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:57,869 [model] Got input parameters: {'Omega_m': 0.29069197469304864, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5130999116323167, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:57,869 [classy] Got parameters {'Omega_m': 0.29069197469304864, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:57,869 [classy] Computing new state
2023-07-02 10:34:57,869 [classy] Setting parameters: {'Omega_m': 0.29069197469304864, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:57,915 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.96652688626705}
2023-07-02 10:34:57,915 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:57,917 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0309818
2023-07-02 10:34:57,917 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5130999116323167, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:57,917 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:57,937 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.31883
2023-07-02 10:34:57,937 [model] Computed derived parameters: {}
2023-07-02 10:34:57,937 [model] Posterior to be computed for parameters {'Omega_m': 0.3151508786660436, 'b1': 0.5026235491902697}
2023-07-02 10:34:57,937 [prior] Evaluating prior at array([0.31515088, 0.50262355])
2023-07-02 10:34:57,938 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:57,938 [model] Got input parameters: {'Omega_m': 0.3151508786660436, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5026235491902697, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:57,938 [classy] Got parameters {'Omega_m': 0.3151508786660436, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:57,938 [classy] Re-using computed results
2023-07-02 10:34:57,938 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.94042574594374}
2023-07-02 10:34:57,938 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:57,938 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5026235491902697, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:57,938 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:57,957 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.90916
2023-07-02 10:34:57,957 [model] Computed derived parameters: {}
2023-07-02 10:34:57,957 [mcmc] New sample, #932:
Omega_m:0.3151509, b1:0.468525
2023-07-02 10:34:57,957 [model] Posterior to be computed for parameters {'Omega_m': 0.3140144815837084, 'b1': 0.5046945678181406}
2023-07-02 10:34:57,957 [prior] Evaluating prior at array([0.31401448, 0.50469457])
2023-07-02 10:34:57,958 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:57,958 [model] Got input parameters: {'Omega_m': 0.3140144815837084, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5046945678181406, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:57,958 [classy] Got parameters {'Omega_m': 0.3140144815837084, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:57,958 [classy] Computing new state
2023-07-02 10:34:57,958 [classy] Setting parameters: {'Omega_m': 0.3140144815837084, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:58,004 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.0763556215367}
2023-07-02 10:34:58,004 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:58,005 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000345525
2023-07-02 10:34:58,006 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5046945678181406, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:58,006 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:58,026 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.90125
2023-07-02 10:34:58,026 [model] Computed derived parameters: {}
2023-07-02 10:34:58,026 [mcmc] New sample, #933:
Omega_m:0.3151509, b1:0.5026235
2023-07-02 10:34:58,026 [model] Posterior to be computed for parameters {'Omega_m': 0.3140144815837084, 'b1': 0.5115241929976359}
2023-07-02 10:34:58,026 [prior] Evaluating prior at array([0.31401448, 0.51152419])
2023-07-02 10:34:58,026 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:58,026 [model] Got input parameters: {'Omega_m': 0.3140144815837084, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5115241929976359, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:58,026 [classy] Got parameters {'Omega_m': 0.3140144815837084, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:58,026 [classy] Re-using computed results
2023-07-02 10:34:58,026 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.0763556215367}
2023-07-02 10:34:58,026 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:58,026 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5115241929976359, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:58,026 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:58,046 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.67934
2023-07-02 10:34:58,046 [model] Computed derived parameters: {}
2023-07-02 10:34:58,046 [mcmc] New sample, #934:
Omega_m:0.3140145, b1:0.5046946
2023-07-02 10:34:58,046 [model] Posterior to be computed for parameters {'Omega_m': 0.26682044852420705, 'b1': 0.5975326165582943}
2023-07-02 10:34:58,046 [prior] Evaluating prior at array([0.26682045, 0.59753262])
2023-07-02 10:34:58,046 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:58,046 [model] Got input parameters: {'Omega_m': 0.26682044852420705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5975326165582943, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:58,046 [classy] Got parameters {'Omega_m': 0.26682044852420705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:58,046 [classy] Computing new state
2023-07-02 10:34:58,046 [classy] Setting parameters: {'Omega_m': 0.26682044852420705, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:58,093 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.1408912535893}
2023-07-02 10:34:58,093 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:58,095 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.144217
2023-07-02 10:34:58,095 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5975326165582943, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:58,095 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:58,114 [fs_likelihood.fslikelihood] Computed log-likelihood = -13.4391
2023-07-02 10:34:58,114 [model] Computed derived parameters: {}
2023-07-02 10:34:58,114 [model] Posterior to be computed for parameters {'Omega_m': 0.3140144815837084, 'b1': 0.48782023886073606}
2023-07-02 10:34:58,114 [prior] Evaluating prior at array([0.31401448, 0.48782024])
2023-07-02 10:34:58,114 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:58,114 [model] Got input parameters: {'Omega_m': 0.3140144815837084, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48782023886073606, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:58,114 [classy] Got parameters {'Omega_m': 0.3140144815837084, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:58,114 [classy] Re-using computed results
2023-07-02 10:34:58,115 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.0763556215367}
2023-07-02 10:34:58,115 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:58,115 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48782023886073606, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:58,115 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:58,137 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.37468
2023-07-02 10:34:58,137 [model] Computed derived parameters: {}
2023-07-02 10:34:58,137 [mcmc] New sample, #935:
Omega_m:0.3140145, b1:0.5115242
2023-07-02 10:34:58,138 [model] Posterior to be computed for parameters {'Omega_m': 0.3517070067979696, 'b1': 0.4191277694205491}
2023-07-02 10:34:58,138 [prior] Evaluating prior at array([0.35170701, 0.41912777])
2023-07-02 10:34:58,138 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:58,138 [model] Got input parameters: {'Omega_m': 0.3517070067979696, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4191277694205491, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:58,138 [classy] Got parameters {'Omega_m': 0.3517070067979696, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:58,138 [classy] Computing new state
2023-07-02 10:34:58,138 [classy] Setting parameters: {'Omega_m': 0.3517070067979696, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:58,184 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.78723074502435}
2023-07-02 10:34:58,184 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:58,186 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0860681
2023-07-02 10:34:58,186 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4191277694205491, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:58,186 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:58,206 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.10164
2023-07-02 10:34:58,206 [model] Computed derived parameters: {}
2023-07-02 10:34:58,206 [model] Posterior to be computed for parameters {'Omega_m': 0.3140144815837084, 'b1': 0.5183199381294669}
2023-07-02 10:34:58,206 [prior] Evaluating prior at array([0.31401448, 0.51831994])
2023-07-02 10:34:58,206 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:58,206 [model] Got input parameters: {'Omega_m': 0.3140144815837084, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5183199381294669, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:58,206 [classy] Got parameters {'Omega_m': 0.3140144815837084, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:58,206 [classy] Re-using computed results
2023-07-02 10:34:58,206 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.0763556215367}
2023-07-02 10:34:58,206 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:58,206 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5183199381294669, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:58,206 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:58,226 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.20204
2023-07-02 10:34:58,226 [model] Computed derived parameters: {}
2023-07-02 10:34:58,226 [mcmc] New sample, #936:
Omega_m:0.3140145, b1:0.4878202
2023-07-02 10:34:58,226 [model] Posterior to be computed for parameters {'Omega_m': 0.2892358367216956, 'b1': 0.5634775999013308}
2023-07-02 10:34:58,226 [prior] Evaluating prior at array([0.28923584, 0.5634776 ])
2023-07-02 10:34:58,227 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:58,227 [model] Got input parameters: {'Omega_m': 0.2892358367216956, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5634775999013308, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:58,227 [classy] Got parameters {'Omega_m': 0.2892358367216956, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:58,227 [classy] Computing new state
2023-07-02 10:34:58,227 [classy] Setting parameters: {'Omega_m': 0.2892358367216956, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:58,273 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.15361071583703}
2023-07-02 10:34:58,273 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:58,275 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.035365
2023-07-02 10:34:58,275 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5634775999013308, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:58,275 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:58,295 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.01219
2023-07-02 10:34:58,295 [model] Computed derived parameters: {}
2023-07-02 10:34:58,295 [model] Posterior to be computed for parameters {'Omega_m': 0.3140144815837084, 'b1': 0.5664622128634488}
2023-07-02 10:34:58,295 [prior] Evaluating prior at array([0.31401448, 0.56646221])
2023-07-02 10:34:58,295 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:58,295 [model] Got input parameters: {'Omega_m': 0.3140144815837084, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5664622128634488, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:58,295 [classy] Got parameters {'Omega_m': 0.3140144815837084, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:58,295 [classy] Re-using computed results
2023-07-02 10:34:58,295 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.0763556215367}
2023-07-02 10:34:58,295 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:58,296 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5664622128634488, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:58,296 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:58,315 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.96109
2023-07-02 10:34:58,315 [model] Computed derived parameters: {}
2023-07-02 10:34:58,315 [model] Posterior to be computed for parameters {'Omega_m': 0.30684652847888955, 'b1': 0.531383122323217}
2023-07-02 10:34:58,315 [prior] Evaluating prior at array([0.30684653, 0.53138312])
2023-07-02 10:34:58,315 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:58,315 [model] Got input parameters: {'Omega_m': 0.30684652847888955, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.531383122323217, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:58,315 [classy] Got parameters {'Omega_m': 0.30684652847888955, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:58,315 [classy] Computing new state
2023-07-02 10:34:58,315 [classy] Setting parameters: {'Omega_m': 0.30684652847888955, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:58,362 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.94395169602592}
2023-07-02 10:34:58,362 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:58,364 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00217899
2023-07-02 10:34:58,364 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.531383122323217, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:58,364 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:58,383 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.80536
2023-07-02 10:34:58,383 [model] Computed derived parameters: {}
2023-07-02 10:34:58,383 [mcmc] New sample, #937:
Omega_m:0.3140145, b1:0.5183199
2023-07-02 10:34:58,383 [model] Posterior to be computed for parameters {'Omega_m': 0.30684652847888955, 'b1': 0.6498374805237729}
2023-07-02 10:34:58,383 [prior] Evaluating prior at array([0.30684653, 0.64983748])
2023-07-02 10:34:58,383 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:58,383 [model] Got input parameters: {'Omega_m': 0.30684652847888955, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6498374805237729, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:58,383 [classy] Got parameters {'Omega_m': 0.30684652847888955, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:58,383 [classy] Re-using computed results
2023-07-02 10:34:58,383 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.94395169602592}
2023-07-02 10:34:58,383 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:58,383 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6498374805237729, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:58,383 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:58,403 [fs_likelihood.fslikelihood] Computed log-likelihood = -52.8192
2023-07-02 10:34:58,403 [model] Computed derived parameters: {}
2023-07-02 10:34:58,403 [model] Posterior to be computed for parameters {'Omega_m': 0.32372898396592137, 'b1': 0.5006158136585412}
2023-07-02 10:34:58,403 [prior] Evaluating prior at array([0.32372898, 0.50061581])
2023-07-02 10:34:58,403 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:58,403 [model] Got input parameters: {'Omega_m': 0.32372898396592137, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5006158136585412, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:58,403 [classy] Got parameters {'Omega_m': 0.32372898396592137, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:58,403 [classy] Computing new state
2023-07-02 10:34:58,403 [classy] Setting parameters: {'Omega_m': 0.32372898396592137, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:58,450 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.9282812801224}
2023-07-02 10:34:58,450 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:58,452 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00774416
2023-07-02 10:34:58,452 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5006158136585412, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:58,452 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:58,471 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.815
2023-07-02 10:34:58,471 [model] Computed derived parameters: {}
2023-07-02 10:34:58,471 [mcmc] New sample, #938:
Omega_m:0.3068465, b1:0.5313831
2023-07-02 10:34:58,472 [model] Posterior to be computed for parameters {'Omega_m': 0.32372898396592137, 'b1': 0.4807382068057356}
2023-07-02 10:34:58,472 [prior] Evaluating prior at array([0.32372898, 0.48073821])
2023-07-02 10:34:58,472 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:58,472 [model] Got input parameters: {'Omega_m': 0.32372898396592137, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4807382068057356, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:58,472 [classy] Got parameters {'Omega_m': 0.32372898396592137, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:58,472 [classy] Re-using computed results
2023-07-02 10:34:58,472 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.9282812801224}
2023-07-02 10:34:58,472 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:58,472 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4807382068057356, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:58,472 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:58,491 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.49294
2023-07-02 10:34:58,491 [model] Computed derived parameters: {}
2023-07-02 10:34:58,491 [mcmc] New sample, #939:
Omega_m:0.323729, b1:0.5006158
2023-07-02 10:34:58,491 [model] Posterior to be computed for parameters {'Omega_m': 0.3179440081624644, 'b1': 0.49128099403827785}
2023-07-02 10:34:58,491 [prior] Evaluating prior at array([0.31794401, 0.49128099])
2023-07-02 10:34:58,491 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:58,492 [model] Got input parameters: {'Omega_m': 0.3179440081624644, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49128099403827785, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:58,492 [classy] Got parameters {'Omega_m': 0.3179440081624644, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:58,492 [classy] Computing new state
2023-07-02 10:34:58,492 [classy] Setting parameters: {'Omega_m': 0.3179440081624644, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:58,538 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.60819436576048}
2023-07-02 10:34:58,538 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:58,540 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00200583
2023-07-02 10:34:58,540 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49128099403827785, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:58,540 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:58,559 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.8473
2023-07-02 10:34:58,559 [model] Computed derived parameters: {}
2023-07-02 10:34:58,559 [mcmc] New sample, #940:
Omega_m:0.323729, b1:0.4807382
2023-07-02 10:34:58,559 [model] Posterior to be computed for parameters {'Omega_m': 0.3179440081624644, 'b1': 0.4948832141926568}
2023-07-02 10:34:58,559 [prior] Evaluating prior at array([0.31794401, 0.49488321])
2023-07-02 10:34:58,560 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:58,560 [model] Got input parameters: {'Omega_m': 0.3179440081624644, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4948832141926568, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:58,560 [classy] Got parameters {'Omega_m': 0.3179440081624644, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:58,560 [classy] Re-using computed results
2023-07-02 10:34:58,560 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.60819436576048}
2023-07-02 10:34:58,560 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:58,560 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4948832141926568, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:58,560 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:58,579 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.8846
2023-07-02 10:34:58,579 [model] Computed derived parameters: {}
2023-07-02 10:34:58,579 [mcmc] New sample, #941:
Omega_m:0.317944, b1:0.491281
2023-07-02 10:34:58,579 [model] Posterior to be computed for parameters {'Omega_m': 0.3681249788020542, 'b1': 0.403431267883824}
2023-07-02 10:34:58,579 [prior] Evaluating prior at array([0.36812498, 0.40343127])
2023-07-02 10:34:58,579 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:58,579 [model] Got input parameters: {'Omega_m': 0.3681249788020542, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.403431267883824, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:58,580 [classy] Got parameters {'Omega_m': 0.3681249788020542, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:58,580 [classy] Computing new state
2023-07-02 10:34:58,580 [classy] Setting parameters: {'Omega_m': 0.3681249788020542, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:58,626 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.04899917801617}
2023-07-02 10:34:58,626 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:58,628 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.166646
2023-07-02 10:34:58,628 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.403431267883824, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:58,628 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:58,647 [fs_likelihood.fslikelihood] Computed log-likelihood = -9.65207
2023-07-02 10:34:58,647 [model] Computed derived parameters: {}
2023-07-02 10:34:58,647 [model] Posterior to be computed for parameters {'Omega_m': 0.3179440081624644, 'b1': 0.5088235760025143}
2023-07-02 10:34:58,648 [prior] Evaluating prior at array([0.31794401, 0.50882358])
2023-07-02 10:34:58,648 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:58,648 [model] Got input parameters: {'Omega_m': 0.3179440081624644, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5088235760025143, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:58,648 [classy] Got parameters {'Omega_m': 0.3179440081624644, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:58,648 [classy] Re-using computed results
2023-07-02 10:34:58,648 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.60819436576048}
2023-07-02 10:34:58,648 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:58,648 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5088235760025143, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:58,648 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:58,667 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.36111
2023-07-02 10:34:58,667 [model] Computed derived parameters: {}
2023-07-02 10:34:58,667 [model] Posterior to be computed for parameters {'Omega_m': 0.32265933531056656, 'b1': 0.48628980040092334}
2023-07-02 10:34:58,668 [prior] Evaluating prior at array([0.32265934, 0.4862898 ])
2023-07-02 10:34:58,668 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:58,668 [model] Got input parameters: {'Omega_m': 0.32265933531056656, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48628980040092334, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:58,668 [classy] Got parameters {'Omega_m': 0.32265933531056656, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:58,668 [classy] Computing new state
2023-07-02 10:34:58,668 [classy] Setting parameters: {'Omega_m': 0.32265933531056656, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:58,714 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.05317654327308}
2023-07-02 10:34:58,714 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:58,716 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00639369
2023-07-02 10:34:58,716 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48628980040092334, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:58,716 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:58,735 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.62287
2023-07-02 10:34:58,735 [model] Computed derived parameters: {}
2023-07-02 10:34:58,735 [model] Posterior to be computed for parameters {'Omega_m': 0.3179440081624644, 'b1': 0.5657738994267227}
2023-07-02 10:34:58,736 [prior] Evaluating prior at array([0.31794401, 0.5657739 ])
2023-07-02 10:34:58,736 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:58,736 [model] Got input parameters: {'Omega_m': 0.3179440081624644, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5657738994267227, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:58,736 [classy] Got parameters {'Omega_m': 0.3179440081624644, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:58,736 [classy] Re-using computed results
2023-07-02 10:34:58,736 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.60819436576048}
2023-07-02 10:34:58,736 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:58,736 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5657738994267227, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:58,736 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:58,756 [fs_likelihood.fslikelihood] Computed log-likelihood = -11.6429
2023-07-02 10:34:58,756 [model] Computed derived parameters: {}
2023-07-02 10:34:58,756 [model] Posterior to be computed for parameters {'Omega_m': 0.32174623527477, 'b1': 0.48795387294443815}
2023-07-02 10:34:58,756 [prior] Evaluating prior at array([0.32174624, 0.48795387])
2023-07-02 10:34:58,756 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:58,756 [model] Got input parameters: {'Omega_m': 0.32174623527477, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48795387294443815, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:58,756 [classy] Got parameters {'Omega_m': 0.32174623527477, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:58,756 [classy] Computing new state
2023-07-02 10:34:58,756 [classy] Setting parameters: {'Omega_m': 0.32174623527477, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:58,802 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.1600867707077}
2023-07-02 10:34:58,802 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:58,804 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00534378
2023-07-02 10:34:58,804 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48795387294443815, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:58,804 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:58,824 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.69172
2023-07-02 10:34:58,824 [model] Computed derived parameters: {}
2023-07-02 10:34:58,824 [mcmc] New sample, #942:
Omega_m:0.317944, b1:0.4948832
2023-07-02 10:34:58,824 [model] Posterior to be computed for parameters {'Omega_m': 0.32174623527477, 'b1': 0.44707805225816194}
2023-07-02 10:34:58,824 [prior] Evaluating prior at array([0.32174624, 0.44707805])
2023-07-02 10:34:58,824 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:58,824 [model] Got input parameters: {'Omega_m': 0.32174623527477, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44707805225816194, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:58,824 [classy] Got parameters {'Omega_m': 0.32174623527477, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:58,824 [classy] Re-using computed results
2023-07-02 10:34:58,824 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.1600867707077}
2023-07-02 10:34:58,824 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:58,824 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44707805225816194, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:58,824 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:58,844 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.68886
2023-07-02 10:34:58,844 [model] Computed derived parameters: {}
2023-07-02 10:34:58,844 [model] Posterior to be computed for parameters {'Omega_m': 0.2925722466695439, 'b1': 0.5411217970705355}
2023-07-02 10:34:58,844 [prior] Evaluating prior at array([0.29257225, 0.5411218 ])
2023-07-02 10:34:58,844 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:58,844 [model] Got input parameters: {'Omega_m': 0.2925722466695439, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5411217970705355, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:58,844 [classy] Got parameters {'Omega_m': 0.2925722466695439, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:58,844 [classy] Computing new state
2023-07-02 10:34:58,844 [classy] Setting parameters: {'Omega_m': 0.2925722466695439, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:58,890 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.72613986876638}
2023-07-02 10:34:58,890 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:58,892 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0257746
2023-07-02 10:34:58,892 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5411217970705355, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:58,892 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:58,912 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.236634
2023-07-02 10:34:58,912 [model] Computed derived parameters: {}
2023-07-02 10:34:58,912 [model] Posterior to be computed for parameters {'Omega_m': 0.32174623527477, 'b1': 0.5087246277457994}
2023-07-02 10:34:58,912 [prior] Evaluating prior at array([0.32174624, 0.50872463])
2023-07-02 10:34:58,912 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:58,912 [model] Got input parameters: {'Omega_m': 0.32174623527477, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5087246277457994, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:58,913 [classy] Got parameters {'Omega_m': 0.32174623527477, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:58,913 [classy] Re-using computed results
2023-07-02 10:34:58,913 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.1600867707077}
2023-07-02 10:34:58,913 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:58,913 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5087246277457994, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:58,913 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:58,932 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.51426
2023-07-02 10:34:58,932 [model] Computed derived parameters: {}
2023-07-02 10:34:58,932 [model] Posterior to be computed for parameters {'Omega_m': 0.32037899903014627, 'b1': 0.4904455827308601}
2023-07-02 10:34:58,932 [prior] Evaluating prior at array([0.320379 , 0.49044558])
2023-07-02 10:34:58,932 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:58,932 [model] Got input parameters: {'Omega_m': 0.32037899903014627, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4904455827308601, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:58,932 [classy] Got parameters {'Omega_m': 0.32037899903014627, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:58,932 [classy] Computing new state
2023-07-02 10:34:58,932 [classy] Setting parameters: {'Omega_m': 0.32037899903014627, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:58,978 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.32067560312797}
2023-07-02 10:34:58,978 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:58,980 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00395044
2023-07-02 10:34:58,980 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4904455827308601, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:58,980 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:58,999 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.77867
2023-07-02 10:34:59,000 [model] Computed derived parameters: {}
2023-07-02 10:34:59,000 [mcmc] New sample, #943:
Omega_m:0.3217462, b1:0.4879539
2023-07-02 10:34:59,000 [model] Posterior to be computed for parameters {'Omega_m': 0.32037899903014627, 'b1': 0.5214293341228836}
2023-07-02 10:34:59,000 [prior] Evaluating prior at array([0.320379 , 0.52142933])
2023-07-02 10:34:59,000 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:59,000 [model] Got input parameters: {'Omega_m': 0.32037899903014627, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5214293341228836, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:59,000 [classy] Got parameters {'Omega_m': 0.32037899903014627, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:59,000 [classy] Re-using computed results
2023-07-02 10:34:59,000 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.32067560312797}
2023-07-02 10:34:59,000 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:59,000 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5214293341228836, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:59,000 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:59,020 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.120101
2023-07-02 10:34:59,020 [model] Computed derived parameters: {}
2023-07-02 10:34:59,020 [model] Posterior to be computed for parameters {'Omega_m': 0.2947676002700546, 'b1': 0.5371208908097784}
2023-07-02 10:34:59,020 [prior] Evaluating prior at array([0.2947676 , 0.53712089])
2023-07-02 10:34:59,020 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:59,020 [model] Got input parameters: {'Omega_m': 0.2947676002700546, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5371208908097784, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:59,020 [classy] Got parameters {'Omega_m': 0.2947676002700546, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:59,020 [classy] Computing new state
2023-07-02 10:34:59,020 [classy] Setting parameters: {'Omega_m': 0.2947676002700546, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:59,066 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.447163414346}
2023-07-02 10:34:59,066 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:59,068 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0203323
2023-07-02 10:34:59,068 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5371208908097784, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:59,068 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:59,087 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.371203
2023-07-02 10:34:59,088 [model] Computed derived parameters: {}
2023-07-02 10:34:59,088 [model] Posterior to be computed for parameters {'Omega_m': 0.32037899903014627, 'b1': 0.45439008736062547}
2023-07-02 10:34:59,088 [prior] Evaluating prior at array([0.320379 , 0.45439009])
2023-07-02 10:34:59,088 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:59,088 [model] Got input parameters: {'Omega_m': 0.32037899903014627, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45439008736062547, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:59,088 [classy] Got parameters {'Omega_m': 0.32037899903014627, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:59,088 [classy] Re-using computed results
2023-07-02 10:34:59,088 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.32067560312797}
2023-07-02 10:34:59,088 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:59,088 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45439008736062547, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:59,088 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:59,108 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.643495
2023-07-02 10:34:59,108 [model] Computed derived parameters: {}
2023-07-02 10:34:59,108 [model] Posterior to be computed for parameters {'Omega_m': 0.2964650666802012, 'b1': 0.5340273554511918}
2023-07-02 10:34:59,108 [prior] Evaluating prior at array([0.29646507, 0.53402736])
2023-07-02 10:34:59,108 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:59,108 [model] Got input parameters: {'Omega_m': 0.2964650666802012, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5340273554511918, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:59,108 [classy] Got parameters {'Omega_m': 0.2964650666802012, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:59,108 [classy] Computing new state
2023-07-02 10:34:59,108 [classy] Setting parameters: {'Omega_m': 0.2964650666802012, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:59,156 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.23268840315893}
2023-07-02 10:34:59,156 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:59,158 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0165878
2023-07-02 10:34:59,158 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5340273554511918, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:59,158 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:59,177 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.793555
2023-07-02 10:34:59,177 [model] Computed derived parameters: {}
2023-07-02 10:34:59,178 [model] Posterior to be computed for parameters {'Omega_m': 0.32037899903014627, 'b1': 0.4905019962733187}
2023-07-02 10:34:59,178 [prior] Evaluating prior at array([0.320379, 0.490502])
2023-07-02 10:34:59,178 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:59,178 [model] Got input parameters: {'Omega_m': 0.32037899903014627, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4905019962733187, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:59,178 [classy] Got parameters {'Omega_m': 0.32037899903014627, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:59,178 [classy] Re-using computed results
2023-07-02 10:34:59,178 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.32067560312797}
2023-07-02 10:34:59,178 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:59,178 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4905019962733187, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:59,178 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:59,197 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.77871
2023-07-02 10:34:59,197 [model] Computed derived parameters: {}
2023-07-02 10:34:59,197 [mcmc] New sample, #944:
Omega_m:0.320379, b1:0.4904456
2023-07-02 10:34:59,198 [model] Posterior to be computed for parameters {'Omega_m': 0.33257414615640135, 'b1': 0.4682770387644515}
2023-07-02 10:34:59,198 [prior] Evaluating prior at array([0.33257415, 0.46827704])
2023-07-02 10:34:59,198 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:59,198 [model] Got input parameters: {'Omega_m': 0.33257414615640135, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4682770387644515, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:59,198 [classy] Got parameters {'Omega_m': 0.33257414615640135, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:59,198 [classy] Computing new state
2023-07-02 10:34:59,198 [classy] Setting parameters: {'Omega_m': 0.33257414615640135, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:59,244 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.90947196724966}
2023-07-02 10:34:59,244 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:59,246 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0237673
2023-07-02 10:34:59,246 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4682770387644515, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:59,246 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:59,266 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.34827
2023-07-02 10:34:59,266 [model] Computed derived parameters: {}
2023-07-02 10:34:59,266 [model] Posterior to be computed for parameters {'Omega_m': 0.32037899903014627, 'b1': 0.550886413726468}
2023-07-02 10:34:59,266 [prior] Evaluating prior at array([0.320379 , 0.55088641])
2023-07-02 10:34:59,267 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:59,267 [model] Got input parameters: {'Omega_m': 0.32037899903014627, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.550886413726468, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:59,267 [classy] Got parameters {'Omega_m': 0.32037899903014627, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:59,267 [classy] Re-using computed results
2023-07-02 10:34:59,267 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.32067560312797}
2023-07-02 10:34:59,267 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:59,267 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.550886413726468, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:59,267 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:59,286 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.68463
2023-07-02 10:34:59,286 [model] Computed derived parameters: {}
2023-07-02 10:34:59,286 [model] Posterior to be computed for parameters {'Omega_m': 0.35068514710965604, 'b1': 0.43527077631743627}
2023-07-02 10:34:59,286 [prior] Evaluating prior at array([0.35068515, 0.43527078])
2023-07-02 10:34:59,287 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:59,287 [model] Got input parameters: {'Omega_m': 0.35068514710965604, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.43527077631743627, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:59,287 [classy] Got parameters {'Omega_m': 0.35068514710965604, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:59,287 [classy] Computing new state
2023-07-02 10:34:59,287 [classy] Setting parameters: {'Omega_m': 0.35068514710965604, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:59,333 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.89787727301976}
2023-07-02 10:34:59,333 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:59,335 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0818454
2023-07-02 10:34:59,335 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.43527077631743627, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:59,335 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:59,354 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.16649
2023-07-02 10:34:59,354 [model] Computed derived parameters: {}
2023-07-02 10:34:59,355 [model] Posterior to be computed for parameters {'Omega_m': 0.32037899903014627, 'b1': 0.48286486428411823}
2023-07-02 10:34:59,355 [prior] Evaluating prior at array([0.320379 , 0.48286486])
2023-07-02 10:34:59,355 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:59,355 [model] Got input parameters: {'Omega_m': 0.32037899903014627, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48286486428411823, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:59,355 [classy] Got parameters {'Omega_m': 0.32037899903014627, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:59,355 [classy] Re-using computed results
2023-07-02 10:34:59,355 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.32067560312797}
2023-07-02 10:34:59,355 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:59,355 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48286486428411823, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:59,355 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:59,375 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.61846
2023-07-02 10:34:59,375 [model] Computed derived parameters: {}
2023-07-02 10:34:59,375 [mcmc] New sample, #945:
Omega_m:0.320379, b1:0.490502
2023-07-02 10:34:59,375 [model] Posterior to be computed for parameters {'Omega_m': 0.3234756058436151, 'b1': 0.4772214756362809}
2023-07-02 10:34:59,375 [prior] Evaluating prior at array([0.32347561, 0.47722148])
2023-07-02 10:34:59,375 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:59,375 [model] Got input parameters: {'Omega_m': 0.3234756058436151, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4772214756362809, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:59,375 [classy] Got parameters {'Omega_m': 0.3234756058436151, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:59,375 [classy] Computing new state
2023-07-02 10:34:59,375 [classy] Setting parameters: {'Omega_m': 0.3234756058436151, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:59,421 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.95783234985123}
2023-07-02 10:34:59,421 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:59,424 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00741257
2023-07-02 10:34:59,424 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4772214756362809, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:59,424 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:59,443 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.39233
2023-07-02 10:34:59,443 [model] Computed derived parameters: {}
2023-07-02 10:34:59,443 [mcmc] New sample, #946:
Omega_m:0.320379, b1:0.4828649
2023-07-02 10:34:59,443 [model] Posterior to be computed for parameters {'Omega_m': 0.3234756058436151, 'b1': 0.5048033044830001}
2023-07-02 10:34:59,443 [prior] Evaluating prior at array([0.32347561, 0.5048033 ])
2023-07-02 10:34:59,444 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:59,444 [model] Got input parameters: {'Omega_m': 0.3234756058436151, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5048033044830001, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:59,444 [classy] Got parameters {'Omega_m': 0.3234756058436151, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:59,444 [classy] Re-using computed results
2023-07-02 10:34:59,444 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.95783234985123}
2023-07-02 10:34:59,444 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:59,444 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5048033044830001, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:59,444 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:59,463 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.4638
2023-07-02 10:34:59,463 [model] Computed derived parameters: {}
2023-07-02 10:34:59,463 [model] Posterior to be computed for parameters {'Omega_m': 0.3004175666242476, 'b1': 0.5192434321229679}
2023-07-02 10:34:59,463 [prior] Evaluating prior at array([0.30041757, 0.51924343])
2023-07-02 10:34:59,464 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:59,464 [model] Got input parameters: {'Omega_m': 0.3004175666242476, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5192434321229679, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:59,464 [classy] Got parameters {'Omega_m': 0.3004175666242476, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:59,464 [classy] Computing new state
2023-07-02 10:34:59,464 [classy] Setting parameters: {'Omega_m': 0.3004175666242476, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:59,510 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.73740313994543}
2023-07-02 10:34:59,510 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:59,512 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0094054
2023-07-02 10:34:59,512 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5192434321229679, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:59,512 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:59,531 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.46916
2023-07-02 10:34:59,531 [model] Computed derived parameters: {}
2023-07-02 10:34:59,531 [model] Posterior to be computed for parameters {'Omega_m': 0.3234756058436151, 'b1': 0.5187277456752967}
2023-07-02 10:34:59,531 [prior] Evaluating prior at array([0.32347561, 0.51872775])
2023-07-02 10:34:59,531 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:59,531 [model] Got input parameters: {'Omega_m': 0.3234756058436151, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5187277456752967, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:59,531 [classy] Got parameters {'Omega_m': 0.3234756058436151, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:59,531 [classy] Re-using computed results
2023-07-02 10:34:59,532 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.95783234985123}
2023-07-02 10:34:59,532 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:59,532 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5187277456752967, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:59,532 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:59,551 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.648973
2023-07-02 10:34:59,551 [model] Computed derived parameters: {}
2023-07-02 10:34:59,551 [model] Posterior to be computed for parameters {'Omega_m': 0.3045694710611836, 'b1': 0.5116768239683916}
2023-07-02 10:34:59,551 [prior] Evaluating prior at array([0.30456947, 0.51167682])
2023-07-02 10:34:59,551 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:59,551 [model] Got input parameters: {'Omega_m': 0.3045694710611836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5116768239683916, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:59,551 [classy] Got parameters {'Omega_m': 0.3045694710611836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:59,551 [classy] Computing new state
2023-07-02 10:34:59,551 [classy] Setting parameters: {'Omega_m': 0.3045694710611836, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:59,598 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2233019978958}
2023-07-02 10:34:59,598 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:59,600 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00412055
2023-07-02 10:34:59,600 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5116768239683916, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:59,600 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:59,620 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.10986
2023-07-02 10:34:59,620 [model] Computed derived parameters: {}
2023-07-02 10:34:59,620 [mcmc] New sample, #947:
Omega_m:0.3234756, b1:0.4772215
2023-07-02 10:34:59,620 [model] Posterior to be computed for parameters {'Omega_m': 0.3045694710611836, 'b1': 0.5028672693299461}
2023-07-02 10:34:59,620 [prior] Evaluating prior at array([0.30456947, 0.50286727])
2023-07-02 10:34:59,620 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:59,620 [model] Got input parameters: {'Omega_m': 0.3045694710611836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5028672693299461, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:59,620 [classy] Got parameters {'Omega_m': 0.3045694710611836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:59,620 [classy] Re-using computed results
2023-07-02 10:34:59,620 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2233019978958}
2023-07-02 10:34:59,620 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:59,620 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5028672693299461, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:59,620 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:59,641 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.55545
2023-07-02 10:34:59,641 [model] Computed derived parameters: {}
2023-07-02 10:34:59,641 [mcmc] New sample, #948:
Omega_m:0.3045695, b1:0.5116768
2023-07-02 10:34:59,642 [model] Posterior to be computed for parameters {'Omega_m': 0.18885511485918938, 'b1': 0.7137500592733739}
2023-07-02 10:34:59,642 [prior] Evaluating prior at array([0.18885511, 0.71375006])
2023-07-02 10:34:59,642 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:59,642 [model] Got input parameters: {'Omega_m': 0.18885511485918938, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.7137500592733739, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:59,642 [classy] Got parameters {'Omega_m': 0.18885511485918938, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:59,642 [classy] Computing new state
2023-07-02 10:34:59,642 [classy] Setting parameters: {'Omega_m': 0.18885511485918938, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:59,688 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 165.45557729054994}
2023-07-02 10:34:59,688 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:59,691 [bao_likelihood.baolikelihood] Computed log-likelihood = -1.33302
2023-07-02 10:34:59,691 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.7137500592733739, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:59,691 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:59,711 [fs_likelihood.fslikelihood] Computed log-likelihood = -147.682
2023-07-02 10:34:59,711 [model] Computed derived parameters: {}
2023-07-02 10:34:59,711 [model] Posterior to be computed for parameters {'Omega_m': 0.3045694710611836, 'b1': 0.5194528022366278}
2023-07-02 10:34:59,711 [prior] Evaluating prior at array([0.30456947, 0.5194528 ])
2023-07-02 10:34:59,711 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:59,711 [model] Got input parameters: {'Omega_m': 0.3045694710611836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5194528022366278, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:59,711 [classy] Got parameters {'Omega_m': 0.3045694710611836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:59,711 [classy] Re-using computed results
2023-07-02 10:34:59,712 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2233019978958}
2023-07-02 10:34:59,712 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:59,712 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5194528022366278, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:59,712 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:59,732 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.26327
2023-07-02 10:34:59,732 [model] Computed derived parameters: {}
2023-07-02 10:34:59,732 [mcmc] New sample, #949:
Omega_m:0.3045695, b1:0.5028673
2023-07-02 10:34:59,732 [model] Posterior to be computed for parameters {'Omega_m': 0.3032972267396811, 'b1': 0.5217713946811106}
2023-07-02 10:34:59,732 [prior] Evaluating prior at array([0.30329723, 0.52177139])
2023-07-02 10:34:59,733 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:59,733 [model] Got input parameters: {'Omega_m': 0.3032972267396811, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5217713946811106, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:59,733 [classy] Got parameters {'Omega_m': 0.3032972267396811, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:59,733 [classy] Computing new state
2023-07-02 10:34:59,733 [classy] Setting parameters: {'Omega_m': 0.3032972267396811, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:59,779 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.38017906821975}
2023-07-02 10:34:59,779 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:59,781 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00549835
2023-07-02 10:34:59,781 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5217713946811106, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:59,781 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:59,801 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.09037
2023-07-02 10:34:59,801 [model] Computed derived parameters: {}
2023-07-02 10:34:59,801 [model] Posterior to be computed for parameters {'Omega_m': 0.3045694710611836, 'b1': 0.4985005612742212}
2023-07-02 10:34:59,801 [prior] Evaluating prior at array([0.30456947, 0.49850056])
2023-07-02 10:34:59,801 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:59,801 [model] Got input parameters: {'Omega_m': 0.3045694710611836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4985005612742212, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:59,801 [classy] Got parameters {'Omega_m': 0.3045694710611836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:59,801 [classy] Re-using computed results
2023-07-02 10:34:59,801 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2233019978958}
2023-07-02 10:34:59,801 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:59,801 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4985005612742212, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:59,801 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:59,821 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.13392
2023-07-02 10:34:59,821 [model] Computed derived parameters: {}
2023-07-02 10:34:59,821 [mcmc] New sample, #950:
Omega_m:0.3045695, b1:0.5194528
2023-07-02 10:34:59,821 [model] Posterior to be computed for parameters {'Omega_m': 0.374046193561705, 'b1': 0.3718832118119013}
2023-07-02 10:34:59,821 [prior] Evaluating prior at array([0.37404619, 0.37188321])
2023-07-02 10:34:59,821 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:59,821 [model] Got input parameters: {'Omega_m': 0.374046193561705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.3718832118119013, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:59,822 [classy] Got parameters {'Omega_m': 0.374046193561705, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:59,822 [classy] Computing new state
2023-07-02 10:34:59,822 [classy] Setting parameters: {'Omega_m': 0.374046193561705, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:59,868 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.43969895255898}
2023-07-02 10:34:59,868 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:59,870 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.201278
2023-07-02 10:34:59,870 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.3718832118119013, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:59,870 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:59,889 [fs_likelihood.fslikelihood] Computed log-likelihood = -13.6095
2023-07-02 10:34:59,889 [model] Computed derived parameters: {}
2023-07-02 10:34:59,889 [model] Posterior to be computed for parameters {'Omega_m': 0.3045694710611836, 'b1': 0.5023366746563164}
2023-07-02 10:34:59,889 [prior] Evaluating prior at array([0.30456947, 0.50233667])
2023-07-02 10:34:59,890 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:59,890 [model] Got input parameters: {'Omega_m': 0.3045694710611836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5023366746563164, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:59,890 [classy] Got parameters {'Omega_m': 0.3045694710611836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:59,890 [classy] Re-using computed results
2023-07-02 10:34:59,890 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2233019978958}
2023-07-02 10:34:59,890 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:59,890 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5023366746563164, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:59,890 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:59,909 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.50937
2023-07-02 10:34:59,909 [model] Computed derived parameters: {}
2023-07-02 10:34:59,909 [mcmc] New sample, #951:
Omega_m:0.3045695, b1:0.4985006
2023-07-02 10:34:59,909 [model] Posterior to be computed for parameters {'Omega_m': 0.28333107173276495, 'b1': 0.541042441609651}
2023-07-02 10:34:59,909 [prior] Evaluating prior at array([0.28333107, 0.54104244])
2023-07-02 10:34:59,909 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:59,909 [model] Got input parameters: {'Omega_m': 0.28333107173276495, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.541042441609651, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:59,909 [classy] Got parameters {'Omega_m': 0.28333107173276495, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:59,909 [classy] Computing new state
2023-07-02 10:34:59,910 [classy] Setting parameters: {'Omega_m': 0.28333107173276495, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:34:59,958 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.92073736057338}
2023-07-02 10:34:59,958 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:34:59,961 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0563575
2023-07-02 10:34:59,961 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.541042441609651, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:59,961 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:34:59,986 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.3133
2023-07-02 10:34:59,987 [model] Computed derived parameters: {}
2023-07-02 10:34:59,987 [model] Posterior to be computed for parameters {'Omega_m': 0.3045694710611836, 'b1': 0.4845369682538885}
2023-07-02 10:34:59,987 [prior] Evaluating prior at array([0.30456947, 0.48453697])
2023-07-02 10:34:59,987 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:34:59,987 [model] Got input parameters: {'Omega_m': 0.3045694710611836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4845369682538885, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:59,987 [classy] Got parameters {'Omega_m': 0.3045694710611836, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:34:59,987 [classy] Re-using computed results
2023-07-02 10:34:59,987 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.2233019978958}
2023-07-02 10:34:59,987 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:34:59,987 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4845369682538885, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:34:59,987 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:00,007 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.848771
2023-07-02 10:35:00,007 [model] Computed derived parameters: {}
2023-07-02 10:35:00,007 [model] Posterior to be computed for parameters {'Omega_m': 0.3252451223500369, 'b1': 0.4646564837897688}
2023-07-02 10:35:00,007 [prior] Evaluating prior at array([0.32524512, 0.46465648])
2023-07-02 10:35:00,007 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:00,008 [model] Got input parameters: {'Omega_m': 0.3252451223500369, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4646564837897688, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:00,008 [classy] Got parameters {'Omega_m': 0.3252451223500369, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:00,008 [classy] Computing new state
2023-07-02 10:35:00,008 [classy] Setting parameters: {'Omega_m': 0.3252451223500369, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:00,065 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.7518816123588}
2023-07-02 10:35:00,065 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:00,068 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0098794
2023-07-02 10:35:00,068 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4646564837897688, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:00,068 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:00,092 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.59947
2023-07-02 10:35:00,092 [model] Computed derived parameters: {}
2023-07-02 10:35:00,092 [mcmc] New sample, #952:
Omega_m:0.3045695, b1:0.5023367
2023-07-02 10:35:00,092 [model] Posterior to be computed for parameters {'Omega_m': 0.3252451223500369, 'b1': 0.4179342487131231}
2023-07-02 10:35:00,092 [prior] Evaluating prior at array([0.32524512, 0.41793425])
2023-07-02 10:35:00,092 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:00,092 [model] Got input parameters: {'Omega_m': 0.3252451223500369, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4179342487131231, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:00,092 [classy] Got parameters {'Omega_m': 0.3252451223500369, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:00,092 [classy] Re-using computed results
2023-07-02 10:35:00,092 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.7518816123588}
2023-07-02 10:35:00,092 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:00,092 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4179342487131231, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:00,092 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:00,116 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.00712
2023-07-02 10:35:00,116 [model] Computed derived parameters: {}
2023-07-02 10:35:00,116 [model] Posterior to be computed for parameters {'Omega_m': 0.34225051421036184, 'b1': 0.4336651306224357}
2023-07-02 10:35:00,116 [prior] Evaluating prior at array([0.34225051, 0.43366513])
2023-07-02 10:35:00,116 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:00,116 [model] Got input parameters: {'Omega_m': 0.34225051421036184, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4336651306224357, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:00,116 [classy] Got parameters {'Omega_m': 0.34225051421036184, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:00,116 [classy] Computing new state
2023-07-02 10:35:00,116 [classy] Setting parameters: {'Omega_m': 0.34225051421036184, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:00,174 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.8226264233208}
2023-07-02 10:35:00,174 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:00,176 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0507595
2023-07-02 10:35:00,176 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4336651306224357, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:00,176 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:00,197 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.56126
2023-07-02 10:35:00,197 [model] Computed derived parameters: {}
2023-07-02 10:35:00,197 [mcmc] New sample, #953:
Omega_m:0.3252451, b1:0.4646565
2023-07-02 10:35:00,197 [model] Posterior to be computed for parameters {'Omega_m': 0.34225051421036184, 'b1': 0.41610957698224155}
2023-07-02 10:35:00,197 [prior] Evaluating prior at array([0.34225051, 0.41610958])
2023-07-02 10:35:00,197 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:00,197 [model] Got input parameters: {'Omega_m': 0.34225051421036184, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.41610957698224155, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:00,197 [classy] Got parameters {'Omega_m': 0.34225051421036184, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:00,197 [classy] Re-using computed results
2023-07-02 10:35:00,197 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.8226264233208}
2023-07-02 10:35:00,197 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:00,198 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.41610957698224155, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:00,198 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:00,217 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.99086
2023-07-02 10:35:00,217 [model] Computed derived parameters: {}
2023-07-02 10:35:00,217 [model] Posterior to be computed for parameters {'Omega_m': 0.34391183165934963, 'b1': 0.43063747467616165}
2023-07-02 10:35:00,217 [prior] Evaluating prior at array([0.34391183, 0.43063747])
2023-07-02 10:35:00,218 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:00,218 [model] Got input parameters: {'Omega_m': 0.34391183165934963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.43063747467616165, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:00,218 [classy] Got parameters {'Omega_m': 0.34391183165934963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:00,218 [classy] Computing new state
2023-07-02 10:35:00,218 [classy] Setting parameters: {'Omega_m': 0.34391183165934963, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:00,265 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.6388342695409}
2023-07-02 10:35:00,265 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:00,267 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0563416
2023-07-02 10:35:00,267 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.43063747467616165, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:00,267 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:00,287 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.00108
2023-07-02 10:35:00,287 [model] Computed derived parameters: {}
2023-07-02 10:35:00,287 [mcmc] New sample, #954:
Omega_m:0.3422505, b1:0.4336651
2023-07-02 10:35:00,287 [model] Posterior to be computed for parameters {'Omega_m': 0.34391183165934963, 'b1': 0.44631008503555586}
2023-07-02 10:35:00,287 [prior] Evaluating prior at array([0.34391183, 0.44631009])
2023-07-02 10:35:00,287 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:00,287 [model] Got input parameters: {'Omega_m': 0.34391183165934963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44631008503555586, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:00,287 [classy] Got parameters {'Omega_m': 0.34391183165934963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:00,287 [classy] Re-using computed results
2023-07-02 10:35:00,287 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.6388342695409}
2023-07-02 10:35:00,287 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:00,287 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44631008503555586, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:00,287 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:00,306 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.18739
2023-07-02 10:35:00,306 [model] Computed derived parameters: {}
2023-07-02 10:35:00,307 [mcmc] New sample, #955:
Omega_m:0.3439118, b1:0.4306375
2023-07-02 10:35:00,307 [model] Posterior to be computed for parameters {'Omega_m': 0.3572801093990901, 'b1': 0.42194716414116035}
2023-07-02 10:35:00,307 [prior] Evaluating prior at array([0.35728011, 0.42194716])
2023-07-02 10:35:00,307 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:00,307 [model] Got input parameters: {'Omega_m': 0.3572801093990901, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42194716414116035, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:00,307 [classy] Got parameters {'Omega_m': 0.3572801093990901, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:00,307 [classy] Computing new state
2023-07-02 10:35:00,307 [classy] Setting parameters: {'Omega_m': 0.3572801093990901, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:00,353 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.18891788405568}
2023-07-02 10:35:00,354 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:00,355 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.110776
2023-07-02 10:35:00,355 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42194716414116035, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:00,356 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:00,375 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.41395
2023-07-02 10:35:00,375 [model] Computed derived parameters: {}
2023-07-02 10:35:00,375 [model] Posterior to be computed for parameters {'Omega_m': 0.34391183165934963, 'b1': 0.453027820860188}
2023-07-02 10:35:00,376 [prior] Evaluating prior at array([0.34391183, 0.45302782])
2023-07-02 10:35:00,376 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:00,376 [model] Got input parameters: {'Omega_m': 0.34391183165934963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.453027820860188, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:00,376 [classy] Got parameters {'Omega_m': 0.34391183165934963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:00,376 [classy] Re-using computed results
2023-07-02 10:35:00,376 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.6388342695409}
2023-07-02 10:35:00,376 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:00,376 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.453027820860188, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:00,376 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:00,395 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.24829
2023-07-02 10:35:00,396 [model] Computed derived parameters: {}
2023-07-02 10:35:00,396 [mcmc] New sample, #956:
Omega_m:0.3439118, b1:0.4463101
2023-07-02 10:35:00,396 [model] Posterior to be computed for parameters {'Omega_m': 0.37981271141340484, 'b1': 0.38760052270590584}
2023-07-02 10:35:00,396 [prior] Evaluating prior at array([0.37981271, 0.38760052])
2023-07-02 10:35:00,396 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:00,396 [model] Got input parameters: {'Omega_m': 0.37981271141340484, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.38760052270590584, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:00,396 [classy] Got parameters {'Omega_m': 0.37981271141340484, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:00,396 [classy] Computing new state
2023-07-02 10:35:00,396 [classy] Setting parameters: {'Omega_m': 0.37981271141340484, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:00,444 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 139.85495459780157}
2023-07-02 10:35:00,444 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:00,446 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.237658
2023-07-02 10:35:00,446 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.38760052270590584, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:00,446 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:00,471 [fs_likelihood.fslikelihood] Computed log-likelihood = -14.9264
2023-07-02 10:35:00,471 [model] Computed derived parameters: {}
2023-07-02 10:35:00,471 [model] Posterior to be computed for parameters {'Omega_m': 0.34391183165934963, 'b1': 0.3967952562619351}
2023-07-02 10:35:00,471 [prior] Evaluating prior at array([0.34391183, 0.39679526])
2023-07-02 10:35:00,472 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:00,472 [model] Got input parameters: {'Omega_m': 0.34391183165934963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.3967952562619351, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:00,472 [classy] Got parameters {'Omega_m': 0.34391183165934963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:00,472 [classy] Re-using computed results
2023-07-02 10:35:00,472 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.6388342695409}
2023-07-02 10:35:00,472 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:00,472 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.3967952562619351, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:00,472 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:00,492 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.06345
2023-07-02 10:35:00,492 [model] Computed derived parameters: {}
2023-07-02 10:35:00,492 [model] Posterior to be computed for parameters {'Omega_m': 0.3620342826907217, 'b1': 0.42000069130128004}
2023-07-02 10:35:00,492 [prior] Evaluating prior at array([0.36203428, 0.42000069])
2023-07-02 10:35:00,492 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:00,492 [model] Got input parameters: {'Omega_m': 0.3620342826907217, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42000069130128004, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:00,492 [classy] Got parameters {'Omega_m': 0.3620342826907217, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:00,492 [classy] Computing new state
2023-07-02 10:35:00,492 [classy] Setting parameters: {'Omega_m': 0.3620342826907217, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:00,539 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.68529669951477}
2023-07-02 10:35:00,539 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:00,541 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.134033
2023-07-02 10:35:00,541 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42000069130128004, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:00,541 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:00,560 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.23591
2023-07-02 10:35:00,560 [model] Computed derived parameters: {}
2023-07-02 10:35:00,560 [model] Posterior to be computed for parameters {'Omega_m': 0.34391183165934963, 'b1': 0.4967319317580447}
2023-07-02 10:35:00,560 [prior] Evaluating prior at array([0.34391183, 0.49673193])
2023-07-02 10:35:00,560 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:00,560 [model] Got input parameters: {'Omega_m': 0.34391183165934963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4967319317580447, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:00,561 [classy] Got parameters {'Omega_m': 0.34391183165934963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:00,561 [classy] Re-using computed results
2023-07-02 10:35:00,561 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.6388342695409}
2023-07-02 10:35:00,561 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:00,561 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4967319317580447, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:00,561 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:00,580 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.06149
2023-07-02 10:35:00,580 [model] Computed derived parameters: {}
2023-07-02 10:35:00,581 [model] Posterior to be computed for parameters {'Omega_m': 0.3633015772324064, 'b1': 0.4176911195471579}
2023-07-02 10:35:00,581 [prior] Evaluating prior at array([0.36330158, 0.41769112])
2023-07-02 10:35:00,581 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:00,581 [model] Got input parameters: {'Omega_m': 0.3633015772324064, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4176911195471579, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:00,581 [classy] Got parameters {'Omega_m': 0.3633015772324064, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:00,581 [classy] Computing new state
2023-07-02 10:35:00,581 [classy] Setting parameters: {'Omega_m': 0.3633015772324064, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:00,628 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.55209103885187}
2023-07-02 10:35:00,628 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:00,630 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.140561
2023-07-02 10:35:00,630 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4176911195471579, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:00,630 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:00,650 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.73111
2023-07-02 10:35:00,651 [model] Computed derived parameters: {}
2023-07-02 10:35:00,651 [model] Posterior to be computed for parameters {'Omega_m': 0.34391183165934963, 'b1': 0.4473157840079476}
2023-07-02 10:35:00,651 [prior] Evaluating prior at array([0.34391183, 0.44731578])
2023-07-02 10:35:00,651 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:00,651 [model] Got input parameters: {'Omega_m': 0.34391183165934963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4473157840079476, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:00,651 [classy] Got parameters {'Omega_m': 0.34391183165934963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:00,651 [classy] Re-using computed results
2023-07-02 10:35:00,651 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.6388342695409}
2023-07-02 10:35:00,651 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:00,651 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4473157840079476, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:00,651 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:00,671 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.18059
2023-07-02 10:35:00,671 [model] Computed derived parameters: {}
2023-07-02 10:35:00,671 [mcmc] New sample, #957:
Omega_m:0.3439118, b1:0.4530278
2023-07-02 10:35:00,671 [model] Posterior to be computed for parameters {'Omega_m': 0.3690627822716684, 'b1': 0.40147961631932905}
2023-07-02 10:35:00,671 [prior] Evaluating prior at array([0.36906278, 0.40147962])
2023-07-02 10:35:00,671 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:00,671 [model] Got input parameters: {'Omega_m': 0.3690627822716684, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.40147961631932905, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:00,671 [classy] Got parameters {'Omega_m': 0.3690627822716684, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:00,671 [classy] Computing new state
2023-07-02 10:35:00,671 [classy] Setting parameters: {'Omega_m': 0.3690627822716684, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:00,718 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 140.9518939290794}
2023-07-02 10:35:00,718 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:00,720 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.171942
2023-07-02 10:35:00,720 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.40147961631932905, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:00,720 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:00,740 [fs_likelihood.fslikelihood] Computed log-likelihood = -10.0515
2023-07-02 10:35:00,740 [model] Computed derived parameters: {}
2023-07-02 10:35:00,740 [model] Posterior to be computed for parameters {'Omega_m': 0.34391183165934963, 'b1': 0.4403018250061556}
2023-07-02 10:35:00,740 [prior] Evaluating prior at array([0.34391183, 0.44030183])
2023-07-02 10:35:00,740 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:00,740 [model] Got input parameters: {'Omega_m': 0.34391183165934963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4403018250061556, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:00,741 [classy] Got parameters {'Omega_m': 0.34391183165934963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:00,741 [classy] Re-using computed results
2023-07-02 10:35:00,741 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.6388342695409}
2023-07-02 10:35:00,741 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:00,741 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4403018250061556, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:00,741 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:00,760 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.34324
2023-07-02 10:35:00,760 [model] Computed derived parameters: {}
2023-07-02 10:35:00,760 [mcmc] New sample, #958:
Omega_m:0.3439118, b1:0.4473158
2023-07-02 10:35:00,760 [model] Posterior to be computed for parameters {'Omega_m': 0.28184214164034893, 'b1': 0.5534202817971291}
2023-07-02 10:35:00,761 [prior] Evaluating prior at array([0.28184214, 0.55342028])
2023-07-02 10:35:00,761 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:00,761 [model] Got input parameters: {'Omega_m': 0.28184214164034893, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5534202817971291, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:00,761 [classy] Got parameters {'Omega_m': 0.28184214164034893, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:00,761 [classy] Computing new state
2023-07-02 10:35:00,761 [classy] Setting parameters: {'Omega_m': 0.28184214164034893, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:00,807 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.11635617958532}
2023-07-02 10:35:00,807 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:00,809 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0624849
2023-07-02 10:35:00,809 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5534202817971291, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:00,809 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:00,829 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.39263
2023-07-02 10:35:00,829 [model] Computed derived parameters: {}
2023-07-02 10:35:00,829 [model] Posterior to be computed for parameters {'Omega_m': 0.34391183165934963, 'b1': 0.41762693273368745}
2023-07-02 10:35:00,829 [prior] Evaluating prior at array([0.34391183, 0.41762693])
2023-07-02 10:35:00,829 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:00,829 [model] Got input parameters: {'Omega_m': 0.34391183165934963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.41762693273368745, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:00,829 [classy] Got parameters {'Omega_m': 0.34391183165934963, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:00,829 [classy] Re-using computed results
2023-07-02 10:35:00,829 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.6388342695409}
2023-07-02 10:35:00,829 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:00,829 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.41762693273368745, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:00,829 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:00,850 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.65642
2023-07-02 10:35:00,851 [model] Computed derived parameters: {}
2023-07-02 10:35:00,851 [model] Posterior to be computed for parameters {'Omega_m': 0.32260084639624564, 'b1': 0.47913987567016814}
2023-07-02 10:35:00,851 [prior] Evaluating prior at array([0.32260085, 0.47913988])
2023-07-02 10:35:00,851 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:00,851 [model] Got input parameters: {'Omega_m': 0.32260084639624564, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47913987567016814, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:00,851 [classy] Got parameters {'Omega_m': 0.32260084639624564, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:00,851 [classy] Computing new state
2023-07-02 10:35:00,851 [classy] Setting parameters: {'Omega_m': 0.32260084639624564, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:00,898 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.06001653484864}
2023-07-02 10:35:00,898 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:00,900 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00632359
2023-07-02 10:35:00,900 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47913987567016814, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:00,900 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:00,920 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.4794
2023-07-02 10:35:00,920 [model] Computed derived parameters: {}
2023-07-02 10:35:00,920 [mcmc] New sample, #959:
Omega_m:0.3439118, b1:0.4403018
2023-07-02 10:35:00,920 [model] Posterior to be computed for parameters {'Omega_m': 0.32260084639624564, 'b1': 0.5162728903924283}
2023-07-02 10:35:00,920 [prior] Evaluating prior at array([0.32260085, 0.51627289])
2023-07-02 10:35:00,920 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:00,920 [model] Got input parameters: {'Omega_m': 0.32260084639624564, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5162728903924283, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:00,920 [classy] Got parameters {'Omega_m': 0.32260084639624564, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:00,920 [classy] Re-using computed results
2023-07-02 10:35:00,920 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.06001653484864}
2023-07-02 10:35:00,920 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:00,920 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5162728903924283, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:00,920 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:00,941 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.157369
2023-07-02 10:35:00,941 [model] Computed derived parameters: {}
2023-07-02 10:35:00,941 [model] Posterior to be computed for parameters {'Omega_m': 0.3266058985391776, 'b1': 0.4718408974146434}
2023-07-02 10:35:00,941 [prior] Evaluating prior at array([0.3266059, 0.4718409])
2023-07-02 10:35:00,941 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:00,941 [model] Got input parameters: {'Omega_m': 0.3266058985391776, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4718408974146434, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:00,941 [classy] Got parameters {'Omega_m': 0.3266058985391776, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:00,941 [classy] Computing new state
2023-07-02 10:35:00,941 [classy] Setting parameters: {'Omega_m': 0.3266058985391776, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:00,988 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.5941816974159}
2023-07-02 10:35:00,988 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:00,989 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0120145
2023-07-02 10:35:00,989 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4718408974146434, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:00,989 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:01,009 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.07841
2023-07-02 10:35:01,009 [model] Computed derived parameters: {}
2023-07-02 10:35:01,009 [mcmc] New sample, #960:
Omega_m:0.3226008, b1:0.4791399
2023-07-02 10:35:01,009 [mcmc] Learn + convergence test @ 960 samples accepted.
2023-07-02 10:35:01,009 [mcmc] Ready to check convergence and learn a new proposal covmat
2023-07-02 10:35:01,014 [mcmc] - Acceptance rate: 0.456
2023-07-02 10:35:01,015 [mcmc] - Condition number = 26.81
2023-07-02 10:35:01,015 [mcmc] - Eigenvalues = array([0.00179519, 0.04812897])
2023-07-02 10:35:01,015 [mcmc] - Convergence of means: R-1 = 0.048129 after 768 accepted steps
2023-07-02 10:35:01,015 [mcmc] - Updated covariance matrix of proposal pdf.
2023-07-02 10:35:01,015 [mcmc] array([[ 0.00010512, -0.0001918 ],
[-0.0001918 , 0.00052479]])
2023-07-02 10:35:01,025 [mcmc] Dumped checkpoint and progress info, and current covmat.
2023-07-02 10:35:01,025 [model] Posterior to be computed for parameters {'Omega_m': 0.3266058985391776, 'b1': 0.48684714590634703}
2023-07-02 10:35:01,025 [prior] Evaluating prior at array([0.3266059 , 0.48684715])
2023-07-02 10:35:01,025 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:01,025 [model] Got input parameters: {'Omega_m': 0.3266058985391776, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48684714590634703, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:01,025 [classy] Got parameters {'Omega_m': 0.3266058985391776, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:01,025 [classy] Re-using computed results
2023-07-02 10:35:01,025 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.5941816974159}
2023-07-02 10:35:01,025 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:01,025 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48684714590634703, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:01,025 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:01,048 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.07221
2023-07-02 10:35:01,048 [model] Computed derived parameters: {}
2023-07-02 10:35:01,048 [mcmc] New sample, #961:
Omega_m:0.3266059, b1:0.4718409
2023-07-02 10:35:01,048 [model] Posterior to be computed for parameters {'Omega_m': 0.3153990271038461, 'b1': 0.5072960797137092}
2023-07-02 10:35:01,048 [prior] Evaluating prior at array([0.31539903, 0.50729608])
2023-07-02 10:35:01,048 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:01,048 [model] Got input parameters: {'Omega_m': 0.3153990271038461, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5072960797137092, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:01,048 [classy] Got parameters {'Omega_m': 0.3153990271038461, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:01,048 [classy] Computing new state
2023-07-02 10:35:01,048 [classy] Setting parameters: {'Omega_m': 0.3153990271038461, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:01,096 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.9108019604391}
2023-07-02 10:35:01,096 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:01,098 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000719795
2023-07-02 10:35:01,098 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5072960797137092, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:01,098 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:01,117 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.7665
2023-07-02 10:35:01,117 [model] Computed derived parameters: {}
2023-07-02 10:35:01,117 [mcmc] New sample, #962:
Omega_m:0.3266059, b1:0.4868471
2023-07-02 10:35:01,118 [model] Posterior to be computed for parameters {'Omega_m': 0.3153990271038461, 'b1': 0.4971942161608111}
2023-07-02 10:35:01,118 [prior] Evaluating prior at array([0.31539903, 0.49719422])
2023-07-02 10:35:01,118 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:01,118 [model] Got input parameters: {'Omega_m': 0.3153990271038461, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4971942161608111, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:01,118 [classy] Got parameters {'Omega_m': 0.3153990271038461, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:01,118 [classy] Re-using computed results
2023-07-02 10:35:01,118 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.9108019604391}
2023-07-02 10:35:01,118 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:01,118 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4971942161608111, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:01,118 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:01,141 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.91061
2023-07-02 10:35:01,141 [model] Computed derived parameters: {}
2023-07-02 10:35:01,141 [mcmc] New sample, #963:
Omega_m:0.315399, b1:0.5072961
2023-07-02 10:35:01,141 [model] Posterior to be computed for parameters {'Omega_m': 0.33146132344899604, 'b1': 0.46788569445147027}
2023-07-02 10:35:01,141 [prior] Evaluating prior at array([0.33146132, 0.46788569])
2023-07-02 10:35:01,141 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:01,141 [model] Got input parameters: {'Omega_m': 0.33146132344899604, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46788569445147027, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:01,142 [classy] Got parameters {'Omega_m': 0.33146132344899604, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:01,142 [classy] Computing new state
2023-07-02 10:35:01,142 [classy] Setting parameters: {'Omega_m': 0.33146132344899604, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:01,188 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.0362888521516}
2023-07-02 10:35:01,188 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:01,190 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0212855
2023-07-02 10:35:01,190 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46788569445147027, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:01,190 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:01,209 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.51873
2023-07-02 10:35:01,209 [model] Computed derived parameters: {}
2023-07-02 10:35:01,209 [mcmc] New sample, #964:
Omega_m:0.315399, b1:0.4971942
2023-07-02 10:35:01,209 [model] Posterior to be computed for parameters {'Omega_m': 0.33146132344899604, 'b1': 0.48839232369723584}
2023-07-02 10:35:01,210 [prior] Evaluating prior at array([0.33146132, 0.48839232])
2023-07-02 10:35:01,210 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:01,210 [model] Got input parameters: {'Omega_m': 0.33146132344899604, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48839232369723584, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:01,210 [classy] Got parameters {'Omega_m': 0.33146132344899604, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:01,210 [classy] Re-using computed results
2023-07-02 10:35:01,210 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.0362888521516}
2023-07-02 10:35:01,210 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:01,210 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48839232369723584, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:01,210 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:01,229 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.646335
2023-07-02 10:35:01,229 [model] Computed derived parameters: {}
2023-07-02 10:35:01,229 [model] Posterior to be computed for parameters {'Omega_m': 0.36292155635551965, 'b1': 0.4104808938358857}
2023-07-02 10:35:01,229 [prior] Evaluating prior at array([0.36292156, 0.41048089])
2023-07-02 10:35:01,229 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:01,229 [model] Got input parameters: {'Omega_m': 0.36292155635551965, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4104808938358857, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:01,230 [classy] Got parameters {'Omega_m': 0.36292155635551965, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:01,230 [classy] Computing new state
2023-07-02 10:35:01,230 [classy] Setting parameters: {'Omega_m': 0.36292155635551965, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:01,276 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.59198852385637}
2023-07-02 10:35:01,276 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:01,278 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.138589
2023-07-02 10:35:01,278 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4104808938358857, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:01,278 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:01,298 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.56235
2023-07-02 10:35:01,298 [model] Computed derived parameters: {}
2023-07-02 10:35:01,298 [model] Posterior to be computed for parameters {'Omega_m': 0.33146132344899604, 'b1': 0.4513028752252615}
2023-07-02 10:35:01,298 [prior] Evaluating prior at array([0.33146132, 0.45130288])
2023-07-02 10:35:01,298 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:01,298 [model] Got input parameters: {'Omega_m': 0.33146132344899604, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4513028752252615, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:01,298 [classy] Got parameters {'Omega_m': 0.33146132344899604, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:01,298 [classy] Re-using computed results
2023-07-02 10:35:01,299 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.0362888521516}
2023-07-02 10:35:01,299 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:01,299 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4513028752252615, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:01,299 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:01,318 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.547978
2023-07-02 10:35:01,318 [model] Computed derived parameters: {}
2023-07-02 10:35:01,318 [mcmc] New sample, #965:
Omega_m:0.3314613, b1:0.4678857
2023-07-02 10:35:01,318 [model] Posterior to be computed for parameters {'Omega_m': 0.3450222149474701, 'b1': 0.4265586123664174}
2023-07-02 10:35:01,318 [prior] Evaluating prior at array([0.34502221, 0.42655861])
2023-07-02 10:35:01,318 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:01,318 [model] Got input parameters: {'Omega_m': 0.3450222149474701, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4265586123664174, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:01,318 [classy] Got parameters {'Omega_m': 0.3450222149474701, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:01,319 [classy] Computing new state
2023-07-02 10:35:01,319 [classy] Setting parameters: {'Omega_m': 0.3450222149474701, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:01,365 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.5164492143454}
2023-07-02 10:35:01,365 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:01,367 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0602224
2023-07-02 10:35:01,367 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4265586123664174, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:01,367 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:01,386 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.51079
2023-07-02 10:35:01,386 [model] Computed derived parameters: {}
2023-07-02 10:35:01,387 [model] Posterior to be computed for parameters {'Omega_m': 0.33146132344899604, 'b1': 0.400922548011895}
2023-07-02 10:35:01,387 [prior] Evaluating prior at array([0.33146132, 0.40092255])
2023-07-02 10:35:01,387 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:01,387 [model] Got input parameters: {'Omega_m': 0.33146132344899604, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.400922548011895, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:01,387 [classy] Got parameters {'Omega_m': 0.33146132344899604, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:01,387 [classy] Re-using computed results
2023-07-02 10:35:01,387 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.0362888521516}
2023-07-02 10:35:01,387 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:01,387 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.400922548011895, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:01,387 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:01,406 [fs_likelihood.fslikelihood] Computed log-likelihood = -10.8001
2023-07-02 10:35:01,407 [model] Computed derived parameters: {}
2023-07-02 10:35:01,407 [model] Posterior to be computed for parameters {'Omega_m': 0.3286369322219044, 'b1': 0.4564564802774982}
2023-07-02 10:35:01,407 [prior] Evaluating prior at array([0.32863693, 0.45645648])
2023-07-02 10:35:01,407 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:01,407 [model] Got input parameters: {'Omega_m': 0.3286369322219044, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4564564802774982, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:01,407 [classy] Got parameters {'Omega_m': 0.3286369322219044, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:01,407 [classy] Computing new state
2023-07-02 10:35:01,407 [classy] Setting parameters: {'Omega_m': 0.3286369322219044, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:01,453 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.35990131271876}
2023-07-02 10:35:01,453 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:01,455 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0155813
2023-07-02 10:35:01,455 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4564564802774982, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:01,455 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:01,475 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.98364
2023-07-02 10:35:01,475 [model] Computed derived parameters: {}
2023-07-02 10:35:01,475 [mcmc] New sample, #966:
Omega_m:0.3314613, b1:0.4513029
2023-07-02 10:35:01,475 [model] Posterior to be computed for parameters {'Omega_m': 0.3286369322219044, 'b1': 0.438528350959547}
2023-07-02 10:35:01,475 [prior] Evaluating prior at array([0.32863693, 0.43852835])
2023-07-02 10:35:01,475 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:01,475 [model] Got input parameters: {'Omega_m': 0.3286369322219044, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.438528350959547, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:01,475 [classy] Got parameters {'Omega_m': 0.3286369322219044, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:01,475 [classy] Re-using computed results
2023-07-02 10:35:01,475 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.35990131271876}
2023-07-02 10:35:01,475 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:01,475 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.438528350959547, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:01,475 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:01,495 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.6493
2023-07-02 10:35:01,495 [model] Computed derived parameters: {}
2023-07-02 10:35:01,495 [model] Posterior to be computed for parameters {'Omega_m': 0.3591332009334993, 'b1': 0.400810604097561}
2023-07-02 10:35:01,495 [prior] Evaluating prior at array([0.3591332, 0.4008106])
2023-07-02 10:35:01,495 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:01,496 [model] Got input parameters: {'Omega_m': 0.3591332009334993, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.400810604097561, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:01,496 [classy] Got parameters {'Omega_m': 0.3591332009334993, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:01,496 [classy] Computing new state
2023-07-02 10:35:01,496 [classy] Setting parameters: {'Omega_m': 0.3591332009334993, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:01,542 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.99187113692795}
2023-07-02 10:35:01,542 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:01,544 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.119608
2023-07-02 10:35:01,544 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.400810604097561, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:01,544 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:01,563 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.16797
2023-07-02 10:35:01,563 [model] Computed derived parameters: {}
2023-07-02 10:35:01,564 [model] Posterior to be computed for parameters {'Omega_m': 0.3286369322219044, 'b1': 0.4336426791470887}
2023-07-02 10:35:01,564 [prior] Evaluating prior at array([0.32863693, 0.43364268])
2023-07-02 10:35:01,564 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:01,564 [model] Got input parameters: {'Omega_m': 0.3286369322219044, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4336426791470887, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:01,564 [classy] Got parameters {'Omega_m': 0.3286369322219044, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:01,564 [classy] Re-using computed results
2023-07-02 10:35:01,564 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.35990131271876}
2023-07-02 10:35:01,564 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:01,564 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4336426791470887, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:01,564 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:01,583 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.64156
2023-07-02 10:35:01,584 [model] Computed derived parameters: {}
2023-07-02 10:35:01,584 [model] Posterior to be computed for parameters {'Omega_m': 0.28338798370664986, 'b1': 0.5390212494354664}
2023-07-02 10:35:01,584 [prior] Evaluating prior at array([0.28338798, 0.53902125])
2023-07-02 10:35:01,584 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:01,584 [model] Got input parameters: {'Omega_m': 0.28338798370664986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5390212494354664, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:01,584 [classy] Got parameters {'Omega_m': 0.28338798370664986, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:01,584 [classy] Computing new state
2023-07-02 10:35:01,584 [classy] Setting parameters: {'Omega_m': 0.28338798370664986, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:01,630 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.9132783609878}
2023-07-02 10:35:01,630 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:01,632 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0561301
2023-07-02 10:35:01,632 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5390212494354664, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:01,632 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:01,652 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.46071
2023-07-02 10:35:01,652 [model] Computed derived parameters: {}
2023-07-02 10:35:01,652 [model] Posterior to be computed for parameters {'Omega_m': 0.3286369322219044, 'b1': 0.5927311807633766}
2023-07-02 10:35:01,652 [prior] Evaluating prior at array([0.32863693, 0.59273118])
2023-07-02 10:35:01,652 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:01,652 [model] Got input parameters: {'Omega_m': 0.3286369322219044, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5927311807633766, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:01,652 [classy] Got parameters {'Omega_m': 0.3286369322219044, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:01,653 [classy] Re-using computed results
2023-07-02 10:35:01,653 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.35990131271876}
2023-07-02 10:35:01,653 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:01,653 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5927311807633766, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:01,653 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:01,672 [fs_likelihood.fslikelihood] Computed log-likelihood = -40.0882
2023-07-02 10:35:01,672 [model] Computed derived parameters: {}
2023-07-02 10:35:01,672 [model] Posterior to be computed for parameters {'Omega_m': 0.30476919199715463, 'b1': 0.5000074251423157}
2023-07-02 10:35:01,672 [prior] Evaluating prior at array([0.30476919, 0.50000743])
2023-07-02 10:35:01,672 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:01,672 [model] Got input parameters: {'Omega_m': 0.30476919199715463, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5000074251423157, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:01,673 [classy] Got parameters {'Omega_m': 0.30476919199715463, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:01,673 [classy] Computing new state
2023-07-02 10:35:01,673 [classy] Setting parameters: {'Omega_m': 0.30476919199715463, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:01,719 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.19872859442944}
2023-07-02 10:35:01,719 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:01,721 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00392345
2023-07-02 10:35:01,721 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5000074251423157, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:01,721 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:01,740 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.35121
2023-07-02 10:35:01,741 [model] Computed derived parameters: {}
2023-07-02 10:35:01,741 [mcmc] New sample, #967:
Omega_m:0.3286369, b1:0.4564565
2023-07-02 10:35:01,741 [model] Posterior to be computed for parameters {'Omega_m': 0.30476919199715463, 'b1': 0.5380503268177612}
2023-07-02 10:35:01,741 [prior] Evaluating prior at array([0.30476919, 0.53805033])
2023-07-02 10:35:01,741 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:01,741 [model] Got input parameters: {'Omega_m': 0.30476919199715463, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5380503268177612, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:01,741 [classy] Got parameters {'Omega_m': 0.30476919199715463, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:01,741 [classy] Re-using computed results
2023-07-02 10:35:01,741 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.19872859442944}
2023-07-02 10:35:01,741 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:01,741 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5380503268177612, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:01,741 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:01,760 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.29392
2023-07-02 10:35:01,761 [model] Computed derived parameters: {}
2023-07-02 10:35:01,761 [mcmc] New sample, #968:
Omega_m:0.3047692, b1:0.5000074
2023-07-02 10:35:01,761 [model] Posterior to be computed for parameters {'Omega_m': 0.27107614815609765, 'b1': 0.5995292888322783}
2023-07-02 10:35:01,761 [prior] Evaluating prior at array([0.27107615, 0.59952929])
2023-07-02 10:35:01,761 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:01,761 [model] Got input parameters: {'Omega_m': 0.27107614815609765, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5995292888322783, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:01,761 [classy] Got parameters {'Omega_m': 0.27107614815609765, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:01,761 [classy] Computing new state
2023-07-02 10:35:01,761 [classy] Setting parameters: {'Omega_m': 0.27107614815609765, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:01,808 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.55767162907225}
2023-07-02 10:35:01,808 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:01,810 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.117261
2023-07-02 10:35:01,810 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5995292888322783, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:01,810 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:01,829 [fs_likelihood.fslikelihood] Computed log-likelihood = -11.2484
2023-07-02 10:35:01,829 [model] Computed derived parameters: {}
2023-07-02 10:35:01,829 [model] Posterior to be computed for parameters {'Omega_m': 0.30476919199715463, 'b1': 0.4943399187940602}
2023-07-02 10:35:01,829 [prior] Evaluating prior at array([0.30476919, 0.49433992])
2023-07-02 10:35:01,829 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:01,829 [model] Got input parameters: {'Omega_m': 0.30476919199715463, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4943399187940602, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:01,829 [classy] Got parameters {'Omega_m': 0.30476919199715463, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:01,829 [classy] Re-using computed results
2023-07-02 10:35:01,829 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.19872859442944}
2023-07-02 10:35:01,830 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:01,830 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4943399187940602, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:01,830 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:01,850 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.7145
2023-07-02 10:35:01,850 [model] Computed derived parameters: {}
2023-07-02 10:35:01,850 [mcmc] New sample, #969:
Omega_m:0.3047692, b1:0.5380503
2023-07-02 10:35:01,850 [model] Posterior to be computed for parameters {'Omega_m': 0.29491750115761656, 'b1': 0.5123160841342982}
2023-07-02 10:35:01,850 [prior] Evaluating prior at array([0.2949175 , 0.51231608])
2023-07-02 10:35:01,850 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:01,850 [model] Got input parameters: {'Omega_m': 0.29491750115761656, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5123160841342982, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:01,850 [classy] Got parameters {'Omega_m': 0.29491750115761656, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:01,850 [classy] Computing new state
2023-07-02 10:35:01,850 [classy] Setting parameters: {'Omega_m': 0.29491750115761656, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:01,896 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.42818080980723}
2023-07-02 10:35:01,896 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:01,898 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0199854
2023-07-02 10:35:01,898 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5123160841342982, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:01,898 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:01,917 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.13525
2023-07-02 10:35:01,917 [model] Computed derived parameters: {}
2023-07-02 10:35:01,918 [model] Posterior to be computed for parameters {'Omega_m': 0.30476919199715463, 'b1': 0.4904441388603413}
2023-07-02 10:35:01,918 [prior] Evaluating prior at array([0.30476919, 0.49044414])
2023-07-02 10:35:01,918 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:01,918 [model] Got input parameters: {'Omega_m': 0.30476919199715463, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4904441388603413, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:01,918 [classy] Got parameters {'Omega_m': 0.30476919199715463, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:01,918 [classy] Re-using computed results
2023-07-02 10:35:01,918 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.19872859442944}
2023-07-02 10:35:01,918 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:01,918 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4904441388603413, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:01,918 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:01,939 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.184428
2023-07-02 10:35:01,939 [model] Computed derived parameters: {}
2023-07-02 10:35:01,939 [mcmc] New sample, #970:
Omega_m:0.3047692, b1:0.4943399
2023-07-02 10:35:01,939 [model] Posterior to be computed for parameters {'Omega_m': 0.310503411314279, 'b1': 0.47998103397603825}
2023-07-02 10:35:01,939 [prior] Evaluating prior at array([0.31050341, 0.47998103])
2023-07-02 10:35:01,939 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:01,939 [model] Got input parameters: {'Omega_m': 0.310503411314279, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47998103397603825, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:01,939 [classy] Got parameters {'Omega_m': 0.310503411314279, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:01,939 [classy] Computing new state
2023-07-02 10:35:01,939 [classy] Setting parameters: {'Omega_m': 0.310503411314279, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:01,986 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.49912258242392}
2023-07-02 10:35:01,986 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:01,988 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000444125
2023-07-02 10:35:01,988 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47998103397603825, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:01,988 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:02,008 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.677234
2023-07-02 10:35:02,008 [model] Computed derived parameters: {}
2023-07-02 10:35:02,008 [mcmc] New sample, #971:
Omega_m:0.3047692, b1:0.4904441
2023-07-02 10:35:02,008 [model] Posterior to be computed for parameters {'Omega_m': 0.310503411314279, 'b1': 0.4771775577013586}
2023-07-02 10:35:02,008 [prior] Evaluating prior at array([0.31050341, 0.47717756])
2023-07-02 10:35:02,008 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:02,008 [model] Got input parameters: {'Omega_m': 0.310503411314279, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4771775577013586, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:02,008 [classy] Got parameters {'Omega_m': 0.310503411314279, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:02,008 [classy] Re-using computed results
2023-07-02 10:35:02,008 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.49912258242392}
2023-07-02 10:35:02,008 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:02,008 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4771775577013586, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:02,008 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:02,029 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.246691
2023-07-02 10:35:02,029 [model] Computed derived parameters: {}
2023-07-02 10:35:02,029 [mcmc] New sample, #972:
Omega_m:0.3105034, b1:0.479981
2023-07-02 10:35:02,029 [model] Posterior to be computed for parameters {'Omega_m': 0.31409531122027234, 'b1': 0.4706234963074924}
2023-07-02 10:35:02,029 [prior] Evaluating prior at array([0.31409531, 0.4706235 ])
2023-07-02 10:35:02,030 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:02,030 [model] Got input parameters: {'Omega_m': 0.31409531122027234, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4706234963074924, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:02,030 [classy] Got parameters {'Omega_m': 0.31409531122027234, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:02,030 [classy] Computing new state
2023-07-02 10:35:02,030 [classy] Setting parameters: {'Omega_m': 0.31409531122027234, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:02,076 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.0666718619617}
2023-07-02 10:35:02,076 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:02,078 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000361015
2023-07-02 10:35:02,078 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4706234963074924, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:02,078 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:02,098 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.352086
2023-07-02 10:35:02,098 [model] Computed derived parameters: {}
2023-07-02 10:35:02,098 [mcmc] New sample, #973:
Omega_m:0.3105034, b1:0.4771776
2023-07-02 10:35:02,098 [model] Posterior to be computed for parameters {'Omega_m': 0.31409531122027234, 'b1': 0.4604213161642931}
2023-07-02 10:35:02,098 [prior] Evaluating prior at array([0.31409531, 0.46042132])
2023-07-02 10:35:02,098 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:02,098 [model] Got input parameters: {'Omega_m': 0.31409531122027234, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4604213161642931, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:02,098 [classy] Got parameters {'Omega_m': 0.31409531122027234, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:02,098 [classy] Re-using computed results
2023-07-02 10:35:02,098 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.0666718619617}
2023-07-02 10:35:02,098 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:02,098 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4604213161642931, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:02,098 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:02,118 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.54354
2023-07-02 10:35:02,118 [model] Computed derived parameters: {}
2023-07-02 10:35:02,118 [model] Posterior to be computed for parameters {'Omega_m': 0.32189574023786205, 'b1': 0.4563902236613161}
2023-07-02 10:35:02,118 [prior] Evaluating prior at array([0.32189574, 0.45639022])
2023-07-02 10:35:02,118 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:02,118 [model] Got input parameters: {'Omega_m': 0.32189574023786205, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4563902236613161, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:02,118 [classy] Got parameters {'Omega_m': 0.32189574023786205, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:02,118 [classy] Computing new state
2023-07-02 10:35:02,118 [classy] Setting parameters: {'Omega_m': 0.32189574023786205, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:02,167 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.142562631618}
2023-07-02 10:35:02,167 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:02,169 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00550918
2023-07-02 10:35:02,169 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4563902236613161, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:02,169 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:02,188 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.0823556
2023-07-02 10:35:02,188 [model] Computed derived parameters: {}
2023-07-02 10:35:02,188 [mcmc] New sample, #974:
Omega_m:0.3140953, b1:0.4706235
2023-07-02 10:35:02,188 [model] Posterior to be computed for parameters {'Omega_m': 0.32189574023786205, 'b1': 0.4776534157242988}
2023-07-02 10:35:02,188 [prior] Evaluating prior at array([0.32189574, 0.47765342])
2023-07-02 10:35:02,188 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:02,188 [model] Got input parameters: {'Omega_m': 0.32189574023786205, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4776534157242988, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:02,188 [classy] Got parameters {'Omega_m': 0.32189574023786205, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:02,188 [classy] Re-using computed results
2023-07-02 10:35:02,189 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.142562631618}
2023-07-02 10:35:02,189 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:02,189 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4776534157242988, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:02,189 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:02,208 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.40273
2023-07-02 10:35:02,208 [model] Computed derived parameters: {}
2023-07-02 10:35:02,208 [mcmc] New sample, #975:
Omega_m:0.3218957, b1:0.4563902
2023-07-02 10:35:02,209 [model] Posterior to be computed for parameters {'Omega_m': 0.31716025012163707, 'b1': 0.486294161225029}
2023-07-02 10:35:02,209 [prior] Evaluating prior at array([0.31716025, 0.48629416])
2023-07-02 10:35:02,209 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:02,209 [model] Got input parameters: {'Omega_m': 0.31716025012163707, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.486294161225029, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:02,209 [classy] Got parameters {'Omega_m': 0.31716025012163707, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:02,209 [classy] Computing new state
2023-07-02 10:35:02,209 [classy] Setting parameters: {'Omega_m': 0.31716025012163707, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:02,256 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.70115488036203}
2023-07-02 10:35:02,256 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:02,258 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00152786
2023-07-02 10:35:02,258 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.486294161225029, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:02,258 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:02,277 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.63059
2023-07-02 10:35:02,277 [model] Computed derived parameters: {}
2023-07-02 10:35:02,277 [mcmc] New sample, #976:
Omega_m:0.3218957, b1:0.4776534
2023-07-02 10:35:02,278 [model] Posterior to be computed for parameters {'Omega_m': 0.31716025012163707, 'b1': 0.4534801701469038}
2023-07-02 10:35:02,278 [prior] Evaluating prior at array([0.31716025, 0.45348017])
2023-07-02 10:35:02,278 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:02,278 [model] Got input parameters: {'Omega_m': 0.31716025012163707, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4534801701469038, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:02,278 [classy] Got parameters {'Omega_m': 0.31716025012163707, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:02,278 [classy] Re-using computed results
2023-07-02 10:35:02,278 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.70115488036203}
2023-07-02 10:35:02,278 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:02,278 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4534801701469038, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:02,278 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:02,298 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.86582
2023-07-02 10:35:02,298 [model] Computed derived parameters: {}
2023-07-02 10:35:02,298 [model] Posterior to be computed for parameters {'Omega_m': 0.3185608664488573, 'b1': 0.4837384871700433}
2023-07-02 10:35:02,298 [prior] Evaluating prior at array([0.31856087, 0.48373849])
2023-07-02 10:35:02,298 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:02,298 [model] Got input parameters: {'Omega_m': 0.3185608664488573, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4837384871700433, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:02,298 [classy] Got parameters {'Omega_m': 0.3185608664488573, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:02,298 [classy] Computing new state
2023-07-02 10:35:02,298 [classy] Setting parameters: {'Omega_m': 0.3185608664488573, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:02,345 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.53517351555683}
2023-07-02 10:35:02,345 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:02,347 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0024329
2023-07-02 10:35:02,347 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4837384871700433, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:02,347 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:02,366 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.58818
2023-07-02 10:35:02,366 [model] Computed derived parameters: {}
2023-07-02 10:35:02,366 [mcmc] New sample, #977:
Omega_m:0.3171603, b1:0.4862942
2023-07-02 10:35:02,367 [model] Posterior to be computed for parameters {'Omega_m': 0.3185608664488573, 'b1': 0.4934481613740825}
2023-07-02 10:35:02,367 [prior] Evaluating prior at array([0.31856087, 0.49344816])
2023-07-02 10:35:02,367 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:02,367 [model] Got input parameters: {'Omega_m': 0.3185608664488573, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4934481613740825, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:02,367 [classy] Got parameters {'Omega_m': 0.3185608664488573, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:02,367 [classy] Re-using computed results
2023-07-02 10:35:02,367 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.53517351555683}
2023-07-02 10:35:02,367 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:02,367 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4934481613740825, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:02,367 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:02,386 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.8633
2023-07-02 10:35:02,386 [model] Computed derived parameters: {}
2023-07-02 10:35:02,386 [mcmc] New sample, #978:
Omega_m:0.3185609, b1:0.4837385
2023-07-02 10:35:02,386 [model] Posterior to be computed for parameters {'Omega_m': 0.31346895603323616, 'b1': 0.5027392592190872}
2023-07-02 10:35:02,386 [prior] Evaluating prior at array([0.31346896, 0.50273926])
2023-07-02 10:35:02,386 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:02,386 [model] Got input parameters: {'Omega_m': 0.31346895603323616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5027392592190872, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:02,386 [classy] Got parameters {'Omega_m': 0.31346895603323616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:02,386 [classy] Computing new state
2023-07-02 10:35:02,386 [classy] Setting parameters: {'Omega_m': 0.31346895603323616, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:02,432 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.14176664238337}
2023-07-02 10:35:02,432 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:02,434 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000261749
2023-07-02 10:35:02,434 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5027392592190872, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:02,434 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:02,455 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.90952
2023-07-02 10:35:02,455 [model] Computed derived parameters: {}
2023-07-02 10:35:02,455 [mcmc] New sample, #979:
Omega_m:0.3185609, b1:0.4934482
2023-07-02 10:35:02,455 [model] Posterior to be computed for parameters {'Omega_m': 0.31346895603323616, 'b1': 0.502907825432902}
2023-07-02 10:35:02,455 [prior] Evaluating prior at array([0.31346896, 0.50290783])
2023-07-02 10:35:02,455 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:02,455 [model] Got input parameters: {'Omega_m': 0.31346895603323616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.502907825432902, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:02,455 [classy] Got parameters {'Omega_m': 0.31346895603323616, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:02,455 [classy] Re-using computed results
2023-07-02 10:35:02,455 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.14176664238337}
2023-07-02 10:35:02,456 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:02,456 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.502907825432902, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:02,456 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:02,475 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.9098
2023-07-02 10:35:02,475 [model] Computed derived parameters: {}
2023-07-02 10:35:02,475 [mcmc] New sample, #980:
Omega_m:0.313469, b1:0.5027393
2023-07-02 10:35:02,475 [model] Posterior to be computed for parameters {'Omega_m': 0.3227621946066772, 'b1': 0.48595065575883956}
2023-07-02 10:35:02,475 [prior] Evaluating prior at array([0.32276219, 0.48595066])
2023-07-02 10:35:02,475 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:02,475 [model] Got input parameters: {'Omega_m': 0.3227621946066772, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48595065575883956, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:02,476 [classy] Got parameters {'Omega_m': 0.3227621946066772, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:02,476 [classy] Computing new state
2023-07-02 10:35:02,476 [classy] Setting parameters: {'Omega_m': 0.3227621946066772, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:02,522 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.0411500758586}
2023-07-02 10:35:02,522 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:02,524 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00651792
2023-07-02 10:35:02,524 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48595065575883956, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:02,524 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:02,543 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.61438
2023-07-02 10:35:02,543 [model] Computed derived parameters: {}
2023-07-02 10:35:02,543 [mcmc] New sample, #981:
Omega_m:0.313469, b1:0.5029078
2023-07-02 10:35:02,543 [model] Posterior to be computed for parameters {'Omega_m': 0.3227621946066772, 'b1': 0.4175192027778834}
2023-07-02 10:35:02,543 [prior] Evaluating prior at array([0.32276219, 0.4175192 ])
2023-07-02 10:35:02,544 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:02,544 [model] Got input parameters: {'Omega_m': 0.3227621946066772, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4175192027778834, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:02,544 [classy] Got parameters {'Omega_m': 0.3227621946066772, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:02,544 [classy] Re-using computed results
2023-07-02 10:35:02,544 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.0411500758586}
2023-07-02 10:35:02,544 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:02,544 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4175192027778834, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:02,544 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:02,563 [fs_likelihood.fslikelihood] Computed log-likelihood = -9.35049
2023-07-02 10:35:02,564 [model] Computed derived parameters: {}
2023-07-02 10:35:02,564 [model] Posterior to be computed for parameters {'Omega_m': 0.34085375493015724, 'b1': 0.4529393803407596}
2023-07-02 10:35:02,564 [prior] Evaluating prior at array([0.34085375, 0.45293938])
2023-07-02 10:35:02,564 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:02,564 [model] Got input parameters: {'Omega_m': 0.34085375493015724, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4529393803407596, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:02,564 [classy] Got parameters {'Omega_m': 0.34085375493015724, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:02,564 [classy] Computing new state
2023-07-02 10:35:02,564 [classy] Setting parameters: {'Omega_m': 0.34085375493015724, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:02,611 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.9777765417801}
2023-07-02 10:35:02,611 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:02,613 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0462772
2023-07-02 10:35:02,613 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4529393803407596, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:02,613 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:02,632 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.395324
2023-07-02 10:35:02,632 [model] Computed derived parameters: {}
2023-07-02 10:35:02,632 [mcmc] New sample, #982:
Omega_m:0.3227622, b1:0.4859507
2023-07-02 10:35:02,632 [model] Posterior to be computed for parameters {'Omega_m': 0.34085375493015724, 'b1': 0.46187149143738443}
2023-07-02 10:35:02,632 [prior] Evaluating prior at array([0.34085375, 0.46187149])
2023-07-02 10:35:02,632 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:02,632 [model] Got input parameters: {'Omega_m': 0.34085375493015724, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46187149143738443, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:02,632 [classy] Got parameters {'Omega_m': 0.34085375493015724, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:02,632 [classy] Re-using computed results
2023-07-02 10:35:02,632 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.9777765417801}
2023-07-02 10:35:02,632 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:02,633 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46187149143738443, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:02,633 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:02,652 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.586998
2023-07-02 10:35:02,652 [model] Computed derived parameters: {}
2023-07-02 10:35:02,653 [mcmc] New sample, #983:
Omega_m:0.3408538, b1:0.4529394
2023-07-02 10:35:02,653 [model] Posterior to be computed for parameters {'Omega_m': 0.367095807045219, 'b1': 0.4139881914667562}
2023-07-02 10:35:02,653 [prior] Evaluating prior at array([0.36709581, 0.41398819])
2023-07-02 10:35:02,653 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:02,653 [model] Got input parameters: {'Omega_m': 0.367095807045219, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4139881914667562, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:02,653 [classy] Got parameters {'Omega_m': 0.367095807045219, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:02,653 [classy] Computing new state
2023-07-02 10:35:02,653 [classy] Setting parameters: {'Omega_m': 0.367095807045219, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:02,699 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.1558293143217}
2023-07-02 10:35:02,699 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:02,701 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.160918
2023-07-02 10:35:02,701 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4139881914667562, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:02,701 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:02,721 [fs_likelihood.fslikelihood] Computed log-likelihood = -9.37164
2023-07-02 10:35:02,721 [model] Computed derived parameters: {}
2023-07-02 10:35:02,721 [model] Posterior to be computed for parameters {'Omega_m': 0.34085375493015724, 'b1': 0.4385645891204837}
2023-07-02 10:35:02,721 [prior] Evaluating prior at array([0.34085375, 0.43856459])
2023-07-02 10:35:02,721 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:02,721 [model] Got input parameters: {'Omega_m': 0.34085375493015724, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4385645891204837, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:02,721 [classy] Got parameters {'Omega_m': 0.34085375493015724, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:02,721 [classy] Re-using computed results
2023-07-02 10:35:02,721 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.9777765417801}
2023-07-02 10:35:02,721 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:02,721 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4385645891204837, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:02,721 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:02,741 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.00366
2023-07-02 10:35:02,741 [model] Computed derived parameters: {}
2023-07-02 10:35:02,741 [mcmc] New sample, #984:
Omega_m:0.3408538, b1:0.4618715
2023-07-02 10:35:02,741 [model] Posterior to be computed for parameters {'Omega_m': 0.2846843302929721, 'b1': 0.5410557128057475}
2023-07-02 10:35:02,741 [prior] Evaluating prior at array([0.28468433, 0.54105571])
2023-07-02 10:35:02,742 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:02,742 [model] Got input parameters: {'Omega_m': 0.2846843302929721, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5410557128057475, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:02,742 [classy] Got parameters {'Omega_m': 0.2846843302929721, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:02,742 [classy] Computing new state
2023-07-02 10:35:02,742 [classy] Setting parameters: {'Omega_m': 0.2846843302929721, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:02,788 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.74371084777152}
2023-07-02 10:35:02,788 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:02,790 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0510832
2023-07-02 10:35:02,790 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5410557128057475, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:02,790 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:02,810 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.54432
2023-07-02 10:35:02,810 [model] Computed derived parameters: {}
2023-07-02 10:35:02,810 [model] Posterior to be computed for parameters {'Omega_m': 0.34085375493015724, 'b1': 0.45410750670821226}
2023-07-02 10:35:02,810 [prior] Evaluating prior at array([0.34085375, 0.45410751])
2023-07-02 10:35:02,810 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:02,810 [model] Got input parameters: {'Omega_m': 0.34085375493015724, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45410750670821226, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:02,810 [classy] Got parameters {'Omega_m': 0.34085375493015724, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:02,810 [classy] Re-using computed results
2023-07-02 10:35:02,810 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.9777765417801}
2023-07-02 10:35:02,810 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:02,810 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45410750670821226, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:02,810 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:02,829 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.395178
2023-07-02 10:35:02,830 [model] Computed derived parameters: {}
2023-07-02 10:35:02,830 [mcmc] New sample, #985:
Omega_m:0.3408538, b1:0.4385646
2023-07-02 10:35:02,830 [model] Posterior to be computed for parameters {'Omega_m': 0.3277020835795291, 'b1': 0.47810507449125156}
2023-07-02 10:35:02,830 [prior] Evaluating prior at array([0.32770208, 0.47810507])
2023-07-02 10:35:02,830 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:02,830 [model] Got input parameters: {'Omega_m': 0.3277020835795291, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47810507449125156, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:02,830 [classy] Got parameters {'Omega_m': 0.3277020835795291, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:02,830 [classy] Computing new state
2023-07-02 10:35:02,830 [classy] Setting parameters: {'Omega_m': 0.3277020835795291, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:02,876 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.46757505437083}
2023-07-02 10:35:02,877 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:02,878 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0138833
2023-07-02 10:35:02,878 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47810507449125156, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:02,878 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:02,898 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.09039
2023-07-02 10:35:02,898 [model] Computed derived parameters: {}
2023-07-02 10:35:02,898 [mcmc] New sample, #986:
Omega_m:0.3408538, b1:0.4541075
2023-07-02 10:35:02,898 [model] Posterior to be computed for parameters {'Omega_m': 0.3277020835795291, 'b1': 0.4667542630605031}
2023-07-02 10:35:02,898 [prior] Evaluating prior at array([0.32770208, 0.46675426])
2023-07-02 10:35:02,898 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:02,898 [model] Got input parameters: {'Omega_m': 0.3277020835795291, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4667542630605031, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:02,898 [classy] Got parameters {'Omega_m': 0.3277020835795291, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:02,898 [classy] Re-using computed results
2023-07-02 10:35:02,898 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.46757505437083}
2023-07-02 10:35:02,898 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:02,898 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4667542630605031, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:02,898 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:02,918 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.7914
2023-07-02 10:35:02,918 [model] Computed derived parameters: {}
2023-07-02 10:35:02,919 [mcmc] New sample, #987:
Omega_m:0.3277021, b1:0.4781051
2023-07-02 10:35:02,919 [model] Posterior to be computed for parameters {'Omega_m': 0.35112491290267633, 'b1': 0.42401513741120384}
2023-07-02 10:35:02,919 [prior] Evaluating prior at array([0.35112491, 0.42401514])
2023-07-02 10:35:02,919 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:02,919 [model] Got input parameters: {'Omega_m': 0.35112491290267633, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42401513741120384, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:02,919 [classy] Got parameters {'Omega_m': 0.35112491290267633, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:02,919 [classy] Computing new state
2023-07-02 10:35:02,919 [classy] Setting parameters: {'Omega_m': 0.35112491290267633, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:02,966 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.85022522430765}
2023-07-02 10:35:02,966 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:02,968 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0836507
2023-07-02 10:35:02,968 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42401513741120384, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:02,968 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:02,987 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.64199
2023-07-02 10:35:02,987 [model] Computed derived parameters: {}
2023-07-02 10:35:02,987 [model] Posterior to be computed for parameters {'Omega_m': 0.3277020835795291, 'b1': 0.47743843239691075}
2023-07-02 10:35:02,987 [prior] Evaluating prior at array([0.32770208, 0.47743843])
2023-07-02 10:35:02,987 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:02,987 [model] Got input parameters: {'Omega_m': 0.3277020835795291, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47743843239691075, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:02,987 [classy] Got parameters {'Omega_m': 0.3277020835795291, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:02,987 [classy] Re-using computed results
2023-07-02 10:35:02,987 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.46757505437083}
2023-07-02 10:35:02,987 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:02,987 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47743843239691075, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:02,987 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:03,007 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.09207
2023-07-02 10:35:03,007 [model] Computed derived parameters: {}
2023-07-02 10:35:03,007 [mcmc] New sample, #988:
Omega_m:0.3277021, b1:0.4667543
2023-07-02 10:35:03,007 [model] Posterior to be computed for parameters {'Omega_m': 0.33670705802433165, 'b1': 0.4610072519893069}
2023-07-02 10:35:03,007 [prior] Evaluating prior at array([0.33670706, 0.46100725])
2023-07-02 10:35:03,008 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:03,008 [model] Got input parameters: {'Omega_m': 0.33670705802433165, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4610072519893069, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:03,008 [classy] Got parameters {'Omega_m': 0.33670705802433165, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:03,008 [classy] Computing new state
2023-07-02 10:35:03,008 [classy] Setting parameters: {'Omega_m': 0.33670705802433165, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:03,054 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.44181171040762}
2023-07-02 10:35:03,055 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:03,057 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0341233
2023-07-02 10:35:03,057 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4610072519893069, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:03,057 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:03,076 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.550712
2023-07-02 10:35:03,076 [model] Computed derived parameters: {}
2023-07-02 10:35:03,076 [model] Posterior to be computed for parameters {'Omega_m': 0.3277020835795291, 'b1': 0.48775256192960637}
2023-07-02 10:35:03,076 [prior] Evaluating prior at array([0.32770208, 0.48775256])
2023-07-02 10:35:03,076 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:03,077 [model] Got input parameters: {'Omega_m': 0.3277020835795291, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48775256192960637, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:03,077 [classy] Got parameters {'Omega_m': 0.3277020835795291, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:03,077 [classy] Re-using computed results
2023-07-02 10:35:03,077 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.46757505437083}
2023-07-02 10:35:03,077 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:03,077 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48775256192960637, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:03,077 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:03,096 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.79163
2023-07-02 10:35:03,096 [model] Computed derived parameters: {}
2023-07-02 10:35:03,096 [mcmc] New sample, #989:
Omega_m:0.3277021, b1:0.4774384
2023-07-02 10:35:03,096 [model] Posterior to be computed for parameters {'Omega_m': 0.31456368313019656, 'b1': 0.5117259145885833}
2023-07-02 10:35:03,096 [prior] Evaluating prior at array([0.31456368, 0.51172591])
2023-07-02 10:35:03,097 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:03,097 [model] Got input parameters: {'Omega_m': 0.31456368313019656, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5117259145885833, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:03,097 [classy] Got parameters {'Omega_m': 0.31456368313019656, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:03,097 [classy] Computing new state
2023-07-02 10:35:03,097 [classy] Setting parameters: {'Omega_m': 0.31456368313019656, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:03,146 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.01060811295588}
2023-07-02 10:35:03,146 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:03,148 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000466308
2023-07-02 10:35:03,148 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5117259145885833, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:03,148 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:03,168 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.61931
2023-07-02 10:35:03,168 [model] Computed derived parameters: {}
2023-07-02 10:35:03,168 [mcmc] New sample, #990:
Omega_m:0.3277021, b1:0.4877526
2023-07-02 10:35:03,168 [model] Posterior to be computed for parameters {'Omega_m': 0.31456368313019656, 'b1': 0.5281136515955757}
2023-07-02 10:35:03,168 [prior] Evaluating prior at array([0.31456368, 0.52811365])
2023-07-02 10:35:03,168 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:03,168 [model] Got input parameters: {'Omega_m': 0.31456368313019656, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5281136515955757, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:03,168 [classy] Got parameters {'Omega_m': 0.31456368313019656, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:03,168 [classy] Re-using computed results
2023-07-02 10:35:03,168 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.01060811295588}
2023-07-02 10:35:03,168 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:03,169 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5281136515955757, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:03,169 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:03,188 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.910226
2023-07-02 10:35:03,188 [model] Computed derived parameters: {}
2023-07-02 10:35:03,188 [mcmc] New sample, #991:
Omega_m:0.3145637, b1:0.5117259
2023-07-02 10:35:03,188 [model] Posterior to be computed for parameters {'Omega_m': 0.3101625911788141, 'b1': 0.5361442280604936}
2023-07-02 10:35:03,188 [prior] Evaluating prior at array([0.31016259, 0.53614423])
2023-07-02 10:35:03,188 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:03,188 [model] Got input parameters: {'Omega_m': 0.3101625911788141, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5361442280604936, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:03,188 [classy] Got parameters {'Omega_m': 0.3101625911788141, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:03,188 [classy] Computing new state
2023-07-02 10:35:03,188 [classy] Setting parameters: {'Omega_m': 0.3101625911788141, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:03,235 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.5403840185025}
2023-07-02 10:35:03,235 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:03,237 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000534768
2023-07-02 10:35:03,237 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5361442280604936, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:03,237 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:03,257 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.770154
2023-07-02 10:35:03,257 [model] Computed derived parameters: {}
2023-07-02 10:35:03,257 [mcmc] New sample, #992:
Omega_m:0.3145637, b1:0.5281137
2023-07-02 10:35:03,257 [model] Posterior to be computed for parameters {'Omega_m': 0.3101625911788141, 'b1': 0.5365392479393729}
2023-07-02 10:35:03,257 [prior] Evaluating prior at array([0.31016259, 0.53653925])
2023-07-02 10:35:03,257 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:03,257 [model] Got input parameters: {'Omega_m': 0.3101625911788141, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5365392479393729, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:03,257 [classy] Got parameters {'Omega_m': 0.3101625911788141, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:03,257 [classy] Re-using computed results
2023-07-02 10:35:03,257 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.5403840185025}
2023-07-02 10:35:03,257 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:03,257 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5365392479393729, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:03,257 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:03,278 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.710084
2023-07-02 10:35:03,278 [model] Computed derived parameters: {}
2023-07-02 10:35:03,278 [model] Posterior to be computed for parameters {'Omega_m': 0.3076013212864909, 'b1': 0.5408177213537051}
2023-07-02 10:35:03,278 [prior] Evaluating prior at array([0.30760132, 0.54081772])
2023-07-02 10:35:03,278 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:03,278 [model] Got input parameters: {'Omega_m': 0.3076013212864909, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5408177213537051, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:03,278 [classy] Got parameters {'Omega_m': 0.3076013212864909, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:03,278 [classy] Computing new state
2023-07-02 10:35:03,278 [classy] Setting parameters: {'Omega_m': 0.3076013212864909, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:03,324 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.85175933230164}
2023-07-02 10:35:03,324 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:03,326 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00168236
2023-07-02 10:35:03,326 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5408177213537051, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:03,326 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:03,345 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.582909
2023-07-02 10:35:03,345 [model] Computed derived parameters: {}
2023-07-02 10:35:03,346 [mcmc] New sample, #993:
Omega_m:0.3101626, b1:0.5361442
2023-07-02 10:35:03,346 [model] Posterior to be computed for parameters {'Omega_m': 0.3076013212864909, 'b1': 0.5497473454981044}
2023-07-02 10:35:03,346 [prior] Evaluating prior at array([0.30760132, 0.54974735])
2023-07-02 10:35:03,346 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:03,346 [model] Got input parameters: {'Omega_m': 0.3076013212864909, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5497473454981044, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:03,346 [classy] Got parameters {'Omega_m': 0.3076013212864909, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:03,346 [classy] Re-using computed results
2023-07-02 10:35:03,346 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.85175933230164}
2023-07-02 10:35:03,346 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:03,346 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5497473454981044, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:03,346 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:03,366 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.995334
2023-07-02 10:35:03,366 [model] Computed derived parameters: {}
2023-07-02 10:35:03,366 [model] Posterior to be computed for parameters {'Omega_m': 0.24893763972576813, 'b1': 0.6478600612300617}
2023-07-02 10:35:03,366 [prior] Evaluating prior at array([0.24893764, 0.64786006])
2023-07-02 10:35:03,366 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:03,366 [model] Got input parameters: {'Omega_m': 0.24893763972576813, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6478600612300617, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:03,366 [classy] Got parameters {'Omega_m': 0.24893763972576813, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:03,366 [classy] Computing new state
2023-07-02 10:35:03,366 [classy] Setting parameters: {'Omega_m': 0.24893763972576813, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:03,413 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 155.6801957274664}
2023-07-02 10:35:03,413 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:03,415 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.293336
2023-07-02 10:35:03,415 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6478600612300617, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:03,415 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:03,434 [fs_likelihood.fslikelihood] Computed log-likelihood = -31.7179
2023-07-02 10:35:03,434 [model] Computed derived parameters: {}
2023-07-02 10:35:03,434 [model] Posterior to be computed for parameters {'Omega_m': 0.3076013212864909, 'b1': 0.5780279312929958}
2023-07-02 10:35:03,435 [prior] Evaluating prior at array([0.30760132, 0.57802793])
2023-07-02 10:35:03,435 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:03,435 [model] Got input parameters: {'Omega_m': 0.3076013212864909, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5780279312929958, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:03,435 [classy] Got parameters {'Omega_m': 0.3076013212864909, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:03,435 [classy] Re-using computed results
2023-07-02 10:35:03,435 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.85175933230164}
2023-07-02 10:35:03,435 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:03,435 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5780279312929958, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:03,435 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:03,455 [fs_likelihood.fslikelihood] Computed log-likelihood = -9.17917
2023-07-02 10:35:03,455 [model] Computed derived parameters: {}
2023-07-02 10:35:03,455 [model] Posterior to be computed for parameters {'Omega_m': 0.3077178453565464, 'b1': 0.5406051024252845}
2023-07-02 10:35:03,455 [prior] Evaluating prior at array([0.30771785, 0.5406051 ])
2023-07-02 10:35:03,455 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:03,455 [model] Got input parameters: {'Omega_m': 0.3077178453565464, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5406051024252845, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:03,455 [classy] Got parameters {'Omega_m': 0.3077178453565464, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:03,455 [classy] Computing new state
2023-07-02 10:35:03,455 [classy] Setting parameters: {'Omega_m': 0.3077178453565464, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:03,501 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.83754230007477}
2023-07-02 10:35:03,501 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:03,503 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00161214
2023-07-02 10:35:03,503 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5406051024252845, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:03,503 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:03,523 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.593166
2023-07-02 10:35:03,523 [model] Computed derived parameters: {}
2023-07-02 10:35:03,523 [mcmc] New sample, #994:
Omega_m:0.3076013, b1:0.5408177
2023-07-02 10:35:03,523 [model] Posterior to be computed for parameters {'Omega_m': 0.3077178453565464, 'b1': 0.5239924924041647}
2023-07-02 10:35:03,523 [prior] Evaluating prior at array([0.30771785, 0.52399249])
2023-07-02 10:35:03,524 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:03,524 [model] Got input parameters: {'Omega_m': 0.3077178453565464, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5239924924041647, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:03,524 [classy] Got parameters {'Omega_m': 0.3077178453565464, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:03,524 [classy] Re-using computed results
2023-07-02 10:35:03,524 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.83754230007477}
2023-07-02 10:35:03,524 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:03,524 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5239924924041647, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:03,524 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:03,543 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.30895
2023-07-02 10:35:03,543 [model] Computed derived parameters: {}
2023-07-02 10:35:03,543 [mcmc] New sample, #995:
Omega_m:0.3077178, b1:0.5406051
2023-07-02 10:35:03,543 [model] Posterior to be computed for parameters {'Omega_m': 0.31082827039579414, 'b1': 0.518316967695296}
2023-07-02 10:35:03,543 [prior] Evaluating prior at array([0.31082827, 0.51831697])
2023-07-02 10:35:03,544 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:03,544 [model] Got input parameters: {'Omega_m': 0.31082827039579414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.518316967695296, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:03,544 [classy] Got parameters {'Omega_m': 0.31082827039579414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:03,544 [classy] Computing new state
2023-07-02 10:35:03,544 [classy] Setting parameters: {'Omega_m': 0.31082827039579414, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:03,590 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.45983092191528}
2023-07-02 10:35:03,590 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:03,592 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000371185
2023-07-02 10:35:03,592 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.518316967695296, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:03,592 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:03,611 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.5246
2023-07-02 10:35:03,611 [model] Computed derived parameters: {}
2023-07-02 10:35:03,611 [mcmc] New sample, #996:
Omega_m:0.3077178, b1:0.5239925
2023-07-02 10:35:03,612 [model] Posterior to be computed for parameters {'Omega_m': 0.31082827039579414, 'b1': 0.5119271911587223}
2023-07-02 10:35:03,612 [prior] Evaluating prior at array([0.31082827, 0.51192719])
2023-07-02 10:35:03,612 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:03,612 [model] Got input parameters: {'Omega_m': 0.31082827039579414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5119271911587223, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:03,612 [classy] Got parameters {'Omega_m': 0.31082827039579414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:03,612 [classy] Re-using computed results
2023-07-02 10:35:03,612 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.45983092191528}
2023-07-02 10:35:03,612 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:03,612 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5119271911587223, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:03,612 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:03,632 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.77448
2023-07-02 10:35:03,632 [model] Computed derived parameters: {}
2023-07-02 10:35:03,632 [mcmc] New sample, #997:
Omega_m:0.3108283, b1:0.518317
2023-07-02 10:35:03,632 [model] Posterior to be computed for parameters {'Omega_m': 0.28588954734311267, 'b1': 0.5574323350239988}
2023-07-02 10:35:03,632 [prior] Evaluating prior at array([0.28588955, 0.55743234])
2023-07-02 10:35:03,632 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:03,632 [model] Got input parameters: {'Omega_m': 0.28588954734311267, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5574323350239988, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:03,632 [classy] Got parameters {'Omega_m': 0.28588954734311267, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:03,632 [classy] Computing new state
2023-07-02 10:35:03,632 [classy] Setting parameters: {'Omega_m': 0.28588954734311267, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:03,679 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.58665502891463}
2023-07-02 10:35:03,679 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:03,681 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0466194
2023-07-02 10:35:03,681 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5574323350239988, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:03,681 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:03,700 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.58025
2023-07-02 10:35:03,701 [model] Computed derived parameters: {}
2023-07-02 10:35:03,701 [model] Posterior to be computed for parameters {'Omega_m': 0.31082827039579414, 'b1': 0.4796578899091886}
2023-07-02 10:35:03,701 [prior] Evaluating prior at array([0.31082827, 0.47965789])
2023-07-02 10:35:03,701 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:03,701 [model] Got input parameters: {'Omega_m': 0.31082827039579414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4796578899091886, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:03,701 [classy] Got parameters {'Omega_m': 0.31082827039579414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:03,701 [classy] Re-using computed results
2023-07-02 10:35:03,701 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.45983092191528}
2023-07-02 10:35:03,701 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:03,701 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4796578899091886, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:03,701 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:03,721 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.732556
2023-07-02 10:35:03,721 [model] Computed derived parameters: {}
2023-07-02 10:35:03,721 [model] Posterior to be computed for parameters {'Omega_m': 0.3413536603187373, 'b1': 0.4562281781397764}
2023-07-02 10:35:03,722 [prior] Evaluating prior at array([0.34135366, 0.45622818])
2023-07-02 10:35:03,722 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:03,722 [model] Got input parameters: {'Omega_m': 0.3413536603187373, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4562281781397764, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:03,722 [classy] Got parameters {'Omega_m': 0.3413536603187373, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:03,722 [classy] Computing new state
2023-07-02 10:35:03,722 [classy] Setting parameters: {'Omega_m': 0.3413536603187373, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:03,768 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.9221811814771}
2023-07-02 10:35:03,769 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:03,770 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0478592
2023-07-02 10:35:03,770 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4562281781397764, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:03,770 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:03,790 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.553151
2023-07-02 10:35:03,790 [model] Computed derived parameters: {}
2023-07-02 10:35:03,790 [model] Posterior to be computed for parameters {'Omega_m': 0.31082827039579414, 'b1': 0.5147991718995647}
2023-07-02 10:35:03,790 [prior] Evaluating prior at array([0.31082827, 0.51479917])
2023-07-02 10:35:03,790 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:03,790 [model] Got input parameters: {'Omega_m': 0.31082827039579414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5147991718995647, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:03,790 [classy] Got parameters {'Omega_m': 0.31082827039579414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:03,790 [classy] Re-using computed results
2023-07-02 10:35:03,790 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.45983092191528}
2023-07-02 10:35:03,790 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:03,790 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5147991718995647, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:03,790 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:03,810 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.68988
2023-07-02 10:35:03,810 [model] Computed derived parameters: {}
2023-07-02 10:35:03,810 [model] Posterior to be computed for parameters {'Omega_m': 0.29489076528820196, 'b1': 0.541008009019466}
2023-07-02 10:35:03,810 [prior] Evaluating prior at array([0.29489077, 0.54100801])
2023-07-02 10:35:03,810 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:03,810 [model] Got input parameters: {'Omega_m': 0.29489076528820196, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.541008009019466, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:03,810 [classy] Got parameters {'Omega_m': 0.29489076528820196, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:03,810 [classy] Computing new state
2023-07-02 10:35:03,810 [classy] Setting parameters: {'Omega_m': 0.29489076528820196, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:03,857 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.43156561611605}
2023-07-02 10:35:03,857 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:03,859 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.020047
2023-07-02 10:35:03,859 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.541008009019466, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:03,859 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:03,879 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.357507
2023-07-02 10:35:03,879 [model] Computed derived parameters: {}
2023-07-02 10:35:03,880 [model] Posterior to be computed for parameters {'Omega_m': 0.31082827039579414, 'b1': 0.4368721328544044}
2023-07-02 10:35:03,880 [prior] Evaluating prior at array([0.31082827, 0.43687213])
2023-07-02 10:35:03,880 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:03,880 [model] Got input parameters: {'Omega_m': 0.31082827039579414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4368721328544044, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:03,880 [classy] Got parameters {'Omega_m': 0.31082827039579414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:03,880 [classy] Re-using computed results
2023-07-02 10:35:03,880 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.45983092191528}
2023-07-02 10:35:03,880 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:03,880 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4368721328544044, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:03,880 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:03,899 [fs_likelihood.fslikelihood] Computed log-likelihood = -9.7971
2023-07-02 10:35:03,899 [model] Computed derived parameters: {}
2023-07-02 10:35:03,899 [model] Posterior to be computed for parameters {'Omega_m': 0.3440624305046478, 'b1': 0.4512855442788749}
2023-07-02 10:35:03,899 [prior] Evaluating prior at array([0.34406243, 0.45128554])
2023-07-02 10:35:03,899 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:03,899 [model] Got input parameters: {'Omega_m': 0.3440624305046478, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4512855442788749, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:03,900 [classy] Got parameters {'Omega_m': 0.3440624305046478, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:03,900 [classy] Computing new state
2023-07-02 10:35:03,900 [classy] Setting parameters: {'Omega_m': 0.3440624305046478, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:03,946 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.6222139155358}
2023-07-02 10:35:03,946 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:03,948 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.056861
2023-07-02 10:35:03,948 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4512855442788749, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:03,948 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:03,967 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.25399
2023-07-02 10:35:03,967 [model] Computed derived parameters: {}
2023-07-02 10:35:03,967 [model] Posterior to be computed for parameters {'Omega_m': 0.31082827039579414, 'b1': 0.4853467433505858}
2023-07-02 10:35:03,967 [prior] Evaluating prior at array([0.31082827, 0.48534674])
2023-07-02 10:35:03,968 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:03,968 [model] Got input parameters: {'Omega_m': 0.31082827039579414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4853467433505858, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:03,968 [classy] Got parameters {'Omega_m': 0.31082827039579414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:03,968 [classy] Re-using computed results
2023-07-02 10:35:03,968 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.45983092191528}
2023-07-02 10:35:03,968 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:03,968 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4853467433505858, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:03,968 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:03,987 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.47977
2023-07-02 10:35:03,988 [model] Computed derived parameters: {}
2023-07-02 10:35:03,988 [model] Posterior to be computed for parameters {'Omega_m': 0.3022977632282667, 'b1': 0.5274926214769506}
2023-07-02 10:35:03,988 [prior] Evaluating prior at array([0.30229776, 0.52749262])
2023-07-02 10:35:03,988 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:03,988 [model] Got input parameters: {'Omega_m': 0.3022977632282667, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5274926214769506, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:03,988 [classy] Got parameters {'Omega_m': 0.3022977632282667, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:03,988 [classy] Computing new state
2023-07-02 10:35:03,988 [classy] Setting parameters: {'Omega_m': 0.3022977632282667, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:04,034 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.50382617666912}
2023-07-02 10:35:04,034 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:04,036 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00672978
2023-07-02 10:35:04,036 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5274926214769506, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:04,036 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:04,056 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.89543
2023-07-02 10:35:04,056 [model] Computed derived parameters: {}
2023-07-02 10:35:04,056 [model] Posterior to be computed for parameters {'Omega_m': 0.31082827039579414, 'b1': 0.523169870564672}
2023-07-02 10:35:04,056 [prior] Evaluating prior at array([0.31082827, 0.52316987])
2023-07-02 10:35:04,056 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:04,056 [model] Got input parameters: {'Omega_m': 0.31082827039579414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.523169870564672, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:04,056 [classy] Got parameters {'Omega_m': 0.31082827039579414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:04,056 [classy] Re-using computed results
2023-07-02 10:35:04,056 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.45983092191528}
2023-07-02 10:35:04,056 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:04,056 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.523169870564672, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:04,056 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:04,076 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.18394
2023-07-02 10:35:04,076 [model] Computed derived parameters: {}
2023-07-02 10:35:04,076 [mcmc] New sample, #998:
Omega_m:0.3108283, b1:0.5119272
2023-07-02 10:35:04,076 [model] Posterior to be computed for parameters {'Omega_m': 0.2773582852648978, 'b1': 0.5842418222172383}
2023-07-02 10:35:04,076 [prior] Evaluating prior at array([0.27735829, 0.58424182])
2023-07-02 10:35:04,076 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:04,076 [model] Got input parameters: {'Omega_m': 0.2773582852648978, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5842418222172383, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:04,077 [classy] Got parameters {'Omega_m': 0.2773582852648978, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:04,077 [classy] Computing new state
2023-07-02 10:35:04,077 [classy] Setting parameters: {'Omega_m': 0.2773582852648978, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:04,125 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.71083648073787}
2023-07-02 10:35:04,125 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:04,128 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0830274
2023-07-02 10:35:04,128 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5842418222172383, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:04,128 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:04,155 [fs_likelihood.fslikelihood] Computed log-likelihood = -7.14995
2023-07-02 10:35:04,155 [model] Computed derived parameters: {}
2023-07-02 10:35:04,155 [model] Posterior to be computed for parameters {'Omega_m': 0.31082827039579414, 'b1': 0.5571576484082378}
2023-07-02 10:35:04,155 [prior] Evaluating prior at array([0.31082827, 0.55715765])
2023-07-02 10:35:04,155 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:04,155 [model] Got input parameters: {'Omega_m': 0.31082827039579414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5571576484082378, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:04,155 [classy] Got parameters {'Omega_m': 0.31082827039579414, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:04,155 [classy] Re-using computed results
2023-07-02 10:35:04,155 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.45983092191528}
2023-07-02 10:35:04,156 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:04,156 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5571576484082378, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:04,156 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:04,176 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.01744
2023-07-02 10:35:04,176 [model] Computed derived parameters: {}
2023-07-02 10:35:04,176 [model] Posterior to be computed for parameters {'Omega_m': 0.3215494132819417, 'b1': 0.5036072350438499}
2023-07-02 10:35:04,176 [prior] Evaluating prior at array([0.32154941, 0.50360724])
2023-07-02 10:35:04,176 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:04,176 [model] Got input parameters: {'Omega_m': 0.3215494132819417, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5036072350438499, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:04,176 [classy] Got parameters {'Omega_m': 0.3215494132819417, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:04,176 [classy] Computing new state
2023-07-02 10:35:04,176 [classy] Setting parameters: {'Omega_m': 0.3215494132819417, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:04,223 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.18316640592158}
2023-07-02 10:35:04,223 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:04,225 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00512997
2023-07-02 10:35:04,225 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5036072350438499, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:04,225 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:04,244 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.07382
2023-07-02 10:35:04,244 [model] Computed derived parameters: {}
2023-07-02 10:35:04,245 [mcmc] New sample, #999:
Omega_m:0.3108283, b1:0.5231699
2023-07-02 10:35:04,245 [model] Posterior to be computed for parameters {'Omega_m': 0.3215494132819417, 'b1': 0.47818708822531564}
2023-07-02 10:35:04,245 [prior] Evaluating prior at array([0.32154941, 0.47818709])
2023-07-02 10:35:04,245 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:04,245 [model] Got input parameters: {'Omega_m': 0.3215494132819417, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47818708822531564, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:04,245 [classy] Got parameters {'Omega_m': 0.3215494132819417, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:04,245 [classy] Re-using computed results
2023-07-02 10:35:04,245 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.18316640592158}
2023-07-02 10:35:04,245 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:04,245 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47818708822531564, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:04,245 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:04,264 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.42205
2023-07-02 10:35:04,265 [model] Computed derived parameters: {}
2023-07-02 10:35:04,265 [mcmc] New sample, #1000:
Omega_m:0.3215494, b1:0.5036072
2023-07-02 10:35:04,265 [model] Posterior to be computed for parameters {'Omega_m': 0.3141222159702808, 'b1': 0.49173933312049223}
2023-07-02 10:35:04,265 [prior] Evaluating prior at array([0.31412222, 0.49173933])
2023-07-02 10:35:04,265 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:04,265 [model] Got input parameters: {'Omega_m': 0.3141222159702808, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49173933312049223, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:04,265 [classy] Got parameters {'Omega_m': 0.3141222159702808, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:04,265 [classy] Computing new state
2023-07-02 10:35:04,265 [classy] Setting parameters: {'Omega_m': 0.3141222159702808, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:04,311 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.06344849549885}
2023-07-02 10:35:04,312 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:04,313 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00036635
2023-07-02 10:35:04,314 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49173933312049223, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:04,314 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:04,334 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.64274
2023-07-02 10:35:04,334 [model] Computed derived parameters: {}
2023-07-02 10:35:04,334 [mcmc] New sample, #1001:
Omega_m:0.3215494, b1:0.4781871
2023-07-02 10:35:04,334 [model] Posterior to be computed for parameters {'Omega_m': 0.3141222159702808, 'b1': 0.49338388832287833}
2023-07-02 10:35:04,334 [prior] Evaluating prior at array([0.31412222, 0.49338389])
2023-07-02 10:35:04,334 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:04,334 [model] Got input parameters: {'Omega_m': 0.3141222159702808, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49338388832287833, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:04,334 [classy] Got parameters {'Omega_m': 0.3141222159702808, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:04,335 [classy] Re-using computed results
2023-07-02 10:35:04,335 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.06344849549885}
2023-07-02 10:35:04,335 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:04,335 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49338388832287833, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:04,335 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:04,354 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.72468
2023-07-02 10:35:04,354 [model] Computed derived parameters: {}
2023-07-02 10:35:04,354 [mcmc] New sample, #1002:
Omega_m:0.3141222, b1:0.4917393
2023-07-02 10:35:04,354 [model] Posterior to be computed for parameters {'Omega_m': 0.3010405833900486, 'b1': 0.5172536578896144}
2023-07-02 10:35:04,354 [prior] Evaluating prior at array([0.30104058, 0.51725366])
2023-07-02 10:35:04,354 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:04,355 [model] Got input parameters: {'Omega_m': 0.3010405833900486, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5172536578896144, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:04,355 [classy] Got parameters {'Omega_m': 0.3010405833900486, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:04,355 [classy] Computing new state
2023-07-02 10:35:04,355 [classy] Setting parameters: {'Omega_m': 0.3010405833900486, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:04,401 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.65986318959216}
2023-07-02 10:35:04,401 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:04,403 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00846654
2023-07-02 10:35:04,403 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5172536578896144, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:04,403 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:04,422 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.54384
2023-07-02 10:35:04,422 [model] Computed derived parameters: {}
2023-07-02 10:35:04,423 [model] Posterior to be computed for parameters {'Omega_m': 0.3141222159702808, 'b1': 0.5694340122727565}
2023-07-02 10:35:04,423 [prior] Evaluating prior at array([0.31412222, 0.56943401])
2023-07-02 10:35:04,423 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:04,423 [model] Got input parameters: {'Omega_m': 0.3141222159702808, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5694340122727565, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:04,423 [classy] Got parameters {'Omega_m': 0.3141222159702808, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:04,423 [classy] Re-using computed results
2023-07-02 10:35:04,423 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.06344849549885}
2023-07-02 10:35:04,423 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:04,423 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5694340122727565, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:04,423 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:04,443 [fs_likelihood.fslikelihood] Computed log-likelihood = -10.2007
2023-07-02 10:35:04,443 [model] Computed derived parameters: {}
2023-07-02 10:35:04,443 [model] Posterior to be computed for parameters {'Omega_m': 0.25930471155066126, 'b1': 0.5934081926820386}
2023-07-02 10:35:04,443 [prior] Evaluating prior at array([0.25930471, 0.59340819])
2023-07-02 10:35:04,444 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:04,444 [model] Got input parameters: {'Omega_m': 0.25930471155066126, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5934081926820386, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:04,444 [classy] Got parameters {'Omega_m': 0.25930471155066126, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:04,444 [classy] Computing new state
2023-07-02 10:35:04,444 [classy] Setting parameters: {'Omega_m': 0.25930471155066126, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:04,490 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 154.19022817291906}
2023-07-02 10:35:04,491 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:04,492 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.199603
2023-07-02 10:35:04,492 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5934081926820386, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:04,492 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:04,512 [fs_likelihood.fslikelihood] Computed log-likelihood = -19.3826
2023-07-02 10:35:04,512 [model] Computed derived parameters: {}
2023-07-02 10:35:04,512 [model] Posterior to be computed for parameters {'Omega_m': 0.3141222159702808, 'b1': 0.5547022422761454}
2023-07-02 10:35:04,512 [prior] Evaluating prior at array([0.31412222, 0.55470224])
2023-07-02 10:35:04,512 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:04,512 [model] Got input parameters: {'Omega_m': 0.3141222159702808, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5547022422761454, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:04,512 [classy] Got parameters {'Omega_m': 0.3141222159702808, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:04,512 [classy] Re-using computed results
2023-07-02 10:35:04,512 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.06344849549885}
2023-07-02 10:35:04,512 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:04,513 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5547022422761454, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:04,513 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:04,533 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.98243
2023-07-02 10:35:04,533 [model] Computed derived parameters: {}
2023-07-02 10:35:04,533 [model] Posterior to be computed for parameters {'Omega_m': 0.2658269187344302, 'b1': 0.5815072635290267}
2023-07-02 10:35:04,533 [prior] Evaluating prior at array([0.26582692, 0.58150726])
2023-07-02 10:35:04,533 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:04,533 [model] Got input parameters: {'Omega_m': 0.2658269187344302, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5815072635290267, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:04,533 [classy] Got parameters {'Omega_m': 0.2658269187344302, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:04,533 [classy] Computing new state
2023-07-02 10:35:04,533 [classy] Setting parameters: {'Omega_m': 0.2658269187344302, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:04,580 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 153.27817366360225}
2023-07-02 10:35:04,580 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:04,582 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.15096
2023-07-02 10:35:04,582 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5815072635290267, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:04,582 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:04,602 [fs_likelihood.fslikelihood] Computed log-likelihood = -14.0625
2023-07-02 10:35:04,602 [model] Computed derived parameters: {}
2023-07-02 10:35:04,602 [model] Posterior to be computed for parameters {'Omega_m': 0.3141222159702808, 'b1': 0.4904875004253085}
2023-07-02 10:35:04,602 [prior] Evaluating prior at array([0.31412222, 0.4904875 ])
2023-07-02 10:35:04,603 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:04,603 [model] Got input parameters: {'Omega_m': 0.3141222159702808, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4904875004253085, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:04,603 [classy] Got parameters {'Omega_m': 0.3141222159702808, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:04,603 [classy] Re-using computed results
2023-07-02 10:35:04,603 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.06344849549885}
2023-07-02 10:35:04,603 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:04,603 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4904875004253085, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:04,603 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:04,622 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.57089
2023-07-02 10:35:04,622 [model] Computed derived parameters: {}
2023-07-02 10:35:04,622 [mcmc] New sample, #1003:
Omega_m:0.3141222, b1:0.4933839
2023-07-02 10:35:04,623 [model] Posterior to be computed for parameters {'Omega_m': 0.3186001496824632, 'b1': 0.48231671247591823}
2023-07-02 10:35:04,623 [prior] Evaluating prior at array([0.31860015, 0.48231671])
2023-07-02 10:35:04,623 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:04,623 [model] Got input parameters: {'Omega_m': 0.3186001496824632, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48231671247591823, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:04,623 [classy] Got parameters {'Omega_m': 0.3186001496824632, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:04,623 [classy] Computing new state
2023-07-02 10:35:04,623 [classy] Setting parameters: {'Omega_m': 0.3186001496824632, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:04,671 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.53052690318833}
2023-07-02 10:35:04,671 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:04,673 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00246162
2023-07-02 10:35:04,673 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48231671247591823, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:04,673 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:04,694 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.50892
2023-07-02 10:35:04,694 [model] Computed derived parameters: {}
2023-07-02 10:35:04,694 [mcmc] New sample, #1004:
Omega_m:0.3141222, b1:0.4904875
2023-07-02 10:35:04,694 [model] Posterior to be computed for parameters {'Omega_m': 0.3186001496824632, 'b1': 0.4625306730208523}
2023-07-02 10:35:04,694 [prior] Evaluating prior at array([0.31860015, 0.46253067])
2023-07-02 10:35:04,694 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:04,694 [model] Got input parameters: {'Omega_m': 0.3186001496824632, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4625306730208523, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:04,694 [classy] Got parameters {'Omega_m': 0.3186001496824632, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:04,694 [classy] Re-using computed results
2023-07-02 10:35:04,694 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.53052690318833}
2023-07-02 10:35:04,694 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:04,694 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4625306730208523, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:04,694 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:04,714 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.297425
2023-07-02 10:35:04,714 [model] Computed derived parameters: {}
2023-07-02 10:35:04,714 [model] Posterior to be computed for parameters {'Omega_m': 0.3357149786952634, 'b1': 0.45108765737105627}
2023-07-02 10:35:04,714 [prior] Evaluating prior at array([0.33571498, 0.45108766])
2023-07-02 10:35:04,714 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:04,714 [model] Got input parameters: {'Omega_m': 0.3357149786952634, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45108765737105627, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:04,714 [classy] Got parameters {'Omega_m': 0.3357149786952634, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:04,714 [classy] Computing new state
2023-07-02 10:35:04,714 [classy] Setting parameters: {'Omega_m': 0.3357149786952634, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:04,762 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.55359667338078}
2023-07-02 10:35:04,762 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:04,764 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0314754
2023-07-02 10:35:04,764 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45108765737105627, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:04,764 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:04,784 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.382344
2023-07-02 10:35:04,784 [model] Computed derived parameters: {}
2023-07-02 10:35:04,784 [model] Posterior to be computed for parameters {'Omega_m': 0.3186001496824632, 'b1': 0.46515693322959323}
2023-07-02 10:35:04,784 [prior] Evaluating prior at array([0.31860015, 0.46515693])
2023-07-02 10:35:04,784 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:04,784 [model] Got input parameters: {'Omega_m': 0.3186001496824632, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46515693322959323, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:04,784 [classy] Got parameters {'Omega_m': 0.3186001496824632, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:04,784 [classy] Re-using computed results
2023-07-02 10:35:04,784 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.53052690318833}
2023-07-02 10:35:04,784 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:04,784 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46515693322959323, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:04,784 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:04,804 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.70427
2023-07-02 10:35:04,804 [model] Computed derived parameters: {}
2023-07-02 10:35:04,804 [model] Posterior to be computed for parameters {'Omega_m': 0.31283210097420755, 'b1': 0.49284154511216155}
2023-07-02 10:35:04,804 [prior] Evaluating prior at array([0.3128321 , 0.49284155])
2023-07-02 10:35:04,804 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:04,804 [model] Got input parameters: {'Omega_m': 0.31283210097420755, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49284154511216155, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:04,804 [classy] Got parameters {'Omega_m': 0.31283210097420755, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:04,804 [classy] Computing new state
2023-07-02 10:35:04,804 [classy] Setting parameters: {'Omega_m': 0.31283210097420755, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:04,853 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.21825539093967}
2023-07-02 10:35:04,853 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:04,855 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000209809
2023-07-02 10:35:04,855 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49284154511216155, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:04,855 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:04,874 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.54686
2023-07-02 10:35:04,874 [model] Computed derived parameters: {}
2023-07-02 10:35:04,874 [mcmc] New sample, #1005:
Omega_m:0.3186001, b1:0.4823167
2023-07-02 10:35:04,875 [model] Posterior to be computed for parameters {'Omega_m': 0.31283210097420755, 'b1': 0.49567106674399247}
2023-07-02 10:35:04,875 [prior] Evaluating prior at array([0.3128321 , 0.49567107])
2023-07-02 10:35:04,875 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:04,875 [model] Got input parameters: {'Omega_m': 0.31283210097420755, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49567106674399247, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:04,875 [classy] Got parameters {'Omega_m': 0.31283210097420755, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:04,875 [classy] Re-using computed results
2023-07-02 10:35:04,875 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.21825539093967}
2023-07-02 10:35:04,875 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:04,875 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49567106674399247, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:04,875 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:04,895 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.69724
2023-07-02 10:35:04,895 [model] Computed derived parameters: {}
2023-07-02 10:35:04,895 [mcmc] New sample, #1006:
Omega_m:0.3128321, b1:0.4928415
2023-07-02 10:35:04,895 [model] Posterior to be computed for parameters {'Omega_m': 0.31943592496555234, 'b1': 0.4836212131828336}
2023-07-02 10:35:04,895 [prior] Evaluating prior at array([0.31943592, 0.48362121])
2023-07-02 10:35:04,895 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:04,896 [model] Got input parameters: {'Omega_m': 0.31943592496555234, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4836212131828336, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:04,896 [classy] Got parameters {'Omega_m': 0.31943592496555234, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:04,896 [classy] Computing new state
2023-07-02 10:35:04,896 [classy] Setting parameters: {'Omega_m': 0.31943592496555234, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:04,942 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.4318005028592}
2023-07-02 10:35:04,942 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:04,944 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00311524
2023-07-02 10:35:04,944 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4836212131828336, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:04,944 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:04,963 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.62527
2023-07-02 10:35:04,963 [model] Computed derived parameters: {}
2023-07-02 10:35:04,963 [mcmc] New sample, #1007:
Omega_m:0.3128321, b1:0.4956711
2023-07-02 10:35:04,963 [model] Posterior to be computed for parameters {'Omega_m': 0.31943592496555234, 'b1': 0.5158522859490702}
2023-07-02 10:35:04,964 [prior] Evaluating prior at array([0.31943592, 0.51585229])
2023-07-02 10:35:04,964 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:04,964 [model] Got input parameters: {'Omega_m': 0.31943592496555234, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5158522859490702, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:04,964 [classy] Got parameters {'Omega_m': 0.31943592496555234, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:04,964 [classy] Re-using computed results
2023-07-02 10:35:04,964 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.4318005028592}
2023-07-02 10:35:04,964 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:04,964 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5158522859490702, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:04,964 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:04,984 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.2892
2023-07-02 10:35:04,984 [model] Computed derived parameters: {}
2023-07-02 10:35:04,984 [model] Posterior to be computed for parameters {'Omega_m': 0.2810559809136331, 'b1': 0.553652259757853}
2023-07-02 10:35:04,984 [prior] Evaluating prior at array([0.28105598, 0.55365226])
2023-07-02 10:35:04,984 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:04,984 [model] Got input parameters: {'Omega_m': 0.2810559809136331, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.553652259757853, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:04,984 [classy] Got parameters {'Omega_m': 0.2810559809136331, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:04,984 [classy] Computing new state
2023-07-02 10:35:04,984 [classy] Setting parameters: {'Omega_m': 0.2810559809136331, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:05,030 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.22000155237208}
2023-07-02 10:35:05,030 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:05,032 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0658585
2023-07-02 10:35:05,032 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.553652259757853, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:05,032 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:05,052 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.80674
2023-07-02 10:35:05,053 [model] Computed derived parameters: {}
2023-07-02 10:35:05,053 [model] Posterior to be computed for parameters {'Omega_m': 0.31943592496555234, 'b1': 0.527157235678055}
2023-07-02 10:35:05,053 [prior] Evaluating prior at array([0.31943592, 0.52715724])
2023-07-02 10:35:05,053 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:05,053 [model] Got input parameters: {'Omega_m': 0.31943592496555234, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.527157235678055, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:05,053 [classy] Got parameters {'Omega_m': 0.31943592496555234, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:05,053 [classy] Re-using computed results
2023-07-02 10:35:05,053 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.4318005028592}
2023-07-02 10:35:05,053 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:05,053 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.527157235678055, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:05,053 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:05,072 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.579564
2023-07-02 10:35:05,073 [model] Computed derived parameters: {}
2023-07-02 10:35:05,073 [model] Posterior to be computed for parameters {'Omega_m': 0.28769412846101794, 'b1': 0.541539776752826}
2023-07-02 10:35:05,073 [prior] Evaluating prior at array([0.28769413, 0.54153978])
2023-07-02 10:35:05,073 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:05,073 [model] Got input parameters: {'Omega_m': 0.28769412846101794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.541539776752826, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:05,073 [classy] Got parameters {'Omega_m': 0.28769412846101794, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:05,073 [classy] Computing new state
2023-07-02 10:35:05,073 [classy] Setting parameters: {'Omega_m': 0.28769412846101794, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:05,119 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.35258196336758}
2023-07-02 10:35:05,120 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:05,123 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.040344
2023-07-02 10:35:05,123 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.541539776752826, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:05,123 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:05,151 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.02545
2023-07-02 10:35:05,151 [model] Computed derived parameters: {}
2023-07-02 10:35:05,151 [model] Posterior to be computed for parameters {'Omega_m': 0.31943592496555234, 'b1': 0.45740156160562223}
2023-07-02 10:35:05,151 [prior] Evaluating prior at array([0.31943592, 0.45740156])
2023-07-02 10:35:05,151 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:05,151 [model] Got input parameters: {'Omega_m': 0.31943592496555234, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45740156160562223, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:05,151 [classy] Got parameters {'Omega_m': 0.31943592496555234, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:05,151 [classy] Re-using computed results
2023-07-02 10:35:05,152 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.4318005028592}
2023-07-02 10:35:05,152 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:05,152 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45740156160562223, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:05,152 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:05,171 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.354989
2023-07-02 10:35:05,171 [model] Computed derived parameters: {}
2023-07-02 10:35:05,171 [model] Posterior to be computed for parameters {'Omega_m': 0.3296361182228213, 'b1': 0.4650091430842509}
2023-07-02 10:35:05,171 [prior] Evaluating prior at array([0.32963612, 0.46500914])
2023-07-02 10:35:05,171 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:05,171 [model] Got input parameters: {'Omega_m': 0.3296361182228213, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4650091430842509, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:05,171 [classy] Got parameters {'Omega_m': 0.3296361182228213, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:05,171 [classy] Computing new state
2023-07-02 10:35:05,171 [classy] Setting parameters: {'Omega_m': 0.3296361182228213, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:05,218 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.2451206559734}
2023-07-02 10:35:05,218 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:05,220 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0175014
2023-07-02 10:35:05,220 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4650091430842509, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:05,220 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:05,240 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.61351
2023-07-02 10:35:05,240 [model] Computed derived parameters: {}
2023-07-02 10:35:05,240 [model] Posterior to be computed for parameters {'Omega_m': 0.31943592496555234, 'b1': 0.47190281592175476}
2023-07-02 10:35:05,240 [prior] Evaluating prior at array([0.31943592, 0.47190282])
2023-07-02 10:35:05,240 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:05,240 [model] Got input parameters: {'Omega_m': 0.31943592496555234, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47190281592175476, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:05,240 [classy] Got parameters {'Omega_m': 0.31943592496555234, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:05,240 [classy] Re-using computed results
2023-07-02 10:35:05,241 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.4318005028592}
2023-07-02 10:35:05,241 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:05,241 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47190281592175476, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:05,241 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:05,260 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.72422
2023-07-02 10:35:05,260 [model] Computed derived parameters: {}
2023-07-02 10:35:05,260 [model] Posterior to be computed for parameters {'Omega_m': 0.27421586656949504, 'b1': 0.5661332671705994}
2023-07-02 10:35:05,260 [prior] Evaluating prior at array([0.27421587, 0.56613327])
2023-07-02 10:35:05,260 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:05,260 [model] Got input parameters: {'Omega_m': 0.27421586656949504, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5661332671705994, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:05,260 [classy] Got parameters {'Omega_m': 0.27421586656949504, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:05,260 [classy] Computing new state
2023-07-02 10:35:05,260 [classy] Setting parameters: {'Omega_m': 0.27421586656949504, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:05,307 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 152.13236186098842}
2023-07-02 10:35:05,307 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:05,309 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.099339
2023-07-02 10:35:05,309 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5661332671705994, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:05,309 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:05,329 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.44517
2023-07-02 10:35:05,329 [model] Computed derived parameters: {}
2023-07-02 10:35:05,329 [model] Posterior to be computed for parameters {'Omega_m': 0.31943592496555234, 'b1': 0.5044123233255025}
2023-07-02 10:35:05,329 [prior] Evaluating prior at array([0.31943592, 0.50441232])
2023-07-02 10:35:05,329 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:05,330 [model] Got input parameters: {'Omega_m': 0.31943592496555234, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5044123233255025, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:05,330 [classy] Got parameters {'Omega_m': 0.31943592496555234, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:05,330 [classy] Re-using computed results
2023-07-02 10:35:05,330 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.4318005028592}
2023-07-02 10:35:05,330 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:05,330 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5044123233255025, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:05,330 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:05,350 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.425
2023-07-02 10:35:05,350 [model] Computed derived parameters: {}
2023-07-02 10:35:05,350 [mcmc] New sample, #1008:
Omega_m:0.3194359, b1:0.4836212
2023-07-02 10:35:05,350 [model] Posterior to be computed for parameters {'Omega_m': 0.30400604035490675, 'b1': 0.5325668971402411}
2023-07-02 10:35:05,350 [prior] Evaluating prior at array([0.30400604, 0.5325669 ])
2023-07-02 10:35:05,350 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:05,350 [model] Got input parameters: {'Omega_m': 0.30400604035490675, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5325668971402411, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:05,350 [classy] Got parameters {'Omega_m': 0.30400604035490675, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:05,350 [classy] Computing new state
2023-07-02 10:35:05,350 [classy] Setting parameters: {'Omega_m': 0.30400604035490675, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:05,397 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.29270557354687}
2023-07-02 10:35:05,397 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:05,399 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00470462
2023-07-02 10:35:05,399 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5325668971402411, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:05,399 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:05,418 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.78403
2023-07-02 10:35:05,418 [model] Computed derived parameters: {}
2023-07-02 10:35:05,419 [model] Posterior to be computed for parameters {'Omega_m': 0.31943592496555234, 'b1': 0.5314609703453154}
2023-07-02 10:35:05,419 [prior] Evaluating prior at array([0.31943592, 0.53146097])
2023-07-02 10:35:05,419 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:05,419 [model] Got input parameters: {'Omega_m': 0.31943592496555234, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5314609703453154, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:05,419 [classy] Got parameters {'Omega_m': 0.31943592496555234, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:05,419 [classy] Re-using computed results
2023-07-02 10:35:05,419 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.4318005028592}
2023-07-02 10:35:05,419 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:05,419 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5314609703453154, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:05,419 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:05,438 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.49112
2023-07-02 10:35:05,438 [model] Computed derived parameters: {}
2023-07-02 10:35:05,438 [model] Posterior to be computed for parameters {'Omega_m': 0.3666060024188422, 'b1': 0.41834211210763506}
2023-07-02 10:35:05,438 [prior] Evaluating prior at array([0.366606 , 0.41834211])
2023-07-02 10:35:05,439 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:05,439 [model] Got input parameters: {'Omega_m': 0.3666060024188422, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.41834211210763506, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:05,439 [classy] Got parameters {'Omega_m': 0.3666060024188422, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:05,439 [classy] Computing new state
2023-07-02 10:35:05,439 [classy] Setting parameters: {'Omega_m': 0.3666060024188422, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:05,485 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 141.20676856243296}
2023-07-02 10:35:05,485 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:05,487 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.158222
2023-07-02 10:35:05,487 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.41834211210763506, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:05,487 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:05,507 [fs_likelihood.fslikelihood] Computed log-likelihood = -9.35011
2023-07-02 10:35:05,507 [model] Computed derived parameters: {}
2023-07-02 10:35:05,507 [model] Posterior to be computed for parameters {'Omega_m': 0.31943592496555234, 'b1': 0.5804313589430583}
2023-07-02 10:35:05,507 [prior] Evaluating prior at array([0.31943592, 0.58043136])
2023-07-02 10:35:05,507 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:05,508 [model] Got input parameters: {'Omega_m': 0.31943592496555234, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5804313589430583, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:05,508 [classy] Got parameters {'Omega_m': 0.31943592496555234, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:05,508 [classy] Re-using computed results
2023-07-02 10:35:05,508 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.4318005028592}
2023-07-02 10:35:05,508 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:05,508 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5804313589430583, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:05,508 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:05,527 [fs_likelihood.fslikelihood] Computed log-likelihood = -20.1246
2023-07-02 10:35:05,527 [model] Computed derived parameters: {}
2023-07-02 10:35:05,527 [model] Posterior to be computed for parameters {'Omega_m': 0.3109572151205396, 'b1': 0.5198832401994021}
2023-07-02 10:35:05,527 [prior] Evaluating prior at array([0.31095722, 0.51988324])
2023-07-02 10:35:05,527 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:05,527 [model] Got input parameters: {'Omega_m': 0.3109572151205396, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5198832401994021, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:05,527 [classy] Got parameters {'Omega_m': 0.3109572151205396, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:05,528 [classy] Computing new state
2023-07-02 10:35:05,528 [classy] Setting parameters: {'Omega_m': 0.3109572151205396, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:05,574 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.44424411384878}
2023-07-02 10:35:05,574 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:05,576 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000345867
2023-07-02 10:35:05,576 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5198832401994021, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:05,576 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:05,596 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.41989
2023-07-02 10:35:05,596 [model] Computed derived parameters: {}
2023-07-02 10:35:05,596 [mcmc] New sample, #1009:
Omega_m:0.3194359, b1:0.5044123
2023-07-02 10:35:05,596 [model] Posterior to be computed for parameters {'Omega_m': 0.3109572151205396, 'b1': 0.54136738611382}
2023-07-02 10:35:05,596 [prior] Evaluating prior at array([0.31095722, 0.54136739])
2023-07-02 10:35:05,596 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:05,597 [model] Got input parameters: {'Omega_m': 0.3109572151205396, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.54136738611382, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:05,597 [classy] Got parameters {'Omega_m': 0.3109572151205396, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:05,597 [classy] Re-using computed results
2023-07-02 10:35:05,597 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.44424411384878}
2023-07-02 10:35:05,597 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:05,597 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.54136738611382, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:05,597 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:05,616 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.325742
2023-07-02 10:35:05,616 [model] Computed derived parameters: {}
2023-07-02 10:35:05,616 [mcmc] New sample, #1010:
Omega_m:0.3109572, b1:0.5198832
2023-07-02 10:35:05,616 [model] Posterior to be computed for parameters {'Omega_m': 0.2855623427685354, 'b1': 0.5877048556537461}
2023-07-02 10:35:05,616 [prior] Evaluating prior at array([0.28556234, 0.58770486])
2023-07-02 10:35:05,616 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:05,616 [model] Got input parameters: {'Omega_m': 0.2855623427685354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5877048556537461, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:05,616 [classy] Got parameters {'Omega_m': 0.2855623427685354, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:05,616 [classy] Computing new state
2023-07-02 10:35:05,616 [classy] Setting parameters: {'Omega_m': 0.2855623427685354, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:05,662 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.62923438209796}
2023-07-02 10:35:05,663 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:05,664 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0478094
2023-07-02 10:35:05,665 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5877048556537461, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:05,665 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:05,684 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.77621
2023-07-02 10:35:05,684 [model] Computed derived parameters: {}
2023-07-02 10:35:05,684 [model] Posterior to be computed for parameters {'Omega_m': 0.3109572151205396, 'b1': 0.5802191203371481}
2023-07-02 10:35:05,684 [prior] Evaluating prior at array([0.31095722, 0.58021912])
2023-07-02 10:35:05,684 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:05,684 [model] Got input parameters: {'Omega_m': 0.3109572151205396, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5802191203371481, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:05,684 [classy] Got parameters {'Omega_m': 0.3109572151205396, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:05,685 [classy] Re-using computed results
2023-07-02 10:35:05,685 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.44424411384878}
2023-07-02 10:35:05,685 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:05,685 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5802191203371481, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:05,685 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:05,704 [fs_likelihood.fslikelihood] Computed log-likelihood = -12.3548
2023-07-02 10:35:05,705 [model] Computed derived parameters: {}
2023-07-02 10:35:05,705 [model] Posterior to be computed for parameters {'Omega_m': 0.3128314693534925, 'b1': 0.5379474753056178}
2023-07-02 10:35:05,705 [prior] Evaluating prior at array([0.31283147, 0.53794748])
2023-07-02 10:35:05,705 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:05,705 [model] Got input parameters: {'Omega_m': 0.3128314693534925, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5379474753056178, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:05,705 [classy] Got parameters {'Omega_m': 0.3128314693534925, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:05,705 [classy] Computing new state
2023-07-02 10:35:05,705 [classy] Setting parameters: {'Omega_m': 0.3128314693534925, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:05,752 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.21833147902151}
2023-07-02 10:35:05,752 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:05,754 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000209781
2023-07-02 10:35:05,754 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5379474753056178, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:05,754 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:05,773 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.257545
2023-07-02 10:35:05,773 [model] Computed derived parameters: {}
2023-07-02 10:35:05,774 [mcmc] New sample, #1011:
Omega_m:0.3109572, b1:0.5413674
2023-07-02 10:35:05,774 [model] Posterior to be computed for parameters {'Omega_m': 0.3128314693534925, 'b1': 0.5207644652408809}
2023-07-02 10:35:05,774 [prior] Evaluating prior at array([0.31283147, 0.52076447])
2023-07-02 10:35:05,774 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:05,774 [model] Got input parameters: {'Omega_m': 0.3128314693534925, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5207644652408809, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:05,774 [classy] Got parameters {'Omega_m': 0.3128314693534925, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:05,774 [classy] Re-using computed results
2023-07-02 10:35:05,774 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.21833147902151}
2023-07-02 10:35:05,774 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:05,774 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5207644652408809, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:05,774 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:05,793 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.15237
2023-07-02 10:35:05,793 [model] Computed derived parameters: {}
2023-07-02 10:35:05,793 [mcmc] New sample, #1012:
Omega_m:0.3128315, b1:0.5379475
2023-07-02 10:35:05,794 [model] Posterior to be computed for parameters {'Omega_m': 0.357226753630325, 'b1': 0.4397573585943402}
2023-07-02 10:35:05,794 [prior] Evaluating prior at array([0.35722675, 0.43975736])
2023-07-02 10:35:05,794 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:05,794 [model] Got input parameters: {'Omega_m': 0.357226753630325, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4397573585943402, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:05,794 [classy] Got parameters {'Omega_m': 0.357226753630325, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:05,794 [classy] Computing new state
2023-07-02 10:35:05,794 [classy] Setting parameters: {'Omega_m': 0.357226753630325, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:05,840 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.1946026330719}
2023-07-02 10:35:05,840 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:05,842 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.110526
2023-07-02 10:35:05,842 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4397573585943402, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:05,842 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:05,862 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.07196
2023-07-02 10:35:05,862 [model] Computed derived parameters: {}
2023-07-02 10:35:05,862 [model] Posterior to be computed for parameters {'Omega_m': 0.3128314693534925, 'b1': 0.5256307579423719}
2023-07-02 10:35:05,862 [prior] Evaluating prior at array([0.31283147, 0.52563076])
2023-07-02 10:35:05,862 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:05,862 [model] Got input parameters: {'Omega_m': 0.3128314693534925, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5256307579423719, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:05,862 [classy] Got parameters {'Omega_m': 0.3128314693534925, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:05,863 [classy] Re-using computed results
2023-07-02 10:35:05,863 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.21833147902151}
2023-07-02 10:35:05,863 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:05,863 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5256307579423719, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:05,863 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:05,882 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.64288
2023-07-02 10:35:05,882 [model] Computed derived parameters: {}
2023-07-02 10:35:05,882 [model] Posterior to be computed for parameters {'Omega_m': 0.3061705766051662, 'b1': 0.532918450917833}
2023-07-02 10:35:05,882 [prior] Evaluating prior at array([0.30617058, 0.53291845])
2023-07-02 10:35:05,882 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:05,882 [model] Got input parameters: {'Omega_m': 0.3061705766051662, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.532918450917833, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:05,882 [classy] Got parameters {'Omega_m': 0.3061705766051662, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:05,882 [classy] Computing new state
2023-07-02 10:35:05,882 [classy] Setting parameters: {'Omega_m': 0.3061705766051662, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:05,929 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.02668982745112}
2023-07-02 10:35:05,929 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:05,931 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00268564
2023-07-02 10:35:05,931 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.532918450917833, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:05,931 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:05,951 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.70853
2023-07-02 10:35:05,951 [model] Computed derived parameters: {}
2023-07-02 10:35:05,951 [model] Posterior to be computed for parameters {'Omega_m': 0.3128314693534925, 'b1': 0.5469439941427626}
2023-07-02 10:35:05,951 [prior] Evaluating prior at array([0.31283147, 0.54694399])
2023-07-02 10:35:05,951 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:05,951 [model] Got input parameters: {'Omega_m': 0.3128314693534925, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5469439941427626, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:05,951 [classy] Got parameters {'Omega_m': 0.3128314693534925, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:05,951 [classy] Re-using computed results
2023-07-02 10:35:05,951 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.21833147902151}
2023-07-02 10:35:05,951 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:05,951 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5469439941427626, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:05,951 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:05,971 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.21321
2023-07-02 10:35:05,971 [model] Computed derived parameters: {}
2023-07-02 10:35:05,971 [model] Posterior to be computed for parameters {'Omega_m': 0.33891877381913726, 'b1': 0.4731635299300092}
2023-07-02 10:35:05,971 [prior] Evaluating prior at array([0.33891877, 0.47316353])
2023-07-02 10:35:05,971 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:05,971 [model] Got input parameters: {'Omega_m': 0.33891877381913726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4731635299300092, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:05,971 [classy] Got parameters {'Omega_m': 0.33891877381913726, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:05,971 [classy] Computing new state
2023-07-02 10:35:05,971 [classy] Setting parameters: {'Omega_m': 0.33891877381913726, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:06,018 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.19367035062794}
2023-07-02 10:35:06,018 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:06,020 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0403893
2023-07-02 10:35:06,020 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4731635299300092, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:06,020 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:06,039 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.663637
2023-07-02 10:35:06,039 [model] Computed derived parameters: {}
2023-07-02 10:35:06,039 [model] Posterior to be computed for parameters {'Omega_m': 0.3128314693534925, 'b1': 0.5576830607960829}
2023-07-02 10:35:06,039 [prior] Evaluating prior at array([0.31283147, 0.55768306])
2023-07-02 10:35:06,039 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:06,039 [model] Got input parameters: {'Omega_m': 0.3128314693534925, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5576830607960829, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:06,039 [classy] Got parameters {'Omega_m': 0.3128314693534925, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:06,039 [classy] Re-using computed results
2023-07-02 10:35:06,039 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.21833147902151}
2023-07-02 10:35:06,039 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:06,039 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5576830607960829, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:06,040 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:06,059 [fs_likelihood.fslikelihood] Computed log-likelihood = -5.19427
2023-07-02 10:35:06,059 [model] Computed derived parameters: {}
2023-07-02 10:35:06,059 [model] Posterior to be computed for parameters {'Omega_m': 0.31043897817794885, 'b1': 0.5251299916918357}
2023-07-02 10:35:06,059 [prior] Evaluating prior at array([0.31043898, 0.52512999])
2023-07-02 10:35:06,060 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:06,060 [model] Got input parameters: {'Omega_m': 0.31043897817794885, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5251299916918357, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:06,060 [classy] Got parameters {'Omega_m': 0.31043897817794885, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:06,060 [classy] Computing new state
2023-07-02 10:35:06,060 [classy] Setting parameters: {'Omega_m': 0.31043897817794885, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:06,106 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.50692062731852}
2023-07-02 10:35:06,107 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:06,109 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000460153
2023-07-02 10:35:06,109 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5251299916918357, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:06,109 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:06,132 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.05431
2023-07-02 10:35:06,132 [model] Computed derived parameters: {}
2023-07-02 10:35:06,133 [mcmc] New sample, #1013:
Omega_m:0.3128315, b1:0.5207645
2023-07-02 10:35:06,133 [model] Posterior to be computed for parameters {'Omega_m': 0.31043897817794885, 'b1': 0.6359790755516318}
2023-07-02 10:35:06,133 [prior] Evaluating prior at array([0.31043898, 0.63597908])
2023-07-02 10:35:06,133 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:06,133 [model] Got input parameters: {'Omega_m': 0.31043897817794885, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6359790755516318, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:06,133 [classy] Got parameters {'Omega_m': 0.31043897817794885, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:06,133 [classy] Re-using computed results
2023-07-02 10:35:06,133 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.50692062731852}
2023-07-02 10:35:06,133 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:06,133 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6359790755516318, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:06,133 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:06,160 [fs_likelihood.fslikelihood] Computed log-likelihood = -46.5261
2023-07-02 10:35:06,160 [model] Computed derived parameters: {}
2023-07-02 10:35:06,161 [model] Posterior to be computed for parameters {'Omega_m': 0.27538262473486586, 'b1': 0.5890965549937988}
2023-07-02 10:35:06,161 [prior] Evaluating prior at array([0.27538262, 0.58909655])
2023-07-02 10:35:06,161 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:06,161 [model] Got input parameters: {'Omega_m': 0.27538262473486586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5890965549937988, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:06,161 [classy] Got parameters {'Omega_m': 0.27538262473486586, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:06,161 [classy] Computing new state
2023-07-02 10:35:06,161 [classy] Setting parameters: {'Omega_m': 0.27538262473486586, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:06,208 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 151.97537772925733}
2023-07-02 10:35:06,208 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:06,209 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0930955
2023-07-02 10:35:06,210 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5890965549937988, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:06,210 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:06,229 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.35736
2023-07-02 10:35:06,229 [model] Computed derived parameters: {}
2023-07-02 10:35:06,229 [model] Posterior to be computed for parameters {'Omega_m': 0.31043897817794885, 'b1': 0.5082245865207342}
2023-07-02 10:35:06,229 [prior] Evaluating prior at array([0.31043898, 0.50822459])
2023-07-02 10:35:06,229 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:06,229 [model] Got input parameters: {'Omega_m': 0.31043897817794885, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5082245865207342, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:06,229 [classy] Got parameters {'Omega_m': 0.31043897817794885, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:06,229 [classy] Re-using computed results
2023-07-02 10:35:06,229 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.50692062731852}
2023-07-02 10:35:06,229 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:06,229 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5082245865207342, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:06,230 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:06,249 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.79672
2023-07-02 10:35:06,249 [model] Computed derived parameters: {}
2023-07-02 10:35:06,249 [mcmc] New sample, #1014:
Omega_m:0.310439, b1:0.52513
2023-07-02 10:35:06,249 [model] Posterior to be computed for parameters {'Omega_m': 0.3245244596700607, 'b1': 0.48252311574549644}
2023-07-02 10:35:06,249 [prior] Evaluating prior at array([0.32452446, 0.48252312])
2023-07-02 10:35:06,250 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:06,250 [model] Got input parameters: {'Omega_m': 0.3245244596700607, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48252311574549644, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:06,250 [classy] Got parameters {'Omega_m': 0.3245244596700607, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:06,250 [classy] Computing new state
2023-07-02 10:35:06,250 [classy] Setting parameters: {'Omega_m': 0.3245244596700607, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:06,297 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.83563703822506}
2023-07-02 10:35:06,297 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:06,299 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0088323
2023-07-02 10:35:06,299 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48252311574549644, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:06,299 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:06,320 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.45515
2023-07-02 10:35:06,320 [model] Computed derived parameters: {}
2023-07-02 10:35:06,320 [model] Posterior to be computed for parameters {'Omega_m': 0.31043897817794885, 'b1': 0.5241135293384505}
2023-07-02 10:35:06,320 [prior] Evaluating prior at array([0.31043898, 0.52411353])
2023-07-02 10:35:06,320 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:06,320 [model] Got input parameters: {'Omega_m': 0.31043897817794885, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5241135293384505, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:06,320 [classy] Got parameters {'Omega_m': 0.31043897817794885, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:06,320 [classy] Re-using computed results
2023-07-02 10:35:06,320 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.50692062731852}
2023-07-02 10:35:06,320 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:06,320 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5241135293384505, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:06,320 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:06,339 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.14368
2023-07-02 10:35:06,339 [model] Computed derived parameters: {}
2023-07-02 10:35:06,340 [model] Posterior to be computed for parameters {'Omega_m': 0.30731123900552176, 'b1': 0.5139317039506722}
2023-07-02 10:35:06,340 [prior] Evaluating prior at array([0.30731124, 0.5139317 ])
2023-07-02 10:35:06,340 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:06,340 [model] Got input parameters: {'Omega_m': 0.30731123900552176, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5139317039506722, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:06,340 [classy] Got parameters {'Omega_m': 0.30731123900552176, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:06,340 [classy] Computing new state
2023-07-02 10:35:06,340 [classy] Setting parameters: {'Omega_m': 0.30731123900552176, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:06,386 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.88716812632163}
2023-07-02 10:35:06,387 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:06,388 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00186464
2023-07-02 10:35:06,388 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5139317039506722, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:06,388 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:06,409 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.56541
2023-07-02 10:35:06,409 [model] Computed derived parameters: {}
2023-07-02 10:35:06,409 [mcmc] New sample, #1015:
Omega_m:0.310439, b1:0.5082246
2023-07-02 10:35:06,409 [model] Posterior to be computed for parameters {'Omega_m': 0.30731123900552176, 'b1': 0.5126146077356437}
2023-07-02 10:35:06,409 [prior] Evaluating prior at array([0.30731124, 0.51261461])
2023-07-02 10:35:06,409 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:06,409 [model] Got input parameters: {'Omega_m': 0.30731123900552176, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5126146077356437, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:06,409 [classy] Got parameters {'Omega_m': 0.30731123900552176, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:06,409 [classy] Re-using computed results
2023-07-02 10:35:06,409 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.88716812632163}
2023-07-02 10:35:06,409 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:06,409 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5126146077356437, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:06,409 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:06,429 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.55811
2023-07-02 10:35:06,429 [model] Computed derived parameters: {}
2023-07-02 10:35:06,429 [mcmc] New sample, #1016:
Omega_m:0.3073112, b1:0.5139317
2023-07-02 10:35:06,429 [model] Posterior to be computed for parameters {'Omega_m': 0.33485263836002027, 'b1': 0.4623604172051172}
2023-07-02 10:35:06,429 [prior] Evaluating prior at array([0.33485264, 0.46236042])
2023-07-02 10:35:06,429 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:06,429 [model] Got input parameters: {'Omega_m': 0.33485263836002027, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4623604172051172, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:06,429 [classy] Got parameters {'Omega_m': 0.33485263836002027, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:06,429 [classy] Computing new state
2023-07-02 10:35:06,429 [classy] Setting parameters: {'Omega_m': 0.33485263836002027, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:06,476 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.6510032450243}
2023-07-02 10:35:06,476 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:06,478 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0292566
2023-07-02 10:35:06,478 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4623604172051172, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:06,478 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:06,497 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.915826
2023-07-02 10:35:06,497 [model] Computed derived parameters: {}
2023-07-02 10:35:06,498 [model] Posterior to be computed for parameters {'Omega_m': 0.30731123900552176, 'b1': 0.5510394829791909}
2023-07-02 10:35:06,498 [prior] Evaluating prior at array([0.30731124, 0.55103948])
2023-07-02 10:35:06,498 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:06,498 [model] Got input parameters: {'Omega_m': 0.30731123900552176, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5510394829791909, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:06,498 [classy] Got parameters {'Omega_m': 0.30731123900552176, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:06,498 [classy] Re-using computed results
2023-07-02 10:35:06,498 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.88716812632163}
2023-07-02 10:35:06,498 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:06,498 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5510394829791909, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:06,498 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:06,518 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.17784
2023-07-02 10:35:06,518 [model] Computed derived parameters: {}
2023-07-02 10:35:06,518 [model] Posterior to be computed for parameters {'Omega_m': 0.31569074546303894, 'b1': 0.49732470511858357}
2023-07-02 10:35:06,518 [prior] Evaluating prior at array([0.31569075, 0.49732471])
2023-07-02 10:35:06,518 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:06,518 [model] Got input parameters: {'Omega_m': 0.31569074546303894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49732470511858357, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:06,518 [classy] Got parameters {'Omega_m': 0.31569074546303894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:06,519 [classy] Computing new state
2023-07-02 10:35:06,519 [classy] Setting parameters: {'Omega_m': 0.31569074546303894, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:06,565 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.87600437085086}
2023-07-02 10:35:06,565 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:06,567 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000828062
2023-07-02 10:35:06,567 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49732470511858357, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:06,567 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:06,587 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.91691
2023-07-02 10:35:06,587 [model] Computed derived parameters: {}
2023-07-02 10:35:06,587 [mcmc] New sample, #1017:
Omega_m:0.3073112, b1:0.5126146
2023-07-02 10:35:06,587 [model] Posterior to be computed for parameters {'Omega_m': 0.31569074546303894, 'b1': 0.5235064712382926}
2023-07-02 10:35:06,587 [prior] Evaluating prior at array([0.31569075, 0.52350647])
2023-07-02 10:35:06,587 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:06,587 [model] Got input parameters: {'Omega_m': 0.31569074546303894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5235064712382926, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:06,587 [classy] Got parameters {'Omega_m': 0.31569074546303894, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:06,587 [classy] Re-using computed results
2023-07-02 10:35:06,587 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.87600437085086}
2023-07-02 10:35:06,587 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:06,587 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5235064712382926, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:06,587 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:06,607 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.27779
2023-07-02 10:35:06,607 [model] Computed derived parameters: {}
2023-07-02 10:35:06,607 [model] Posterior to be computed for parameters {'Omega_m': 0.30752480330784293, 'b1': 0.5122249216125379}
2023-07-02 10:35:06,608 [prior] Evaluating prior at array([0.3075248 , 0.51222492])
2023-07-02 10:35:06,608 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:06,608 [model] Got input parameters: {'Omega_m': 0.30752480330784293, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5122249216125379, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:06,608 [classy] Got parameters {'Omega_m': 0.30752480330784293, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:06,608 [classy] Computing new state
2023-07-02 10:35:06,608 [classy] Setting parameters: {'Omega_m': 0.30752480330784293, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:06,654 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.86109532711052}
2023-07-02 10:35:06,654 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:06,657 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00172939
2023-07-02 10:35:06,657 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5122249216125379, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:06,657 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:06,676 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.57769
2023-07-02 10:35:06,677 [model] Computed derived parameters: {}
2023-07-02 10:35:06,677 [mcmc] New sample, #1018:
Omega_m:0.3156907, b1:0.4973247
2023-07-02 10:35:06,677 [model] Posterior to be computed for parameters {'Omega_m': 0.30752480330784293, 'b1': 0.47678640078786116}
2023-07-02 10:35:06,677 [prior] Evaluating prior at array([0.3075248, 0.4767864])
2023-07-02 10:35:06,677 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:06,677 [model] Got input parameters: {'Omega_m': 0.30752480330784293, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47678640078786116, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:06,677 [classy] Got parameters {'Omega_m': 0.30752480330784293, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:06,677 [classy] Re-using computed results
2023-07-02 10:35:06,677 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.86109532711052}
2023-07-02 10:35:06,677 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:06,677 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47678640078786116, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:06,677 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:06,697 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.970283
2023-07-02 10:35:06,697 [model] Computed derived parameters: {}
2023-07-02 10:35:06,697 [model] Posterior to be computed for parameters {'Omega_m': 0.23502993489670398, 'b1': 0.6445047263793846}
2023-07-02 10:35:06,697 [prior] Evaluating prior at array([0.23502993, 0.64450473])
2023-07-02 10:35:06,697 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:06,697 [model] Got input parameters: {'Omega_m': 0.23502993489670398, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6445047263793846, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:06,697 [classy] Got parameters {'Omega_m': 0.23502993489670398, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:06,697 [classy] Computing new state
2023-07-02 10:35:06,697 [classy] Setting parameters: {'Omega_m': 0.23502993489670398, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:06,743 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 157.76128523408792}
2023-07-02 10:35:06,743 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:06,745 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.453514
2023-07-02 10:35:06,745 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6445047263793846, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:06,745 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:06,766 [fs_likelihood.fslikelihood] Computed log-likelihood = -47.475
2023-07-02 10:35:06,766 [model] Computed derived parameters: {}
2023-07-02 10:35:06,766 [model] Posterior to be computed for parameters {'Omega_m': 0.30752480330784293, 'b1': 0.5641447840570022}
2023-07-02 10:35:06,766 [prior] Evaluating prior at array([0.3075248 , 0.56414478])
2023-07-02 10:35:06,766 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:06,766 [model] Got input parameters: {'Omega_m': 0.30752480330784293, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5641447840570022, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:06,766 [classy] Got parameters {'Omega_m': 0.30752480330784293, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:06,766 [classy] Re-using computed results
2023-07-02 10:35:06,766 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.86109532711052}
2023-07-02 10:35:06,766 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:06,766 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5641447840570022, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:06,766 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:06,786 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.5094
2023-07-02 10:35:06,786 [model] Computed derived parameters: {}
2023-07-02 10:35:06,786 [model] Posterior to be computed for parameters {'Omega_m': 0.2974926621607847, 'b1': 0.5305303506920175}
2023-07-02 10:35:06,786 [prior] Evaluating prior at array([0.29749266, 0.53053035])
2023-07-02 10:35:06,787 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:06,787 [model] Got input parameters: {'Omega_m': 0.2974926621607847, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5305303506920175, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:06,787 [classy] Got parameters {'Omega_m': 0.2974926621607847, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:06,787 [classy] Computing new state
2023-07-02 10:35:06,787 [classy] Setting parameters: {'Omega_m': 0.2974926621607847, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:06,834 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.10336947977225}
2023-07-02 10:35:06,834 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:06,836 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0145151
2023-07-02 10:35:06,836 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5305303506920175, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:06,836 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:06,855 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.02262
2023-07-02 10:35:06,855 [model] Computed derived parameters: {}
2023-07-02 10:35:06,855 [model] Posterior to be computed for parameters {'Omega_m': 0.30752480330784293, 'b1': 0.6005456261154756}
2023-07-02 10:35:06,855 [prior] Evaluating prior at array([0.3075248 , 0.60054563])
2023-07-02 10:35:06,855 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:06,856 [model] Got input parameters: {'Omega_m': 0.30752480330784293, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.6005456261154756, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:06,856 [classy] Got parameters {'Omega_m': 0.30752480330784293, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:06,856 [classy] Re-using computed results
2023-07-02 10:35:06,856 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.86109532711052}
2023-07-02 10:35:06,856 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:06,856 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.6005456261154756, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:06,856 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:06,877 [fs_likelihood.fslikelihood] Computed log-likelihood = -19.2859
2023-07-02 10:35:06,877 [model] Computed derived parameters: {}
2023-07-02 10:35:06,877 [model] Posterior to be computed for parameters {'Omega_m': 0.3240326131346507, 'b1': 0.4821034811729985}
2023-07-02 10:35:06,877 [prior] Evaluating prior at array([0.32403261, 0.48210348])
2023-07-02 10:35:06,877 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:06,877 [model] Got input parameters: {'Omega_m': 0.3240326131346507, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4821034811729985, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:06,877 [classy] Got parameters {'Omega_m': 0.3240326131346507, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:06,877 [classy] Computing new state
2023-07-02 10:35:06,877 [classy] Setting parameters: {'Omega_m': 0.3240326131346507, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:06,924 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.89289505253635}
2023-07-02 10:35:06,924 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:06,926 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0081511
2023-07-02 10:35:06,926 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4821034811729985, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:06,926 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:06,945 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.49404
2023-07-02 10:35:06,945 [model] Computed derived parameters: {}
2023-07-02 10:35:06,945 [mcmc] New sample, #1019:
Omega_m:0.3075248, b1:0.5122249
2023-07-02 10:35:06,946 [model] Posterior to be computed for parameters {'Omega_m': 0.3240326131346507, 'b1': 0.4192901371143257}
2023-07-02 10:35:06,946 [prior] Evaluating prior at array([0.32403261, 0.41929014])
2023-07-02 10:35:06,946 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:06,946 [model] Got input parameters: {'Omega_m': 0.3240326131346507, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4192901371143257, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:06,946 [classy] Got parameters {'Omega_m': 0.3240326131346507, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:06,946 [classy] Re-using computed results
2023-07-02 10:35:06,946 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.89289505253635}
2023-07-02 10:35:06,946 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:06,946 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4192901371143257, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:06,946 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:06,966 [fs_likelihood.fslikelihood] Computed log-likelihood = -8.1415
2023-07-02 10:35:06,966 [model] Computed derived parameters: {}
2023-07-02 10:35:06,966 [model] Posterior to be computed for parameters {'Omega_m': 0.29198729253320754, 'b1': 0.540575878540625}
2023-07-02 10:35:06,966 [prior] Evaluating prior at array([0.29198729, 0.54057588])
2023-07-02 10:35:06,966 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:06,966 [model] Got input parameters: {'Omega_m': 0.29198729253320754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.540575878540625, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:06,967 [classy] Got parameters {'Omega_m': 0.29198729253320754, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:06,967 [classy] Computing new state
2023-07-02 10:35:06,967 [classy] Setting parameters: {'Omega_m': 0.29198729253320754, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:07,015 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 149.80078028440124}
2023-07-02 10:35:07,015 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:07,018 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0273402
2023-07-02 10:35:07,019 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.540575878540625, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:07,019 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:07,039 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.416746
2023-07-02 10:35:07,039 [model] Computed derived parameters: {}
2023-07-02 10:35:07,040 [model] Posterior to be computed for parameters {'Omega_m': 0.3240326131346507, 'b1': 0.4898941472097447}
2023-07-02 10:35:07,040 [prior] Evaluating prior at array([0.32403261, 0.48989415])
2023-07-02 10:35:07,040 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:07,040 [model] Got input parameters: {'Omega_m': 0.3240326131346507, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4898941472097447, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:07,040 [classy] Got parameters {'Omega_m': 0.3240326131346507, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:07,040 [classy] Re-using computed results
2023-07-02 10:35:07,040 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.89289505253635}
2023-07-02 10:35:07,040 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:07,040 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4898941472097447, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:07,040 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:07,059 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.40709
2023-07-02 10:35:07,059 [model] Computed derived parameters: {}
2023-07-02 10:35:07,059 [mcmc] New sample, #1020:
Omega_m:0.3240326, b1:0.4821035
2023-07-02 10:35:07,060 [model] Posterior to be computed for parameters {'Omega_m': 0.32210066425083966, 'b1': 0.49341933218864154}
2023-07-02 10:35:07,060 [prior] Evaluating prior at array([0.32210066, 0.49341933])
2023-07-02 10:35:07,060 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:07,060 [model] Got input parameters: {'Omega_m': 0.32210066425083966, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49341933218864154, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:07,060 [classy] Got parameters {'Omega_m': 0.32210066425083966, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:07,060 [classy] Computing new state
2023-07-02 10:35:07,060 [classy] Setting parameters: {'Omega_m': 0.32210066425083966, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:07,106 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.11855611390976}
2023-07-02 10:35:07,106 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:07,108 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00574002
2023-07-02 10:35:07,108 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49341933218864154, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:07,108 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:07,133 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.56921
2023-07-02 10:35:07,134 [model] Computed derived parameters: {}
2023-07-02 10:35:07,134 [mcmc] New sample, #1021:
Omega_m:0.3240326, b1:0.4898941
2023-07-02 10:35:07,134 [model] Posterior to be computed for parameters {'Omega_m': 0.32210066425083966, 'b1': 0.5179895625729616}
2023-07-02 10:35:07,134 [prior] Evaluating prior at array([0.32210066, 0.51798956])
2023-07-02 10:35:07,134 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:07,134 [model] Got input parameters: {'Omega_m': 0.32210066425083966, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5179895625729616, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:07,134 [classy] Got parameters {'Omega_m': 0.32210066425083966, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:07,134 [classy] Re-using computed results
2023-07-02 10:35:07,134 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.11855611390976}
2023-07-02 10:35:07,134 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:07,134 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5179895625729616, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:07,134 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:07,159 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.0584937
2023-07-02 10:35:07,159 [model] Computed derived parameters: {}
2023-07-02 10:35:07,159 [model] Posterior to be computed for parameters {'Omega_m': 0.3316826280809165, 'b1': 0.47593533183792436}
2023-07-02 10:35:07,159 [prior] Evaluating prior at array([0.33168263, 0.47593533])
2023-07-02 10:35:07,159 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:07,160 [model] Got input parameters: {'Omega_m': 0.3316826280809165, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47593533183792436, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:07,160 [classy] Got parameters {'Omega_m': 0.3316826280809165, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:07,160 [classy] Computing new state
2023-07-02 10:35:07,160 [classy] Setting parameters: {'Omega_m': 0.3316826280809165, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:07,206 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.01103906154577}
2023-07-02 10:35:07,206 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:07,208 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0217686
2023-07-02 10:35:07,208 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47593533183792436, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:07,208 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:07,228 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.40724
2023-07-02 10:35:07,229 [model] Computed derived parameters: {}
2023-07-02 10:35:07,229 [mcmc] New sample, #1022:
Omega_m:0.3221007, b1:0.4934193
2023-07-02 10:35:07,229 [model] Posterior to be computed for parameters {'Omega_m': 0.3316826280809165, 'b1': 0.42690244653728865}
2023-07-02 10:35:07,229 [prior] Evaluating prior at array([0.33168263, 0.42690245])
2023-07-02 10:35:07,229 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:07,229 [model] Got input parameters: {'Omega_m': 0.3316826280809165, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42690244653728865, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:07,229 [classy] Got parameters {'Omega_m': 0.3316826280809165, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:07,229 [classy] Re-using computed results
2023-07-02 10:35:07,229 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.01103906154577}
2023-07-02 10:35:07,229 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:07,229 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42690244653728865, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:07,229 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:07,248 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.38707
2023-07-02 10:35:07,248 [model] Computed derived parameters: {}
2023-07-02 10:35:07,249 [model] Posterior to be computed for parameters {'Omega_m': 0.34582129867748496, 'b1': 0.45013680806421313}
2023-07-02 10:35:07,249 [prior] Evaluating prior at array([0.3458213 , 0.45013681])
2023-07-02 10:35:07,249 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:07,249 [model] Got input parameters: {'Omega_m': 0.34582129867748496, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45013680806421313, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:07,249 [classy] Got parameters {'Omega_m': 0.34582129867748496, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:07,249 [classy] Computing new state
2023-07-02 10:35:07,249 [classy] Setting parameters: {'Omega_m': 0.34582129867748496, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:07,297 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.42860489928856}
2023-07-02 10:35:07,297 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:07,299 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0630884
2023-07-02 10:35:07,299 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45013680806421313, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:07,299 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:07,319 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.7906
2023-07-02 10:35:07,319 [model] Computed derived parameters: {}
2023-07-02 10:35:07,319 [model] Posterior to be computed for parameters {'Omega_m': 0.3316826280809165, 'b1': 0.4471023418328156}
2023-07-02 10:35:07,319 [prior] Evaluating prior at array([0.33168263, 0.44710234])
2023-07-02 10:35:07,320 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:07,320 [model] Got input parameters: {'Omega_m': 0.3316826280809165, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4471023418328156, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:07,320 [classy] Got parameters {'Omega_m': 0.3316826280809165, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:07,320 [classy] Re-using computed results
2023-07-02 10:35:07,320 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.01103906154577}
2023-07-02 10:35:07,320 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:07,320 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4471023418328156, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:07,320 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:07,339 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.0861262
2023-07-02 10:35:07,339 [model] Computed derived parameters: {}
2023-07-02 10:35:07,339 [model] Posterior to be computed for parameters {'Omega_m': 0.3208541233473353, 'b1': 0.49569386817944155}
2023-07-02 10:35:07,339 [prior] Evaluating prior at array([0.32085412, 0.49569387])
2023-07-02 10:35:07,340 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:07,340 [model] Got input parameters: {'Omega_m': 0.3208541233473353, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49569386817944155, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:07,340 [classy] Got parameters {'Omega_m': 0.3208541233473353, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:07,340 [classy] Computing new state
2023-07-02 10:35:07,340 [classy] Setting parameters: {'Omega_m': 0.3208541233473353, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:07,389 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.26479654260697}
2023-07-02 10:35:07,389 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:07,391 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00441031
2023-07-02 10:35:07,391 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49569386817944155, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:07,391 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:07,410 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.65353
2023-07-02 10:35:07,410 [model] Computed derived parameters: {}
2023-07-02 10:35:07,410 [mcmc] New sample, #1023:
Omega_m:0.3316826, b1:0.4759353
2023-07-02 10:35:07,410 [model] Posterior to be computed for parameters {'Omega_m': 0.3208541233473353, 'b1': 0.4809719506029375}
2023-07-02 10:35:07,410 [prior] Evaluating prior at array([0.32085412, 0.48097195])
2023-07-02 10:35:07,411 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:07,411 [model] Got input parameters: {'Omega_m': 0.3208541233473353, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4809719506029375, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:07,411 [classy] Got parameters {'Omega_m': 0.3208541233473353, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:07,411 [classy] Re-using computed results
2023-07-02 10:35:07,411 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.26479654260697}
2023-07-02 10:35:07,411 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:07,411 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4809719506029375, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:07,411 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:07,432 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.54492
2023-07-02 10:35:07,432 [model] Computed derived parameters: {}
2023-07-02 10:35:07,432 [model] Posterior to be computed for parameters {'Omega_m': 0.3239151321585103, 'b1': 0.49010851218382173}
2023-07-02 10:35:07,432 [prior] Evaluating prior at array([0.32391513, 0.49010851])
2023-07-02 10:35:07,432 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:07,432 [model] Got input parameters: {'Omega_m': 0.3239151321585103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49010851218382173, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:07,432 [classy] Got parameters {'Omega_m': 0.3239151321585103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:07,432 [classy] Computing new state
2023-07-02 10:35:07,432 [classy] Setting parameters: {'Omega_m': 0.3239151321585103, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:07,480 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.90658179891582}
2023-07-02 10:35:07,480 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:07,482 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00799245
2023-07-02 10:35:07,482 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49010851218382173, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:07,482 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:07,503 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.41802
2023-07-02 10:35:07,503 [model] Computed derived parameters: {}
2023-07-02 10:35:07,503 [mcmc] New sample, #1024:
Omega_m:0.3208541, b1:0.4956939
2023-07-02 10:35:07,503 [model] Posterior to be computed for parameters {'Omega_m': 0.3239151321585103, 'b1': 0.4606982027946477}
2023-07-02 10:35:07,503 [prior] Evaluating prior at array([0.32391513, 0.4606982 ])
2023-07-02 10:35:07,503 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:07,503 [model] Got input parameters: {'Omega_m': 0.3239151321585103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4606982027946477, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:07,503 [classy] Got parameters {'Omega_m': 0.3239151321585103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:07,503 [classy] Re-using computed results
2023-07-02 10:35:07,503 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.90658179891582}
2023-07-02 10:35:07,503 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:07,503 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4606982027946477, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:07,503 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:07,527 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.05163
2023-07-02 10:35:07,527 [model] Computed derived parameters: {}
2023-07-02 10:35:07,527 [model] Posterior to be computed for parameters {'Omega_m': 0.3475953664194987, 'b1': 0.4468997053602557}
2023-07-02 10:35:07,527 [prior] Evaluating prior at array([0.34759537, 0.44689971])
2023-07-02 10:35:07,527 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:07,527 [model] Got input parameters: {'Omega_m': 0.3475953664194987, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4468997053602557, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:07,527 [classy] Got parameters {'Omega_m': 0.3475953664194987, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:07,527 [classy] Computing new state
2023-07-02 10:35:07,527 [classy] Setting parameters: {'Omega_m': 0.3475953664194987, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:07,577 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.2342416526686}
2023-07-02 10:35:07,577 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:07,578 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0696702
2023-07-02 10:35:07,579 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4468997053602557, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:07,579 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:07,599 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.30224
2023-07-02 10:35:07,599 [model] Computed derived parameters: {}
2023-07-02 10:35:07,599 [model] Posterior to be computed for parameters {'Omega_m': 0.3239151321585103, 'b1': 0.4875687796484934}
2023-07-02 10:35:07,599 [prior] Evaluating prior at array([0.32391513, 0.48756878])
2023-07-02 10:35:07,599 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:07,599 [model] Got input parameters: {'Omega_m': 0.3239151321585103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4875687796484934, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:07,599 [classy] Got parameters {'Omega_m': 0.3239151321585103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:07,599 [classy] Re-using computed results
2023-07-02 10:35:07,599 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.90658179891582}
2023-07-02 10:35:07,599 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:07,599 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4875687796484934, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:07,599 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:07,621 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.48291
2023-07-02 10:35:07,621 [model] Computed derived parameters: {}
2023-07-02 10:35:07,621 [mcmc] New sample, #1025:
Omega_m:0.3239151, b1:0.4901085
2023-07-02 10:35:07,621 [model] Posterior to be computed for parameters {'Omega_m': 0.3318423058451499, 'b1': 0.4731042387698944}
2023-07-02 10:35:07,621 [prior] Evaluating prior at array([0.33184231, 0.47310424])
2023-07-02 10:35:07,621 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:07,622 [model] Got input parameters: {'Omega_m': 0.3318423058451499, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4731042387698944, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:07,622 [classy] Got parameters {'Omega_m': 0.3318423058451499, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:07,622 [classy] Computing new state
2023-07-02 10:35:07,622 [classy] Setting parameters: {'Omega_m': 0.3318423058451499, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:07,670 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.9928285230569}
2023-07-02 10:35:07,671 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:07,672 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0221204
2023-07-02 10:35:07,673 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4731042387698944, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:07,673 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:07,693 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.44434
2023-07-02 10:35:07,693 [model] Computed derived parameters: {}
2023-07-02 10:35:07,693 [model] Posterior to be computed for parameters {'Omega_m': 0.3239151321585103, 'b1': 0.5222298755311566}
2023-07-02 10:35:07,693 [prior] Evaluating prior at array([0.32391513, 0.52222988])
2023-07-02 10:35:07,693 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:07,693 [model] Got input parameters: {'Omega_m': 0.3239151321585103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5222298755311566, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:07,693 [classy] Got parameters {'Omega_m': 0.3239151321585103, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:07,693 [classy] Re-using computed results
2023-07-02 10:35:07,693 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.90658179891582}
2023-07-02 10:35:07,693 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:07,693 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5222298755311566, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:07,693 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:07,713 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.57568
2023-07-02 10:35:07,713 [model] Computed derived parameters: {}
2023-07-02 10:35:07,713 [model] Posterior to be computed for parameters {'Omega_m': 0.31602833965672056, 'b1': 0.5019596378600945}
2023-07-02 10:35:07,713 [prior] Evaluating prior at array([0.31602834, 0.50195964])
2023-07-02 10:35:07,713 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:07,713 [model] Got input parameters: {'Omega_m': 0.31602833965672056, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5019596378600945, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:07,713 [classy] Got parameters {'Omega_m': 0.31602833965672056, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:07,713 [classy] Computing new state
2023-07-02 10:35:07,713 [classy] Setting parameters: {'Omega_m': 0.31602833965672056, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:07,762 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.83577472459245}
2023-07-02 10:35:07,762 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:07,764 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000966025
2023-07-02 10:35:07,764 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5019596378600945, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:07,764 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:07,785 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.89005
2023-07-02 10:35:07,785 [model] Computed derived parameters: {}
2023-07-02 10:35:07,785 [mcmc] New sample, #1026:
Omega_m:0.3239151, b1:0.4875688
2023-07-02 10:35:07,786 [model] Posterior to be computed for parameters {'Omega_m': 0.31602833965672056, 'b1': 0.4688032408897801}
2023-07-02 10:35:07,786 [prior] Evaluating prior at array([0.31602834, 0.46880324])
2023-07-02 10:35:07,786 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:07,786 [model] Got input parameters: {'Omega_m': 0.31602833965672056, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4688032408897801, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:07,786 [classy] Got parameters {'Omega_m': 0.31602833965672056, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:07,786 [classy] Re-using computed results
2023-07-02 10:35:07,786 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.83577472459245}
2023-07-02 10:35:07,786 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:07,786 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4688032408897801, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:07,786 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:07,806 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.615974
2023-07-02 10:35:07,806 [model] Computed derived parameters: {}
2023-07-02 10:35:07,806 [model] Posterior to be computed for parameters {'Omega_m': 0.33486431033566555, 'b1': 0.4675900531072232}
2023-07-02 10:35:07,806 [prior] Evaluating prior at array([0.33486431, 0.46759005])
2023-07-02 10:35:07,806 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:07,806 [model] Got input parameters: {'Omega_m': 0.33486431033566555, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4675900531072232, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:07,806 [classy] Got parameters {'Omega_m': 0.33486431033566555, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:07,806 [classy] Computing new state
2023-07-02 10:35:07,806 [classy] Setting parameters: {'Omega_m': 0.33486431033566555, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:07,855 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.64968662982378}
2023-07-02 10:35:07,855 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:07,857 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0292859
2023-07-02 10:35:07,857 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4675900531072232, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:07,857 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:07,878 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.895857
2023-07-02 10:35:07,878 [model] Computed derived parameters: {}
2023-07-02 10:35:07,878 [model] Posterior to be computed for parameters {'Omega_m': 0.31602833965672056, 'b1': 0.5435518277887451}
2023-07-02 10:35:07,878 [prior] Evaluating prior at array([0.31602834, 0.54355183])
2023-07-02 10:35:07,878 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:07,878 [model] Got input parameters: {'Omega_m': 0.31602833965672056, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5435518277887451, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:07,878 [classy] Got parameters {'Omega_m': 0.31602833965672056, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:07,878 [classy] Re-using computed results
2023-07-02 10:35:07,878 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.83577472459245}
2023-07-02 10:35:07,878 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:07,878 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5435518277887451, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:07,878 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:07,898 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.81119
2023-07-02 10:35:07,898 [model] Computed derived parameters: {}
2023-07-02 10:35:07,898 [model] Posterior to be computed for parameters {'Omega_m': 0.28946826962585825, 'b1': 0.5504232181834765}
2023-07-02 10:35:07,898 [prior] Evaluating prior at array([0.28946827, 0.55042322])
2023-07-02 10:35:07,898 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:07,898 [model] Got input parameters: {'Omega_m': 0.28946826962585825, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5504232181834765, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:07,898 [classy] Got parameters {'Omega_m': 0.28946826962585825, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:07,898 [classy] Computing new state
2023-07-02 10:35:07,898 [classy] Setting parameters: {'Omega_m': 0.28946826962585825, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:07,947 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.12369173085096}
2023-07-02 10:35:07,947 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:07,949 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0346446
2023-07-02 10:35:07,949 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5504232181834765, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:07,949 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:07,968 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.25473
2023-07-02 10:35:07,968 [model] Computed derived parameters: {}
2023-07-02 10:35:07,968 [model] Posterior to be computed for parameters {'Omega_m': 0.31602833965672056, 'b1': 0.5391844009862896}
2023-07-02 10:35:07,968 [prior] Evaluating prior at array([0.31602834, 0.5391844 ])
2023-07-02 10:35:07,968 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:07,968 [model] Got input parameters: {'Omega_m': 0.31602833965672056, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5391844009862896, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:07,969 [classy] Got parameters {'Omega_m': 0.31602833965672056, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:07,969 [classy] Re-using computed results
2023-07-02 10:35:07,969 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.83577472459245}
2023-07-02 10:35:07,969 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:07,969 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5391844009862896, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:07,969 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:07,989 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.73356
2023-07-02 10:35:07,989 [model] Computed derived parameters: {}
2023-07-02 10:35:07,989 [model] Posterior to be computed for parameters {'Omega_m': 0.3187614287664508, 'b1': 0.49697262978946577}
2023-07-02 10:35:07,989 [prior] Evaluating prior at array([0.31876143, 0.49697263])
2023-07-02 10:35:07,989 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:07,989 [model] Got input parameters: {'Omega_m': 0.3187614287664508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.49697262978946577, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:07,989 [classy] Got parameters {'Omega_m': 0.3187614287664508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:07,989 [classy] Computing new state
2023-07-02 10:35:07,989 [classy] Setting parameters: {'Omega_m': 0.3187614287664508, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:08,037 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.51145642240135}
2023-07-02 10:35:08,037 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:08,039 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00258141
2023-07-02 10:35:08,039 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.49697262978946577, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:08,039 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:08,058 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.82381
2023-07-02 10:35:08,058 [model] Computed derived parameters: {}
2023-07-02 10:35:08,058 [mcmc] New sample, #1027:
Omega_m:0.3160283, b1:0.5019596
2023-07-02 10:35:08,058 [model] Posterior to be computed for parameters {'Omega_m': 0.3187614287664508, 'b1': 0.4861198818226653}
2023-07-02 10:35:08,058 [prior] Evaluating prior at array([0.31876143, 0.48611988])
2023-07-02 10:35:08,058 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:08,058 [model] Got input parameters: {'Omega_m': 0.3187614287664508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4861198818226653, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:08,058 [classy] Got parameters {'Omega_m': 0.3187614287664508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:08,058 [classy] Re-using computed results
2023-07-02 10:35:08,058 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.51145642240135}
2023-07-02 10:35:08,058 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:08,058 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4861198818226653, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:08,058 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:08,079 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.70908
2023-07-02 10:35:08,079 [model] Computed derived parameters: {}
2023-07-02 10:35:08,079 [mcmc] New sample, #1028:
Omega_m:0.3187614, b1:0.4969726
2023-07-02 10:35:08,079 [model] Posterior to be computed for parameters {'Omega_m': 0.3310714915161198, 'b1': 0.46365797889239324}
2023-07-02 10:35:08,079 [prior] Evaluating prior at array([0.33107149, 0.46365798])
2023-07-02 10:35:08,079 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:08,079 [model] Got input parameters: {'Omega_m': 0.3310714915161198, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.46365797889239324, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:08,079 [classy] Got parameters {'Omega_m': 0.3310714915161198, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:08,079 [classy] Computing new state
2023-07-02 10:35:08,079 [classy] Setting parameters: {'Omega_m': 0.3310714915161198, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:08,127 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.0808057934897}
2023-07-02 10:35:08,127 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:08,129 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0204472
2023-07-02 10:35:08,130 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.46365797889239324, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:08,130 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:08,150 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.44618
2023-07-02 10:35:08,150 [model] Computed derived parameters: {}
2023-07-02 10:35:08,150 [model] Posterior to be computed for parameters {'Omega_m': 0.3187614287664508, 'b1': 0.4695062984992326}
2023-07-02 10:35:08,150 [prior] Evaluating prior at array([0.31876143, 0.4695063 ])
2023-07-02 10:35:08,150 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:08,150 [model] Got input parameters: {'Omega_m': 0.3187614287664508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4695062984992326, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:08,150 [classy] Got parameters {'Omega_m': 0.3187614287664508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:08,150 [classy] Re-using computed results
2023-07-02 10:35:08,150 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.51145642240135}
2023-07-02 10:35:08,150 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:08,150 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4695062984992326, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:08,150 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:08,170 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.33326
2023-07-02 10:35:08,170 [model] Computed derived parameters: {}
2023-07-02 10:35:08,170 [mcmc] New sample, #1029:
Omega_m:0.3187614, b1:0.4861199
2023-07-02 10:35:08,170 [model] Posterior to be computed for parameters {'Omega_m': 0.3298709082023951, 'b1': 0.44923507374834787}
2023-07-02 10:35:08,170 [prior] Evaluating prior at array([0.32987091, 0.44923507])
2023-07-02 10:35:08,171 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:08,171 [model] Got input parameters: {'Omega_m': 0.3298709082023951, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44923507374834787, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:08,171 [classy] Got parameters {'Omega_m': 0.3298709082023951, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:08,171 [classy] Computing new state
2023-07-02 10:35:08,171 [classy] Setting parameters: {'Omega_m': 0.3298709082023951, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:08,218 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.21820126031002}
2023-07-02 10:35:08,218 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:08,220 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.017968
2023-07-02 10:35:08,220 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44923507374834787, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:08,220 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:08,239 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.233302
2023-07-02 10:35:08,239 [model] Computed derived parameters: {}
2023-07-02 10:35:08,239 [model] Posterior to be computed for parameters {'Omega_m': 0.3187614287664508, 'b1': 0.4854278396919156}
2023-07-02 10:35:08,239 [prior] Evaluating prior at array([0.31876143, 0.48542784])
2023-07-02 10:35:08,240 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:08,240 [model] Got input parameters: {'Omega_m': 0.3187614287664508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4854278396919156, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:08,240 [classy] Got parameters {'Omega_m': 0.3187614287664508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:08,240 [classy] Re-using computed results
2023-07-02 10:35:08,240 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.51145642240135}
2023-07-02 10:35:08,240 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:08,240 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4854278396919156, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:08,240 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:08,259 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.6804
2023-07-02 10:35:08,259 [model] Computed derived parameters: {}
2023-07-02 10:35:08,259 [mcmc] New sample, #1030:
Omega_m:0.3187614, b1:0.4695063
2023-07-02 10:35:08,259 [model] Posterior to be computed for parameters {'Omega_m': 0.35260204325852296, 'b1': 0.42367960873004495}
2023-07-02 10:35:08,259 [prior] Evaluating prior at array([0.35260204, 0.42367961])
2023-07-02 10:35:08,259 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:08,259 [model] Got input parameters: {'Omega_m': 0.35260204325852296, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.42367960873004495, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:08,260 [classy] Got parameters {'Omega_m': 0.35260204325852296, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:08,260 [classy] Computing new state
2023-07-02 10:35:08,260 [classy] Setting parameters: {'Omega_m': 0.35260204325852296, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:08,308 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 142.69056120918876}
2023-07-02 10:35:08,308 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:08,309 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0898457
2023-07-02 10:35:08,309 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.42367960873004495, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:08,309 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:08,329 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.99727
2023-07-02 10:35:08,329 [model] Computed derived parameters: {}
2023-07-02 10:35:08,329 [model] Posterior to be computed for parameters {'Omega_m': 0.3187614287664508, 'b1': 0.48285830005573693}
2023-07-02 10:35:08,329 [prior] Evaluating prior at array([0.31876143, 0.4828583 ])
2023-07-02 10:35:08,329 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:08,329 [model] Got input parameters: {'Omega_m': 0.3187614287664508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.48285830005573693, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:08,330 [classy] Got parameters {'Omega_m': 0.3187614287664508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:08,330 [classy] Re-using computed results
2023-07-02 10:35:08,330 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.51145642240135}
2023-07-02 10:35:08,330 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:08,330 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.48285830005573693, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:08,330 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:08,349 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.55187
2023-07-02 10:35:08,349 [model] Computed derived parameters: {}
2023-07-02 10:35:08,349 [mcmc] New sample, #1031:
Omega_m:0.3187614, b1:0.4854278
2023-07-02 10:35:08,349 [model] Posterior to be computed for parameters {'Omega_m': 0.30433693805608064, 'b1': 0.5091783535553551}
2023-07-02 10:35:08,349 [prior] Evaluating prior at array([0.30433694, 0.50917835])
2023-07-02 10:35:08,349 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:08,349 [model] Got input parameters: {'Omega_m': 0.30433693805608064, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5091783535553551, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:08,349 [classy] Got parameters {'Omega_m': 0.30433693805608064, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:08,349 [classy] Computing new state
2023-07-02 10:35:08,350 [classy] Setting parameters: {'Omega_m': 0.30433693805608064, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:08,397 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 148.25193240975852}
2023-07-02 10:35:08,397 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:08,398 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00435659
2023-07-02 10:35:08,399 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5091783535553551, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:08,399 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:08,418 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.94041
2023-07-02 10:35:08,418 [model] Computed derived parameters: {}
2023-07-02 10:35:08,418 [model] Posterior to be computed for parameters {'Omega_m': 0.3187614287664508, 'b1': 0.4904082641696383}
2023-07-02 10:35:08,418 [prior] Evaluating prior at array([0.31876143, 0.49040826])
2023-07-02 10:35:08,418 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:08,418 [model] Got input parameters: {'Omega_m': 0.3187614287664508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4904082641696383, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:08,418 [classy] Got parameters {'Omega_m': 0.3187614287664508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:08,418 [classy] Re-using computed results
2023-07-02 10:35:08,418 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.51145642240135}
2023-07-02 10:35:08,418 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:08,418 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4904082641696383, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:08,418 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:08,438 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.83004
2023-07-02 10:35:08,438 [model] Computed derived parameters: {}
2023-07-02 10:35:08,438 [mcmc] New sample, #1032:
Omega_m:0.3187614, b1:0.4828583
2023-07-02 10:35:08,438 [model] Posterior to be computed for parameters {'Omega_m': 0.32691742349601877, 'b1': 0.47552619852620426}
2023-07-02 10:35:08,438 [prior] Evaluating prior at array([0.32691742, 0.4755262 ])
2023-07-02 10:35:08,438 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:08,438 [model] Got input parameters: {'Omega_m': 0.32691742349601877, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.47552619852620426, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:08,438 [classy] Got parameters {'Omega_m': 0.32691742349601877, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:08,438 [classy] Computing new state
2023-07-02 10:35:08,438 [classy] Setting parameters: {'Omega_m': 0.32691742349601877, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:08,485 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.55816136393182}
2023-07-02 10:35:08,486 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:08,487 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0125322
2023-07-02 10:35:08,488 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.47552619852620426, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:08,488 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:08,507 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.16316
2023-07-02 10:35:08,507 [model] Computed derived parameters: {}
2023-07-02 10:35:08,507 [model] Posterior to be computed for parameters {'Omega_m': 0.3187614287664508, 'b1': 0.45951800180218555}
2023-07-02 10:35:08,507 [prior] Evaluating prior at array([0.31876143, 0.459518 ])
2023-07-02 10:35:08,507 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:08,507 [model] Got input parameters: {'Omega_m': 0.3187614287664508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45951800180218555, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:08,507 [classy] Got parameters {'Omega_m': 0.3187614287664508, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:08,507 [classy] Re-using computed results
2023-07-02 10:35:08,507 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.51145642240135}
2023-07-02 10:35:08,507 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:08,507 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45951800180218555, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:08,507 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:08,526 [fs_likelihood.fslikelihood] Computed log-likelihood = -0.166277
2023-07-02 10:35:08,526 [model] Computed derived parameters: {}
2023-07-02 10:35:08,526 [model] Posterior to be computed for parameters {'Omega_m': 0.3199822654120504, 'b1': 0.4881806301774465}
2023-07-02 10:35:08,526 [prior] Evaluating prior at array([0.31998227, 0.48818063])
2023-07-02 10:35:08,527 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:08,527 [model] Got input parameters: {'Omega_m': 0.3199822654120504, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4881806301774465, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:08,527 [classy] Got parameters {'Omega_m': 0.3199822654120504, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:08,527 [classy] Computing new state
2023-07-02 10:35:08,527 [classy] Setting parameters: {'Omega_m': 0.3199822654120504, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:08,574 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.36738807560533}
2023-07-02 10:35:08,574 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:08,576 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00358651
2023-07-02 10:35:08,576 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4881806301774465, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:08,576 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:08,595 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.77392
2023-07-02 10:35:08,595 [model] Computed derived parameters: {}
2023-07-02 10:35:08,595 [mcmc] New sample, #1033:
Omega_m:0.3187614, b1:0.4904083
2023-07-02 10:35:08,595 [model] Posterior to be computed for parameters {'Omega_m': 0.3199822654120504, 'b1': 0.43240203612913003}
2023-07-02 10:35:08,595 [prior] Evaluating prior at array([0.31998227, 0.43240204])
2023-07-02 10:35:08,596 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:08,596 [model] Got input parameters: {'Omega_m': 0.3199822654120504, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.43240203612913003, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:08,596 [classy] Got parameters {'Omega_m': 0.3199822654120504, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:08,596 [classy] Re-using computed results
2023-07-02 10:35:08,596 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.36738807560533}
2023-07-02 10:35:08,596 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:08,596 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.43240203612913003, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:08,596 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:08,615 [fs_likelihood.fslikelihood] Computed log-likelihood = -6.05209
2023-07-02 10:35:08,615 [model] Computed derived parameters: {}
2023-07-02 10:35:08,615 [model] Posterior to be computed for parameters {'Omega_m': 0.34702855530393056, 'b1': 0.43882985508154004}
2023-07-02 10:35:08,615 [prior] Evaluating prior at array([0.34702856, 0.43882986])
2023-07-02 10:35:08,616 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:08,616 [model] Got input parameters: {'Omega_m': 0.34702855530393056, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.43882985508154004, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:08,616 [classy] Got parameters {'Omega_m': 0.34702855530393056, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:08,616 [classy] Computing new state
2023-07-02 10:35:08,616 [classy] Setting parameters: {'Omega_m': 0.34702855530393056, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:08,662 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.2962409684692}
2023-07-02 10:35:08,662 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:08,664 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0675348
2023-07-02 10:35:08,664 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.43882985508154004, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:08,664 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:08,684 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.08786
2023-07-02 10:35:08,684 [model] Computed derived parameters: {}
2023-07-02 10:35:08,684 [model] Posterior to be computed for parameters {'Omega_m': 0.3199822654120504, 'b1': 0.4818369931368075}
2023-07-02 10:35:08,684 [prior] Evaluating prior at array([0.31998227, 0.48183699])
2023-07-02 10:35:08,684 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:08,684 [model] Got input parameters: {'Omega_m': 0.3199822654120504, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4818369931368075, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:08,684 [classy] Got parameters {'Omega_m': 0.3199822654120504, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:08,685 [classy] Re-using computed results
2023-07-02 10:35:08,685 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.36738807560533}
2023-07-02 10:35:08,685 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:08,685 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4818369931368075, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:08,685 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:08,704 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.55976
2023-07-02 10:35:08,704 [model] Computed derived parameters: {}
2023-07-02 10:35:08,704 [mcmc] New sample, #1034:
Omega_m:0.3199823, b1:0.4881806
2023-07-02 10:35:08,704 [model] Posterior to be computed for parameters {'Omega_m': 0.31445654198061374, 'b1': 0.4919196601272578}
2023-07-02 10:35:08,704 [prior] Evaluating prior at array([0.31445654, 0.49191966])
2023-07-02 10:35:08,704 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:08,704 [model] Got input parameters: {'Omega_m': 0.31445654198061374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4919196601272578, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:08,704 [classy] Got parameters {'Omega_m': 0.31445654198061374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:08,705 [classy] Computing new state
2023-07-02 10:35:08,705 [classy] Setting parameters: {'Omega_m': 0.31445654198061374, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:08,751 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.02342492111913}
2023-07-02 10:35:08,751 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:08,753 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.000439891
2023-07-02 10:35:08,753 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4919196601272578, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:08,753 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:08,772 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.68707
2023-07-02 10:35:08,772 [model] Computed derived parameters: {}
2023-07-02 10:35:08,772 [mcmc] New sample, #1035:
Omega_m:0.3199823, b1:0.481837
2023-07-02 10:35:08,772 [model] Posterior to be computed for parameters {'Omega_m': 0.31445654198061374, 'b1': 0.44981503289275676}
2023-07-02 10:35:08,772 [prior] Evaluating prior at array([0.31445654, 0.44981503])
2023-07-02 10:35:08,772 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:08,772 [model] Got input parameters: {'Omega_m': 0.31445654198061374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.44981503289275676, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:08,772 [classy] Got parameters {'Omega_m': 0.31445654198061374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:08,772 [classy] Re-using computed results
2023-07-02 10:35:08,772 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.02342492111913}
2023-07-02 10:35:08,772 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:08,772 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.44981503289275676, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:08,772 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:08,792 [fs_likelihood.fslikelihood] Computed log-likelihood = -3.86562
2023-07-02 10:35:08,793 [model] Computed derived parameters: {}
2023-07-02 10:35:08,793 [model] Posterior to be computed for parameters {'Omega_m': 0.3295677053360502, 'b1': 0.4643466500333471}
2023-07-02 10:35:08,793 [prior] Evaluating prior at array([0.32956771, 0.46434665])
2023-07-02 10:35:08,793 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:08,793 [model] Got input parameters: {'Omega_m': 0.3295677053360502, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4643466500333471, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:08,793 [classy] Got parameters {'Omega_m': 0.3295677053360502, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:08,793 [classy] Computing new state
2023-07-02 10:35:08,793 [classy] Setting parameters: {'Omega_m': 0.3295677053360502, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:08,839 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.25297019729933}
2023-07-02 10:35:08,839 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:08,841 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0173664
2023-07-02 10:35:08,841 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4643466500333471, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:08,841 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:08,861 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.58469
2023-07-02 10:35:08,861 [model] Computed derived parameters: {}
2023-07-02 10:35:08,861 [model] Posterior to be computed for parameters {'Omega_m': 0.31445654198061374, 'b1': 0.5407098898760135}
2023-07-02 10:35:08,861 [prior] Evaluating prior at array([0.31445654, 0.54070989])
2023-07-02 10:35:08,861 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:08,861 [model] Got input parameters: {'Omega_m': 0.31445654198061374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5407098898760135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:08,861 [classy] Got parameters {'Omega_m': 0.31445654198061374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:08,861 [classy] Re-using computed results
2023-07-02 10:35:08,861 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.02342492111913}
2023-07-02 10:35:08,861 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:08,861 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5407098898760135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:08,861 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:08,881 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.42138
2023-07-02 10:35:08,881 [model] Computed derived parameters: {}
2023-07-02 10:35:08,881 [model] Posterior to be computed for parameters {'Omega_m': 0.33446424786503753, 'b1': 0.4554120357087353}
2023-07-02 10:35:08,881 [prior] Evaluating prior at array([0.33446425, 0.45541204])
2023-07-02 10:35:08,881 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:08,881 [model] Got input parameters: {'Omega_m': 0.33446424786503753, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4554120357087353, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:08,881 [classy] Got parameters {'Omega_m': 0.33446424786503753, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:08,881 [classy] Computing new state
2023-07-02 10:35:08,881 [classy] Setting parameters: {'Omega_m': 0.33446424786503753, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:08,927 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 144.69495118105922}
2023-07-02 10:35:08,927 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:08,929 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0282823
2023-07-02 10:35:08,929 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4554120357087353, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:08,929 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:08,949 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.748278
2023-07-02 10:35:08,949 [model] Computed derived parameters: {}
2023-07-02 10:35:08,949 [model] Posterior to be computed for parameters {'Omega_m': 0.31445654198061374, 'b1': 0.5138059754665897}
2023-07-02 10:35:08,949 [prior] Evaluating prior at array([0.31445654, 0.51380598])
2023-07-02 10:35:08,949 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:08,949 [model] Got input parameters: {'Omega_m': 0.31445654198061374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5138059754665897, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:08,949 [classy] Got parameters {'Omega_m': 0.31445654198061374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:08,949 [classy] Re-using computed results
2023-07-02 10:35:08,949 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.02342492111913}
2023-07-02 10:35:08,949 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:08,949 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5138059754665897, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:08,949 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:08,969 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.49932
2023-07-02 10:35:08,969 [model] Computed derived parameters: {}
2023-07-02 10:35:08,969 [mcmc] New sample, #1036:
Omega_m:0.3144565, b1:0.4919197
2023-07-02 10:35:08,969 [model] Posterior to be computed for parameters {'Omega_m': 0.34417623635635236, 'b1': 0.45957709753474135}
2023-07-02 10:35:08,969 [prior] Evaluating prior at array([0.34417624, 0.4595771 ])
2023-07-02 10:35:08,969 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:08,969 [model] Got input parameters: {'Omega_m': 0.34417623635635236, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.45957709753474135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:08,969 [classy] Got parameters {'Omega_m': 0.34417623635635236, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:08,969 [classy] Computing new state
2023-07-02 10:35:08,969 [classy] Setting parameters: {'Omega_m': 0.34417623635635236, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:09,016 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 143.6096585255666}
2023-07-02 10:35:09,016 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:09,018 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0572549
2023-07-02 10:35:09,018 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.45957709753474135, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:09,018 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:09,037 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.65422
2023-07-02 10:35:09,037 [model] Computed derived parameters: {}
2023-07-02 10:35:09,037 [model] Posterior to be computed for parameters {'Omega_m': 0.31445654198061374, 'b1': 0.4589538282593211}
2023-07-02 10:35:09,037 [prior] Evaluating prior at array([0.31445654, 0.45895383])
2023-07-02 10:35:09,038 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:09,038 [model] Got input parameters: {'Omega_m': 0.31445654198061374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4589538282593211, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:09,038 [classy] Got parameters {'Omega_m': 0.31445654198061374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:09,038 [classy] Re-using computed results
2023-07-02 10:35:09,038 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.02342492111913}
2023-07-02 10:35:09,038 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:09,038 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4589538282593211, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:09,038 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:09,057 [fs_likelihood.fslikelihood] Computed log-likelihood = -1.71353
2023-07-02 10:35:09,057 [model] Computed derived parameters: {}
2023-07-02 10:35:09,057 [model] Posterior to be computed for parameters {'Omega_m': 0.28590053202600774, 'b1': 0.565911503823339}
2023-07-02 10:35:09,057 [prior] Evaluating prior at array([0.28590053, 0.5659115 ])
2023-07-02 10:35:09,058 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:09,058 [model] Got input parameters: {'Omega_m': 0.28590053202600774, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.565911503823339, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:09,058 [classy] Got parameters {'Omega_m': 0.28590053202600774, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:09,058 [classy] Computing new state
2023-07-02 10:35:09,058 [classy] Setting parameters: {'Omega_m': 0.28590053202600774, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:09,104 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 150.5852256997668}
2023-07-02 10:35:09,104 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:09,106 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0465797
2023-07-02 10:35:09,107 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.565911503823339, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:09,107 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:09,128 [fs_likelihood.fslikelihood] Computed log-likelihood = -2.95988
2023-07-02 10:35:09,128 [model] Computed derived parameters: {}
2023-07-02 10:35:09,128 [model] Posterior to be computed for parameters {'Omega_m': 0.31445654198061374, 'b1': 0.5680557699525874}
2023-07-02 10:35:09,128 [prior] Evaluating prior at array([0.31445654, 0.56805577])
2023-07-02 10:35:09,128 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:09,128 [model] Got input parameters: {'Omega_m': 0.31445654198061374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5680557699525874, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:09,128 [classy] Got parameters {'Omega_m': 0.31445654198061374, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:09,128 [classy] Re-using computed results
2023-07-02 10:35:09,128 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.02342492111913}
2023-07-02 10:35:09,128 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:09,128 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5680557699525874, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:09,128 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:09,150 [fs_likelihood.fslikelihood] Computed log-likelihood = -9.89368
2023-07-02 10:35:09,151 [model] Computed derived parameters: {}
2023-07-02 10:35:09,151 [model] Posterior to be computed for parameters {'Omega_m': 0.3186696435499658, 'b1': 0.5061184209503702}
2023-07-02 10:35:09,151 [prior] Evaluating prior at array([0.31866964, 0.50611842])
2023-07-02 10:35:09,151 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:09,151 [model] Got input parameters: {'Omega_m': 0.3186696435499658, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5061184209503702, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:09,151 [classy] Got parameters {'Omega_m': 0.3186696435499658, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:09,151 [classy] Computing new state
2023-07-02 10:35:09,151 [classy] Setting parameters: {'Omega_m': 0.3186696435499658, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:09,199 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.5223102323367}
2023-07-02 10:35:09,199 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:09,201 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00251284
2023-07-02 10:35:09,201 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5061184209503702, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:09,201 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:09,221 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.4364
2023-07-02 10:35:09,221 [model] Computed derived parameters: {}
2023-07-02 10:35:09,221 [mcmc] New sample, #1037:
Omega_m:0.3144565, b1:0.513806
2023-07-02 10:35:09,222 [model] Posterior to be computed for parameters {'Omega_m': 0.3186696435499658, 'b1': 0.5712602913875514}
2023-07-02 10:35:09,222 [prior] Evaluating prior at array([0.31866964, 0.57126029])
2023-07-02 10:35:09,222 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:09,222 [model] Got input parameters: {'Omega_m': 0.3186696435499658, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5712602913875514, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:09,222 [classy] Got parameters {'Omega_m': 0.3186696435499658, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:09,222 [classy] Re-using computed results
2023-07-02 10:35:09,222 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.5223102323367}
2023-07-02 10:35:09,222 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:09,222 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5712602913875514, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:09,222 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:09,243 [fs_likelihood.fslikelihood] Computed log-likelihood = -14.7246
2023-07-02 10:35:09,243 [model] Computed derived parameters: {}
2023-07-02 10:35:09,243 [model] Posterior to be computed for parameters {'Omega_m': 0.3219917227547285, 'b1': 0.5000566955033524}
2023-07-02 10:35:09,243 [prior] Evaluating prior at array([0.32199172, 0.5000567 ])
2023-07-02 10:35:09,243 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:09,243 [model] Got input parameters: {'Omega_m': 0.3219917227547285, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5000566955033524, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:09,243 [classy] Got parameters {'Omega_m': 0.3219917227547285, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:09,243 [classy] Computing new state
2023-07-02 10:35:09,243 [classy] Setting parameters: {'Omega_m': 0.3219917227547285, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:09,292 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.13131686436915}
2023-07-02 10:35:09,292 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:09,294 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0056167
2023-07-02 10:35:09,294 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5000566955033524, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:09,294 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:09,315 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.2519
2023-07-02 10:35:09,315 [model] Computed derived parameters: {}
2023-07-02 10:35:09,315 [mcmc] New sample, #1038:
Omega_m:0.3186696, b1:0.5061184
2023-07-02 10:35:09,315 [model] Posterior to be computed for parameters {'Omega_m': 0.3219917227547285, 'b1': 0.4352841546914152}
2023-07-02 10:35:09,315 [prior] Evaluating prior at array([0.32199172, 0.43528415])
2023-07-02 10:35:09,315 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:09,315 [model] Got input parameters: {'Omega_m': 0.3219917227547285, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.4352841546914152, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:09,315 [classy] Got parameters {'Omega_m': 0.3219917227547285, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:09,315 [classy] Re-using computed results
2023-07-02 10:35:09,315 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 146.13131686436915}
2023-07-02 10:35:09,315 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:09,315 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.4352841546914152, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:09,315 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:09,336 [fs_likelihood.fslikelihood] Computed log-likelihood = -4.38444
2023-07-02 10:35:09,336 [model] Computed derived parameters: {}
2023-07-02 10:35:09,336 [model] Posterior to be computed for parameters {'Omega_m': 0.3085284211800855, 'b1': 0.5246228881573046}
2023-07-02 10:35:09,336 [prior] Evaluating prior at array([0.30852842, 0.52462289])
2023-07-02 10:35:09,336 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:09,336 [model] Got input parameters: {'Omega_m': 0.3085284211800855, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5246228881573046, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:09,336 [classy] Got parameters {'Omega_m': 0.3085284211800855, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:09,336 [classy] Computing new state
2023-07-02 10:35:09,336 [classy] Setting parameters: {'Omega_m': 0.3085284211800855, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:09,385 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.73878994153398}
2023-07-02 10:35:09,385 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:09,386 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.00117145
2023-07-02 10:35:09,386 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5246228881573046, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:09,387 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:09,407 [fs_likelihood.fslikelihood] Computed log-likelihood = 2.2446
2023-07-02 10:35:09,407 [model] Computed derived parameters: {}
2023-07-02 10:35:09,407 [mcmc] New sample, #1039:
Omega_m:0.3219917, b1:0.5000567
2023-07-02 10:35:09,407 [model] Posterior to be computed for parameters {'Omega_m': 0.3085284211800855, 'b1': 0.5402539877013627}
2023-07-02 10:35:09,407 [prior] Evaluating prior at array([0.30852842, 0.54025399])
2023-07-02 10:35:09,407 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:09,407 [model] Got input parameters: {'Omega_m': 0.3085284211800855, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.5402539877013627, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:09,407 [classy] Got parameters {'Omega_m': 0.3085284211800855, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:09,407 [classy] Re-using computed results
2023-07-02 10:35:09,407 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 147.73878994153398}
2023-07-02 10:35:09,407 [bao_likelihood.baolikelihood] Re-using computed results
2023-07-02 10:35:09,407 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.5402539877013627, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:09,407 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:09,427 [fs_likelihood.fslikelihood] Computed log-likelihood = 0.486176
2023-07-02 10:35:09,427 [model] Computed derived parameters: {}
2023-07-02 10:35:09,427 [model] Posterior to be computed for parameters {'Omega_m': 0.32769842517074427, 'b1': 0.489643800108165}
2023-07-02 10:35:09,427 [prior] Evaluating prior at array([0.32769843, 0.4896438 ])
2023-07-02 10:35:09,427 [prior] Got logpriors (internal) = -1.2809338454620642
2023-07-02 10:35:09,427 [model] Got input parameters: {'Omega_m': 0.32769842517074427, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'b1': 0.489643800108165, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:09,427 [classy] Got parameters {'Omega_m': 0.32769842517074427, 'omega_b': 0.02237, 'H0': 67.36, 'As': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544}
2023-07-02 10:35:09,427 [classy] Computing new state
2023-07-02 10:35:09,427 [classy] Setting parameters: {'Omega_m': 0.32769842517074427, 'omega_b': 0.02237, 'H0': 67.36, 'A_s': 2.083e-09, 'n_s': 0.9649, 'tau_reio': 0.0544, 'N_ncdm': 1, 'N_ur': 2.0328, 'output': ''}
2023-07-02 10:35:09,474 [bao_likelihood.baolikelihood] Got parameters {'rdrag': 145.4679967540426}
2023-07-02 10:35:09,475 [bao_likelihood.baolikelihood] Computing new state
2023-07-02 10:35:09,476 [bao_likelihood.baolikelihood] Computed log-likelihood = -0.0138769
2023-07-02 10:35:09,476 [fs_likelihood.fslikelihood] Got parameters {'b1': 0.489643800108165, 'sigmapar': 0.0, 'sigmaper': 0.0}
2023-07-02 10:35:09,476 [fs_likelihood.fslikelihood] Computing new state
2023-07-02 10:35:09,496 [fs_likelihood.fslikelihood] Computed log-likelihood = 1.67305
2023-07-02 10:35:09,496 [model] Computed derived parameters: {}
2023-07-02 10:35:09,497 [mcmc] New sample, #1040:
Omega_m:0.3085284, b1:0.5246229
2023-07-02 10:35:09,497 [mcmc] Learn + convergence test @ 1040 samples accepted.
2023-07-02 10:35:09,497 [mcmc] Ready to check convergence and learn a new proposal covmat
2023-07-02 10:35:09,502 [mcmc] - Acceptance rate: 0.451
2023-07-02 10:35:09,502 [mcmc] - Condition number = 4.45256
2023-07-02 10:35:09,502 [mcmc] - Eigenvalues = array([0.00484795, 0.02158577])
2023-07-02 10:35:09,502 [mcmc] - Convergence of means: R-1 = 0.021586 after 832 accepted steps
2023-07-02 10:35:09,508 [mcmc] - normalized std's of bounds = array([[0.14346561, 0.17114478],
[0.17787582, 0.18262451]])
2023-07-02 10:35:09,508 [mcmc] - Convergence of bounds: R-1 = 0.182625 after 1040 accepted steps
2023-07-02 10:35:09,508 [mcmc] The run has converged!
2023-07-02 10:35:09,518 [mcmc] Dumped checkpoint and progress info, and current covmat.
2023-07-02 10:35:09,519 [mcmc] Sampling complete after 1040 accepted steps.
CosmoSIS¶
In [51]:
%%file _tests/config_bao_fs.ini
[DEFAULT]
fatal_errors = T
[runtime]
sampler = emcee
[output]
filename = _tests/chains_bao_fs_cosmosis/chain.txt
format = text
verbosity = 0
[pipeline]
modules = consistency camb bao fs
values = _tests/values_bao_fs.ini
likelihoods = BAOLikelihood FSLikelihood ; notice the name of the liklelihood: the same as the *.py file
quiet = T
debug = F
timing = F
[consistency]
file = ${COSMOSIS_STD_DIR}/utility/consistency/consistency_interface.py
[camb]
file = ${COSMOSIS_STD_DIR}/boltzmann/camb/camb_interface.py
mode = background
feedback = 0
; We need quite fine redshift spacing, because the supernovae
; go down to low z where things are pretty sensitive
nz = 901
[bao]
file = _tests/cosmosis/BAOLikelihood.py
[fs]
file = _tests/cosmosis/FSLikelihood.py
[emcee]
walkers = 10
samples = 800
nsteps = 20
Writing _tests/config_bao_fs.ini
In this case the likelihood has nuisance parameters, to be copied in the input *values.ini file.
In [52]:
!cat _tests/cosmosis/FSLikelihood_values.ini
/bin/bash: /home/adematti/anaconda3/envs/cosmodesi/lib/libtinfo.so.6: no version information available (required by /bin/bash) [desi] sigmapar = 0.0 sigmaper = 0.0 b1 = 0.0 1.5 4.0
In [53]:
%%file _tests/values_bao_fs.ini
[desi]
sigmapar = 0.0
sigmaper = 0.0
b1 = 0.0 1.5 4.0
[cosmological_parameters]
; This is the only parameter being varied.
omega_m = 0.1 0.3 0.9
ombh2 = 0.02237
h0 = 0.6736
A_s = 2.083e-09
n_s = 0.9649
tau = 0.0544
mnu = 0.06
nnu = 3.046
num_massive_neutrinos = 1
omega_k = 0.0
w = -1.0
wa = 0.0
Writing _tests/values_bao_fs.ini
Let's sample!
In [54]:
!cosmosis _tests/config_bao_fs.ini
/bin/bash: /home/adematti/anaconda3/envs/cosmodesi/lib/libtinfo.so.6: no version information available (required by /bin/bash) WARNING:absl:No GPU/TPU found, falling back to CPU. (Set TF_CPP_MIN_LOG_LEVEL=0 and rerun for more info.) Parameter Priors ---------------- cosmological_parameters--omega_m ~ U(0.1, 0.9) cosmological_parameters--ombh2 ~ delta(0.02237) cosmological_parameters--h0 ~ delta(0.6736) cosmological_parameters--a_s ~ delta(2.083e-09) cosmological_parameters--n_s ~ delta(0.9649) cosmological_parameters--tau ~ delta(0.0544) cosmological_parameters--mnu ~ delta(0.06) cosmological_parameters--nnu ~ delta(3.046) cosmological_parameters--num_massive_neutrinos ~ delta(1) cosmological_parameters--omega_k ~ delta(0.0) cosmological_parameters--w ~ delta(-1.0) cosmological_parameters--wa ~ delta(0.0) desi--sigmapar ~ delta(0.0) desi--sigmaper ~ delta(0.0) desi--b1 ~ U(0.0, 4.0) **************************** * Running sampler 1/1: emcee * Saving output -> _tests/chains_bao_fs_cosmosis/chain.txt **************************** Begun sampling Done 20 iterations of emcee. Acceptance fraction 0.485 Done 40 iterations of emcee. Acceptance fraction 0.467 Done 60 iterations of emcee. Acceptance fraction 0.455 Done 80 iterations of emcee. Acceptance fraction 0.444 Done 100 iterations of emcee. Acceptance fraction 0.442 Done 120 iterations of emcee. Acceptance fraction 0.465 Done 140 iterations of emcee. Acceptance fraction 0.494 Done 160 iterations of emcee. Acceptance fraction 0.519 Done 180 iterations of emcee. Acceptance fraction 0.537 Done 200 iterations of emcee. Acceptance fraction 0.557 Done 220 iterations of emcee. Acceptance fraction 0.572 Done 240 iterations of emcee. Acceptance fraction 0.584 Done 260 iterations of emcee. Acceptance fraction 0.592 Done 280 iterations of emcee. Acceptance fraction 0.599 Done 300 iterations of emcee. Acceptance fraction 0.610 Done 320 iterations of emcee. Acceptance fraction 0.617 Done 340 iterations of emcee. Acceptance fraction 0.623 Done 360 iterations of emcee. Acceptance fraction 0.625 Done 380 iterations of emcee. Acceptance fraction 0.632 Done 400 iterations of emcee. Acceptance fraction 0.634 Done 420 iterations of emcee. Acceptance fraction 0.642 Done 440 iterations of emcee. Acceptance fraction 0.650 Done 460 iterations of emcee. Acceptance fraction 0.652 Done 480 iterations of emcee. Acceptance fraction 0.656 Done 500 iterations of emcee. Acceptance fraction 0.655
MontePython¶
In [56]:
!ls -la _tests/montepython/FSLikelihood
!cp -r _tests/montepython/FSLikelihood _tests/montepython_public/montepython/likelihoods/
/bin/bash: /home/adematti/anaconda3/envs/cosmodesi/lib/libtinfo.so.6: no version information available (required by /bin/bash) total 20 drwxr-xr-x 2 adematti idphp 4096 juil. 2 10:32 . drwxr-xr-x 4 adematti idphp 4096 juil. 2 10:32 .. -rw-r--r-- 1 adematti idphp 33 juil. 2 10:33 FSLikelihood.data -rw-r--r-- 1 adematti idphp 268 juil. 2 10:33 FSLikelihood.param -rw-r--r-- 1 adematti idphp 477 juil. 2 10:33 __init__.py /bin/bash: /home/adematti/anaconda3/envs/cosmodesi/lib/libtinfo.so.6: no version information available (required by /bin/bash)
In this case the likelihood has nuisance parameters, to be copied in the input *.param file.
In [57]:
!cat _tests/montepython/FSLikelihood/FSLikelihood.param
/bin/bash: /home/adematti/anaconda3/envs/cosmodesi/lib/libtinfo.so.6: no version information available (required by /bin/bash) # To be copy-pasted in the MontePython *.param file data.parameters['sigmapar'] = [0.0, 0.0, 10.0, 0.0, 1.0, 'nuisance'] data.parameters['sigmaper'] = [0.0, 0.0, 10.0, 0.0, 1.0, 'nuisance'] data.parameters['b1'] = [1.5, 0.0, 4.0, 0.28867513459481287, 1.0, 'nuisance']
In [58]:
%%file _tests/conf_bao_fs.param
data.experiments = ['BAOLikelihood', 'FSLikelihood']
# Cosmological parameters list
data.parameters['Omega_m'] = [0.3, 0.1, 0.9, 0.1, 1., 'cosmo']
# Fixed parameters
data.parameters['omega_b'] = [0.02237, 0.001, 0.1, 0., 1., 'cosmo']
data.parameters['H0'] = [67.36, 0.1, 0.9, 0., 1., 'cosmo']
data.parameters['A_s'] = [2.083e-09, 1e-09, 3e-09, 0., 1., 'cosmo']
data.parameters['n_s'] = [0.9649, 0.9, 1.0, 0., 1., 'cosmo']
data.parameters['tau_reio'] = [0.0544, 0.02, 0.1, 0., 1., 'cosmo']
# Nuisance parameters list
data.parameters['sigmapar'] = [0.0, 0.0, 10.0, 0.0, 1.0, 'nuisance']
data.parameters['sigmaper'] = [0.0, 0.0, 10.0, 0.0, 1.0, 'nuisance']
data.parameters['b1'] = [1.5, 0.0, 4.0, 0.28867513459481287, 1.0, 'nuisance']
# Cosmo arguments
data.cosmo_arguments['k_pivot'] = 0.05
# The base model features two massless
# and one massive neutrino with m=0.06eV.
# The settings below ensures that Neff=3.046
# and m/omega = 93.14 eV
data.cosmo_arguments['N_ur'] = 2.0328
data.cosmo_arguments['N_ncdm'] = 1
data.cosmo_arguments['m_ncdm'] = 0.06
data.cosmo_arguments['T_ncdm'] = 0.71611
#------ MCMC parameters ----
# Number of steps taken, by default (overwritten by the -N command)
data.N = 9000
# Number of accepted steps before writing to file the chain. Larger means less
# access to disc, but this is not so much time consuming.
data.write_step = 5
Writing _tests/conf_bao_fs.param
Let's sample!
In [59]:
!python _tests/montepython_public/montepython/MontePython.py run --conf _tests/montepython_public/default.conf -p _tests/conf_bao_fs.param -o _tests/chains_bao_fs_montepython
/bin/bash: /home/adematti/anaconda3/envs/cosmodesi/lib/libtinfo.so.6: no version information available (required by /bin/bash)
/!\ PyMultiNest detected but MultiNest likely not installed correctly. You can
safely ignore this if not running with option -m NS
Running Monte Python v3.6.0
with CLASS v3.2.0
Testing likelihoods for:
->BAOLikelihood, FSLikelihood
WARNING:absl:No GPU/TPU found, falling back to CPU. (Set TF_CPP_MIN_LOG_LEVEL=0 and rerun for more info.)
Creating _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt
Deduced starting covariance matrix:
['Omega_m', 'b1']
[[0.01 0. ]
[0. 0.08]]
Update routine is enabled with value 50 (recommended: 50)
This number is rescaled by cycle length 2 (N_slow + f_fast * N_fast) to 100
# -LogLkl Omega_m b1
/!\ PyMultiNest detected but MultiNest likely not installed correctly. You can
safely ignore this if not running with option -m NS
1 8711.4 3.000000e-01 1.621846e+00
2 174.297 3.000000e-01 2.266003e-01
22 53.5086 3.000000e-01 6.624145e-01
14 0.128235 3.000000e-01 5.022887e-01
14 -0.877214 3.000000e-01 5.117996e-01
28 -1.51021 3.000000e-01 5.249515e-01
8 0.661607 3.000000e-01 4.984443e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 3 points of burn-in, and first 50 percent, keep 1 steps
Step 90 chain 0 : Failed to calculate covariance matrix
/!\ PyMultiNest detected but MultiNest likely not installed correctly. You can
safely ignore this if not running with option -m NS
35 -1.4765 3.000000e-01 5.231471e-01
10 -1.78897 3.135776e-01 5.231471e-01
30 0.583581 3.213354e-01 5.231471e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 3 points of burn-in, and first 50 percent, keep 4 steps
Step 190 chain 0 : Failed to calculate covariance matrix
28 -2.14692 3.111806e-01 5.231471e-01
19 -2.2103 3.105647e-01 5.231471e-01
19 -2.58273 3.105647e-01 5.174114e-01
41 -1.65937 3.172893e-01 5.174114e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 3 points of burn-in, and first 50 percent, keep 4 steps
Step 290 chain 0 : Failed to calculate covariance matrix
21 -2.27128 3.172893e-01 5.113553e-01
81 -2.72205 3.135318e-01 5.113553e-01
13 -2.38692 3.135318e-01 4.889639e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 3 points of burn-in, and first 50 percent, keep 6 steps
/!\ Convergence computed for a single file
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.099171 for Omega_m
0.152791 for b1
--> Not computing covariance matrix
6 -1.08039 3.079173e-01 4.889639e-01
15 -2.57355 3.229237e-01 4.889639e-01
73 -2.41446 3.229237e-01 4.941567e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 3 points of burn-in, and first 50 percent, keep 9 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.762166 for Omega_m
0.227418 for b1
--> Computing covariance matrix
After 20 accepted steps: update proposal with max(R-1) = 0.762166 and jumping factor = 2.400000
16 -0.198255 3.308563e-01 4.941567e-01
1 0.269173 3.331269e-01 4.906302e-01
1 0.122175 3.331269e-01 4.894809e-01
4 -2.06522 3.163232e-01 5.155794e-01
1 -1.82068 3.059657e-01 5.316662e-01
1 -2.41079 3.059657e-01 5.189505e-01
2 -2.83301 3.121173e-01 5.093961e-01
2 -2.72094 3.197148e-01 4.975962e-01
4 -2.63538 3.084015e-01 5.151673e-01
2 -2.81726 3.176557e-01 5.007942e-01
3 -2.86978 3.150349e-01 5.048647e-01
4 -2.78399 3.150349e-01 4.929856e-01
1 -2.48015 3.150349e-01 4.873329e-01
1 -1.73945 3.284564e-01 4.664873e-01
1 -1.75524 3.284564e-01 4.850044e-01
1 -2.67847 3.092750e-01 5.147959e-01
3 -1.78269 3.092750e-01 4.918417e-01
1 -2.02488 3.219731e-01 4.721197e-01
2 -2.6075 3.219731e-01 4.925893e-01
1 -2.28852 3.219731e-01 4.995245e-01
1 -1.9185 3.253604e-01 4.942636e-01
1 -2.36331 3.253604e-01 4.819940e-01
1 -1.76992 3.298628e-01 4.750011e-01
2 -1.72151 3.298628e-01 4.688852e-01
1 -1.54832 3.298628e-01 4.825050e-01
1 -2.84839 3.154596e-01 5.048752e-01
1 -2.68635 3.154596e-01 5.089021e-01
1 -2.69775 3.143231e-01 5.106672e-01
1 -2.02753 3.143231e-01 5.196380e-01
1 -1.97856 3.160946e-01 5.168868e-01
1 -2.88856 3.160946e-01 4.948279e-01
1 -2.82494 3.123324e-01 5.006710e-01
2 -2.76043 3.123324e-01 4.985110e-01
1 -2.78416 3.123324e-01 5.111336e-01
1 -2.8091 3.143523e-01 5.079964e-01
2 -2.65632 3.143523e-01 4.915310e-01
1 -2.22919 3.143523e-01 4.853497e-01
1 -2.20022 3.205898e-01 4.756621e-01
1 -2.33525 3.205898e-01 4.775312e-01
1 -2.04697 3.089504e-01 4.956089e-01
1 -1.36037 3.089504e-01 4.887274e-01
1 -1.58635 3.237990e-01 4.656653e-01
1 -2.4905 3.237990e-01 4.877160e-01
1 -1.19841 2.984948e-01 5.270172e-01
3 -1.21519 2.984948e-01 5.281876e-01
1 -1.10185 2.979733e-01 5.289976e-01
1 -0.810813 2.979733e-01 5.204834e-01
3 -2.30022 3.066080e-01 5.070724e-01
1 -2.49176 3.066080e-01 5.150718e-01
3 -2.61849 3.079409e-01 5.130016e-01
1 -2.26864 3.079409e-01 5.016692e-01
2 -2.66508 3.143217e-01 4.917589e-01
3 -1.56472 3.027503e-01 5.097310e-01
1 -1.14098 3.027503e-01 5.403921e-01
2 -1.74653 3.122373e-01 5.256574e-01
2 -1.71702 3.147584e-01 5.217417e-01
1 -1.59707 3.175411e-01 5.174198e-01
1 -2.79804 3.175411e-01 4.897053e-01
3 -2.60881 3.101335e-01 5.012104e-01
2 -2.57811 3.101335e-01 5.005145e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 39 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.031991 for Omega_m
0.013889 for b1
--> Not computing covariance matrix
1 -1.93895 3.101335e-01 4.913420e-01
2 -2.21739 3.182281e-01 4.787699e-01
1 -2.03711 3.229024e-01 4.715100e-01
1 -2.49364 3.229024e-01 4.797388e-01
2 -2.72235 3.183170e-01 4.868606e-01
1 -2.69366 3.192768e-01 4.853700e-01
1 -2.7947 3.192768e-01 4.887888e-01
2 -2.29989 3.258307e-01 4.786096e-01
3 -1.53158 3.313979e-01 4.699629e-01
1 -0.771878 3.313979e-01 4.871602e-01
2 -0.103681 3.346447e-01 4.821175e-01
1 -2.42334 3.178278e-01 5.082366e-01
1 -2.71773 3.178278e-01 4.872532e-01
1 -2.72821 3.170955e-01 4.883906e-01
4 -1.69531 3.170955e-01 4.751416e-01
2 -2.69881 3.170955e-01 4.877407e-01
2 -2.78086 3.170955e-01 5.033364e-01
3 -1.24952 3.170955e-01 4.714638e-01
1 -0.978931 3.251948e-01 4.588844e-01
1 -1.98209 3.251948e-01 4.696616e-01
1 -0.995291 3.328695e-01 4.577417e-01
2 -1.26469 3.328695e-01 4.657235e-01
2 -1.26413 3.328695e-01 4.702373e-01
1 -1.23509 3.328695e-01 4.639778e-01
1 -2.6565 3.125135e-01 4.955938e-01
1 -2.75276 3.125135e-01 5.118628e-01
1 -2.74716 3.122632e-01 5.122514e-01
1 -2.85149 3.122632e-01 5.022127e-01
2 -2.49689 3.071813e-01 5.101057e-01
1 -2.86136 3.125325e-01 5.017945e-01
1 -2.75235 3.125325e-01 5.118542e-01
2 -2.72927 3.116448e-01 5.132329e-01
2 -2.76086 3.130136e-01 5.111069e-01
2 -1.90042 3.266461e-01 4.899336e-01
1 -2.71706 3.172449e-01 5.045351e-01
1 -2.66118 3.172449e-01 5.056897e-01
2 -2.43868 3.210611e-01 4.997625e-01
1 -2.71872 3.144238e-01 5.100712e-01
1 -2.7178 3.144238e-01 5.100906e-01
2 -2.57159 3.191130e-01 5.028076e-01
1 -1.93404 3.258488e-01 4.923459e-01
1 -2.2811 3.258488e-01 4.839058e-01
1 -2.02716 3.278339e-01 4.808227e-01
6 -1.95696 3.278339e-01 4.707396e-01
2 -0.857491 3.278339e-01 4.978995e-01
3 -0.626278 3.278339e-01 4.997837e-01
1 -0.382551 3.292355e-01 4.976067e-01
1 -1.46853 3.292355e-01 4.865920e-01
1 -2.54497 3.199658e-01 5.009893e-01
1 -0.975104 3.199658e-01 5.169600e-01
1 -1.33703 3.131144e-01 5.276011e-01
1 -2.89748 3.131144e-01 5.024811e-01
1 -2.6455 3.084686e-01 5.096967e-01
3 -2.18978 3.084686e-01 5.254041e-01
1 -1.2591 3.003120e-01 5.380726e-01
3 -1.22135 3.003120e-01 5.386877e-01
3 -0.363049 2.960085e-01 5.453716e-01
1 -0.392384 2.960085e-01 5.247159e-01
1 -2.14137 3.049283e-01 5.108621e-01
2 -2.06162 3.049283e-01 5.091126e-01
1 -2.29421 3.049283e-01 5.169806e-01
1 -2.53105 3.070251e-01 5.137240e-01
1 -2.50203 3.070251e-01 5.182989e-01
1 -2.52404 3.072663e-01 5.179242e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 69 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.017263 for Omega_m
0.002206 for b1
--> Not computing covariance matrix
1 -1.86645 3.072663e-01 5.303369e-01
2 -1.07973 3.004919e-01 5.408585e-01
2 -1.90993 3.180441e-01 5.135974e-01
1 -2.01418 3.158476e-01 5.170088e-01
5 -0.981019 3.158476e-01 5.252932e-01
1 -1.07248 3.108087e-01 5.331194e-01
1 -2.10508 3.108087e-01 5.240938e-01
1 -2.03892 3.090706e-01 5.267934e-01
1 -1.9274 3.090706e-01 5.280389e-01
5 -1.85933 3.179980e-01 5.141733e-01
1 -2.67289 3.179980e-01 5.036735e-01
2 -2.72954 3.163691e-01 5.062035e-01
1 -2.74994 3.131108e-01 5.112641e-01
3 -2.0632 3.131108e-01 5.212781e-01
1 -1.67403 3.050365e-01 5.338186e-01
1 -2.08268 3.050365e-01 5.090707e-01
3 -2.32723 3.070296e-01 5.059752e-01
2 -2.42606 3.070296e-01 5.211769e-01
1 -2.52951 3.070296e-01 5.162228e-01
2 -2.83374 3.115933e-01 5.091346e-01
1 -2.86151 3.171122e-01 5.005630e-01
1 -2.82608 3.171122e-01 5.019377e-01
2 -2.86318 3.147033e-01 5.056791e-01
1 -2.48738 3.226947e-01 4.932672e-01
1 -2.39295 3.226947e-01 4.954252e-01
1 -2.29383 3.236884e-01 4.938820e-01
4 -0.430854 3.236884e-01 4.563858e-01
1 -2.10081 3.236884e-01 4.719223e-01
3 -2.21814 3.120697e-01 4.899679e-01
1 -2.85059 3.120697e-01 5.029409e-01
1 -2.83271 3.192531e-01 4.917839e-01
1 -2.63517 3.192531e-01 4.840068e-01
2 -2.62688 3.132142e-01 4.933861e-01
1 -2.6188 3.130018e-01 4.937161e-01
1 -2.79495 3.130018e-01 4.977332e-01
1 -2.74177 3.200812e-01 4.867378e-01
2 -2.52726 3.200812e-01 4.811585e-01
2 -1.77511 3.200812e-01 5.103317e-01
1 -2.79047 3.200812e-01 4.900316e-01
2 -2.66132 3.221159e-01 4.868712e-01
1 -2.89116 3.173755e-01 4.942338e-01
2 -2.67999 3.173755e-01 5.050171e-01
1 -2.66203 3.173755e-01 5.053750e-01
1 -2.49199 3.079451e-01 5.200219e-01
1 -2.60424 3.079451e-01 5.154988e-01
1 -2.6837 3.089870e-01 5.138805e-01
1 -2.32634 3.089870e-01 4.993570e-01
1 -1.19651 3.009962e-01 5.117680e-01
4 -1.71019 3.009962e-01 5.252293e-01
2 -1.27029 3.009962e-01 5.128181e-01
2 -1.13115 3.009962e-01 5.108982e-01
1 -0.702957 3.009962e-01 5.061118e-01
1 -1.21259 3.037827e-01 5.017840e-01
2 -1.49685 3.037827e-01 5.049368e-01
1 -2.12397 3.037827e-01 5.175600e-01
2 -2.9093 3.134981e-01 5.024705e-01
2 -2.62503 3.081442e-01 5.107859e-01
3 -2.56437 3.231990e-01 4.874035e-01
1 -2.54585 3.231990e-01 4.887154e-01
1 -2.36806 3.249687e-01 4.859668e-01
1 -2.04979 3.249687e-01 4.707623e-01
1 -2.2796 3.119799e-01 4.909358e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 101 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.023649 for Omega_m
0.051105 for b1
--> Not computing covariance matrix
1 -2.85466 3.119799e-01 5.036656e-01
2 -2.66876 3.088596e-01 5.085120e-01
1 -2.91703 3.162909e-01 4.969700e-01
1 -2.84533 3.162909e-01 5.032474e-01
1 -2.72252 3.097757e-01 5.133666e-01
1 -2.64501 3.097757e-01 5.033794e-01
2 -2.7387 3.204179e-01 4.868504e-01
1 -2.83698 3.137743e-01 4.971689e-01
1 -2.88888 3.137743e-01 4.994410e-01
1 -2.87842 3.177412e-01 4.932798e-01
2 -2.8874 3.177412e-01 4.943487e-01
1 -2.6307 3.177412e-01 5.051232e-01
1 -1.84285 3.023012e-01 5.291039e-01
3 -1.70818 3.023012e-01 5.142449e-01
1 -2.61967 3.097976e-01 5.026019e-01
1 -2.70458 3.097976e-01 5.142262e-01
2 -2.7397 3.185632e-01 5.006120e-01
2 -2.51136 3.220042e-01 4.952676e-01
3 -2.82755 3.132213e-01 5.089088e-01
3 -2.89773 3.132213e-01 5.019970e-01
2 -2.75492 3.207495e-01 4.903046e-01
1 -2.69777 3.091865e-01 5.082636e-01
2 -2.33822 3.091865e-01 4.989561e-01
2 -2.48787 3.091865e-01 5.200965e-01
1 -2.30184 3.091865e-01 4.983910e-01
1 -2.5989 3.146958e-01 4.898342e-01
2 -2.83472 3.146958e-01 4.950858e-01
1 -1.87796 3.146958e-01 5.204218e-01
1 -1.62106 3.196067e-01 5.127945e-01
3 -2.56062 3.196067e-01 5.016906e-01
1 -2.6792 3.172100e-01 5.054130e-01
1 -2.69581 3.172100e-01 4.875231e-01
1 -2.6646 3.188047e-01 4.850463e-01
1 -2.8371 3.188047e-01 4.909606e-01
1 -2.81221 3.194254e-01 4.899966e-01
3 -2.81084 3.194254e-01 4.947363e-01
1 -2.88183 3.176697e-01 4.974631e-01
2 -2.49238 3.176697e-01 5.075916e-01
1 -2.89188 3.176697e-01 4.951344e-01
1 -2.90309 3.134320e-01 5.017162e-01
2 -2.59806 3.134320e-01 4.923899e-01
2 -2.63323 3.134320e-01 4.930226e-01
1 -2.85435 3.134320e-01 4.986806e-01
2 -2.86604 3.139278e-01 4.979106e-01
1 -2.84328 3.130479e-01 4.992772e-01
4 -2.59704 3.130479e-01 5.144532e-01
3 -2.85514 3.130479e-01 5.079827e-01
4 -2.78311 3.108239e-01 5.114369e-01
1 -2.80798 3.114101e-01 5.105264e-01
1 -1.32268 3.114101e-01 5.303859e-01
2 -0.869705 3.208461e-01 5.157304e-01
2 -1.21355 3.163769e-01 5.226718e-01
1 -1.32519 3.122280e-01 5.291157e-01
1 -1.03271 3.122280e-01 5.312298e-01
1 -1.03316 3.114334e-01 5.324639e-01
1 -1.73721 3.114334e-01 5.269284e-01
1 -1.7426 3.119664e-01 5.261006e-01
2 -2.10416 3.119664e-01 5.225597e-01
1 -2.78334 3.119664e-01 5.114115e-01
1 -2.67135 3.194517e-01 4.997856e-01
1 -2.80128 3.194517e-01 4.892728e-01
2 -2.86782 3.140881e-01 4.976034e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 131 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000178 for Omega_m
0.004217 for b1
--> Not computing covariance matrix
10 -2.86893 3.141483e-01 4.975098e-01
4 -2.84837 3.181254e-01 4.913328e-01
1 -2.55579 3.232905e-01 4.833106e-01
1 -2.16387 3.232905e-01 4.974067e-01
1 -1.82559 3.261094e-01 4.930286e-01
1 -2.27369 3.261094e-01 4.817043e-01
2 -1.71716 3.301371e-01 4.754487e-01
1 -2.85779 3.186896e-01 4.932282e-01
2 -2.83864 3.186896e-01 4.963415e-01
1 -2.27778 3.186896e-01 4.788936e-01
3 -1.28525 3.306641e-01 4.602954e-01
2 -0.813053 3.306641e-01 4.542723e-01
2 -1.52351 3.306641e-01 4.650645e-01
2 -1.40069 3.306641e-01 4.623110e-01
1 -1.61213 3.306641e-01 4.757707e-01
1 -1.44749 3.316356e-01 4.742618e-01
1 -1.47326 3.316356e-01 4.728745e-01
2 -1.21739 3.330660e-01 4.706529e-01
2 1.66636 3.451358e-01 4.519067e-01
3 5.76347 3.573801e-01 4.328895e-01
2 5.73255 3.573801e-01 4.154388e-01
1 5.95807 3.573801e-01 4.114964e-01
1 5.66174 3.565255e-01 4.128236e-01
1 5.29386 3.565255e-01 4.303529e-01
1 -1.79693 3.296793e-01 4.720490e-01
1 -1.66812 3.296793e-01 4.666365e-01
1 -2.15618 3.256221e-01 4.729380e-01
1 -2.33469 3.256221e-01 4.806718e-01
5 -2.79894 3.197899e-01 4.897301e-01
1 -2.79491 3.197899e-01 4.939291e-01
1 -2.81238 3.194548e-01 4.944496e-01
1 -2.82383 3.194548e-01 4.930118e-01
2 -2.87922 3.124179e-01 5.039411e-01
1 -2.87676 3.123459e-01 5.040530e-01
1 -1.78844 3.123459e-01 4.848122e-01
1 -1.93927 3.176194e-01 4.766216e-01
1 -2.82947 3.176194e-01 5.004533e-01
1 -2.84341 3.122046e-01 5.088632e-01
1 -2.87414 3.122046e-01 5.060882e-01
1 -2.28795 3.048539e-01 5.175050e-01
4 -2.06911 3.048539e-01 5.278758e-01
2 -2.06683 3.048539e-01 5.279218e-01
3 -2.28873 3.048539e-01 5.199198e-01
1 -2.88002 3.135913e-01 5.063493e-01
3 -1.91103 3.135913e-01 5.220047e-01
1 -1.91519 3.129551e-01 5.229930e-01
3 -2.28925 3.129551e-01 5.189907e-01
2 -2.28968 3.131216e-01 5.187320e-01
1 -1.64598 3.238124e-01 5.021275e-01
4 -1.46663 3.238124e-01 5.038496e-01
1 -1.47602 3.238124e-01 5.037634e-01
1 -2.14733 3.129711e-01 5.206016e-01
1 -1.84005 3.129711e-01 5.236710e-01
2 -1.47653 3.205034e-01 5.119722e-01
1 -1.66627 3.073423e-01 5.324133e-01
1 -1.6127 3.073423e-01 5.329419e-01
1 -1.6988 3.088862e-01 5.305441e-01
2 -2.62999 3.088862e-01 5.163483e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 161 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.001871 for Omega_m
0.001055 for b1
--> Not computing covariance matrix
1 -2.62148 3.088862e-01 5.062140e-01
1 -1.66088 3.014932e-01 5.176963e-01
1 -1.75797 3.014932e-01 5.210383e-01
4 -1.53744 3.002898e-01 5.229074e-01
1 -2.914 3.137615e-01 5.019839e-01
2 -2.83147 3.137615e-01 4.970114e-01
1 -1.54889 3.137615e-01 4.798137e-01
2 -1.3472 3.106547e-01 4.846390e-01
1 -1.15558 3.086621e-01 4.877338e-01
1 -2.17549 3.086621e-01 4.980739e-01
4 -1.64121 3.043409e-01 5.047854e-01
1 -1.59253 3.040247e-01 5.052765e-01
1 -1.7159 3.040247e-01 5.334395e-01
1 -1.21565 3.004782e-01 5.389477e-01
1 -1.61308 3.004782e-01 5.280555e-01
2 -0.798015 2.965807e-01 5.341089e-01
1 -2.82436 3.122677e-01 5.097447e-01
2 -1.37374 3.122677e-01 5.286834e-01
1 -0.836582 3.122677e-01 5.324885e-01
2 -0.312465 3.025335e-01 5.476071e-01
1 -0.641672 3.060094e-01 5.422085e-01
1 -2.19203 3.060094e-01 5.260396e-01
1 -2.29153 3.071183e-01 5.243174e-01
4 -2.43295 3.071183e-01 5.210657e-01
1 -1.9383 3.071183e-01 4.995075e-01
3 -2.47851 3.154226e-01 4.866097e-01
2 -2.72705 3.154226e-01 4.909456e-01
1 -2.59346 3.154226e-01 4.884073e-01
1 -2.31518 3.095735e-01 4.974919e-01
4 -2.68129 3.095735e-01 5.053958e-01
1 -2.67162 3.095735e-01 5.050316e-01
1 -2.67138 3.218518e-01 4.859615e-01
1 -2.25797 3.218518e-01 5.003335e-01
2 -2.40123 3.200879e-01 5.030731e-01
2 -2.0354 3.240236e-01 4.969604e-01
2 -1.97838 3.245128e-01 4.962007e-01
1 -2.54021 3.101075e-01 5.185743e-01
3 -2.76899 3.101075e-01 5.075524e-01
2 -2.91535 3.138644e-01 5.017173e-01
1 -2.53909 3.072387e-01 5.120080e-01
1 -2.36472 3.072387e-01 5.228386e-01
1 -2.6353 3.144377e-01 5.116576e-01
1 -1.95333 3.144377e-01 5.201663e-01
1 -1.82696 3.176960e-01 5.151055e-01
1 0.605125 3.176960e-01 5.307920e-01
1 0.505574 3.163959e-01 5.328113e-01
1 0.946785 3.163959e-01 5.349582e-01
1 0.739324 3.119077e-01 5.419290e-01
5 -0.69492 3.119077e-01 5.339794e-01
2 -0.687161 3.126802e-01 5.327796e-01
1 -0.623353 3.080712e-01 5.399380e-01
1 0.0876989 3.080712e-01 5.442937e-01
1 0.039644 3.103778e-01 5.407113e-01
1 -2.75623 3.103778e-01 5.123985e-01
2 -2.81718 3.118202e-01 5.101583e-01
1 -1.51373 2.999336e-01 5.286200e-01
1 -1.50446 2.999336e-01 5.297837e-01
1 -2.82829 3.149066e-01 5.065284e-01
2 -2.84009 3.149066e-01 5.061559e-01
1 -2.24929 3.149066e-01 4.845432e-01
2 -2.23204 3.198104e-01 4.769269e-01
1 -2.22991 3.142306e-01 4.855932e-01
1 -2.72761 3.142306e-01 4.932267e-01
1 -2.71731 3.185422e-01 4.865301e-01
1 -2.79971 3.185422e-01 4.987775e-01
1 -2.80414 3.110327e-01 5.104409e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 194 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000222 for Omega_m
0.001046 for b1
--> Not computing covariance matrix
4 -2.57779 3.110327e-01 4.978800e-01
1 -2.79949 3.110327e-01 5.043690e-01
1 -2.8278 3.116050e-01 5.034803e-01
3 -2.44245 3.116050e-01 4.940838e-01
1 -2.45648 3.213206e-01 4.789939e-01
2 -2.67198 3.213206e-01 4.847147e-01
2 -2.50699 3.213206e-01 4.800009e-01
1 -0.938533 3.213206e-01 5.141761e-01
1 -1.17653 3.187174e-01 5.182193e-01
1 -2.73314 3.187174e-01 4.868063e-01
1 -2.27061 3.255922e-01 4.761287e-01
2 -2.26012 3.255922e-01 4.864834e-01
2 0.164055 3.255922e-01 5.110017e-01
1 -1.93081 3.255922e-01 4.932959e-01
1 -2.63735 3.170663e-01 5.065379e-01
1 -2.50378 3.170663e-01 4.843047e-01
2 -2.19131 3.241848e-01 4.732486e-01
1 -2.48867 3.150282e-01 4.874700e-01
1 -2.87473 3.150282e-01 4.959021e-01
1 -2.16786 3.049137e-01 5.116114e-01
1 -2.22588 3.049137e-01 5.133915e-01
1 -2.90086 3.167204e-01 4.950539e-01
2 -2.77041 3.167204e-01 4.899173e-01
1 -1.96813 3.167204e-01 4.783351e-01
3 -1.82596 3.225131e-01 4.693383e-01
3 -1.92415 3.225131e-01 4.704409e-01
6 -2.06529 3.186802e-01 4.763940e-01
1 -1.91913 3.120951e-01 4.866216e-01
1 -2.78049 3.120951e-01 5.114233e-01
1 -2.76926 3.170775e-01 5.036848e-01
1 -1.97039 3.170775e-01 5.150233e-01
1 -1.84937 3.190832e-01 5.119081e-01
3 -2.78935 3.190832e-01 4.973433e-01
1 -2.64653 3.213793e-01 4.937771e-01
5 -2.39786 3.213793e-01 4.779011e-01
2 -2.27934 3.232629e-01 4.749756e-01
1 -2.17458 3.245740e-01 4.729392e-01
1 -1.27137 3.245740e-01 5.035462e-01
1 -1.37688 3.237439e-01 5.048355e-01
1 -1.40192 3.237439e-01 5.046147e-01
2 -2.02834 3.158159e-01 5.169282e-01
1 -1.58273 3.221569e-01 5.070797e-01
2 -2.62301 3.221569e-01 4.910004e-01
1 -2.5934 3.221569e-01 4.824290e-01
2 -2.80155 3.149158e-01 4.936755e-01
5 -2.77899 3.137557e-01 4.954773e-01
1 -2.47388 3.137557e-01 5.153241e-01
2 -2.31489 3.084702e-01 5.235332e-01
1 -2.47394 3.137285e-01 5.153664e-01
1 -2.91418 3.137285e-01 5.029795e-01
2 -1.91425 3.023237e-01 5.206928e-01
4 -1.17529 2.984200e-01 5.267558e-01
3 -1.25972 2.988147e-01 5.261428e-01
1 -1.26643 2.988147e-01 5.329482e-01
3 -1.15743 2.982842e-01 5.337720e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 221 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000097 for Omega_m
0.000604 for b1
--> Not computing covariance matrix
3 -1.15033 2.982842e-01 5.272087e-01
3 -1.4872 2.999133e-01 5.246786e-01
1 -0.397815 2.999133e-01 5.070446e-01
1 -2.15914 3.141577e-01 4.849209e-01
1 -2.10431 3.141577e-01 5.191355e-01
1 -1.89262 3.070390e-01 5.301918e-01
4 -1.7249 3.070390e-01 5.320661e-01
2 -2.39851 3.070390e-01 5.076186e-01
1 -2.43466 3.070390e-01 5.086408e-01
4 -2.51634 3.078492e-01 5.073826e-01
1 -2.77101 3.112971e-01 5.020274e-01
2 -2.83732 3.112971e-01 5.062741e-01
1 -2.36159 3.112971e-01 5.203156e-01
1 -2.34662 3.107811e-01 5.211171e-01
1 -1.82889 3.107811e-01 4.886678e-01
1 -1.68225 3.257560e-01 4.654095e-01
1 -1.98643 3.257560e-01 4.697023e-01
1 -2.37792 3.138498e-01 4.881944e-01
2 -2.787 3.138498e-01 5.093449e-01
2 -2.46413 3.138498e-01 4.893920e-01
1 -2.22548 3.138498e-01 4.862884e-01
1 -2.27819 3.180293e-01 4.797972e-01
1 -2.80536 3.180293e-01 5.001445e-01
1 -2.7692 3.188522e-01 4.988664e-01
2 -2.81833 3.188522e-01 4.968677e-01
3 -2.42899 3.188522e-01 5.057790e-01
5 -1.70777 3.261549e-01 4.944368e-01
1 -2.10564 3.261549e-01 4.879595e-01
1 -2.45058 3.230621e-01 4.927632e-01
1 -2.07659 3.230621e-01 4.719253e-01
1 -2.05234 3.234169e-01 4.713742e-01
3 -2.4727 3.234169e-01 4.905796e-01
4 -2.08705 3.267916e-01 4.853381e-01
1 -1.84671 3.285049e-01 4.826772e-01
3 -1.87745 3.285049e-01 4.698756e-01
1 -1.46268 3.313688e-01 4.654275e-01
1 -1.53213 3.313688e-01 4.692612e-01
1 -1.12886 3.336756e-01 4.656785e-01
1 -0.727217 3.336756e-01 4.785625e-01
2 -1.90147 3.268306e-01 4.891938e-01
1 -1.67412 3.283908e-01 4.867706e-01
1 -0.57477 3.283908e-01 4.985830e-01
1 -1.3554 3.030021e-01 5.380154e-01
3 -2.01052 3.030021e-01 5.253289e-01
1 -0.992796 2.974560e-01 5.339427e-01
1 -0.624575 2.974560e-01 5.440531e-01
3 -0.179542 2.954578e-01 5.471566e-01
1 -0.0114715 2.954578e-01 5.218215e-01
1 -2.1631 3.065702e-01 5.045624e-01
2 -2.48637 3.065702e-01 5.165610e-01
2 -1.37811 3.065702e-01 4.950660e-01
1 0.0884683 3.065702e-01 4.841155e-01
1 -0.0445494 3.075416e-01 4.826067e-01
2 -2.2343 3.075416e-01 5.024102e-01
2 -2.57442 3.075416e-01 5.156947e-01
1 -1.86359 3.075416e-01 4.973594e-01
2 -1.77292 3.067743e-01 4.985513e-01
1 -1.84375 3.267794e-01 4.674804e-01
2 -2.08821 3.267794e-01 4.853701e-01
3 -2.05682 3.267794e-01 4.717044e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 251 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000799 for Omega_m
0.000527 for b1
--> Not computing covariance matrix
2 -2.4886 3.217884e-01 4.794562e-01
1 -1.14698 3.331151e-01 4.618641e-01
3 -1.22997 3.331151e-01 4.687292e-01
3 -2.06988 3.278015e-01 4.769819e-01
1 -2.05073 3.278015e-01 4.744737e-01
1 -2.83424 3.155323e-01 4.935296e-01
1 -1.06867 3.155323e-01 4.727869e-01
1 -0.677918 3.095966e-01 4.820058e-01
1 -0.686503 3.095966e-01 4.820652e-01
3 -1.03698 3.220104e-01 4.627847e-01
4 -1.08912 3.220104e-01 4.631895e-01
2 -2.43732 3.220104e-01 4.783218e-01
3 -2.5366 3.220104e-01 4.946153e-01
3 -2.64995 3.205238e-01 4.969243e-01
1 -2.28965 3.205238e-01 5.035327e-01
4 -2.55058 3.148917e-01 5.122801e-01
1 -2.52324 3.161723e-01 5.102911e-01
2 -2.91965 3.161723e-01 4.974359e-01
1 -2.48754 3.161723e-01 4.854612e-01
1 -1.72813 3.054599e-01 5.020991e-01
1 -1.74998 3.054599e-01 5.023704e-01
4 -2.42058 3.128313e-01 4.909215e-01
1 -1.76975 3.056043e-01 5.021462e-01
2 -2.06572 3.056043e-01 5.064574e-01
1 -2.3729 3.056043e-01 5.154933e-01
1 -2.92568 3.149881e-01 5.009189e-01
1 -2.73826 3.149881e-01 4.919788e-01
1 -2.4519 3.091445e-01 5.010549e-01
1 -0.466288 3.091445e-01 4.815978e-01
1 -0.530498 3.097559e-01 4.806482e-01
1 -1.04048 3.097559e-01 4.842628e-01
2 -1.1731 3.112685e-01 4.819135e-01
1 -0.269166 3.327263e-01 4.485864e-01
1 -1.10897 3.327263e-01 4.766219e-01
2 -2.34023 3.245459e-01 4.893273e-01
2 -2.63586 3.213428e-01 4.943021e-01
2 -2.88771 3.148376e-01 5.044057e-01
1 -2.66962 3.208776e-01 4.950247e-01
1 -2.58734 3.208776e-01 4.973367e-01
1 -2.80045 3.165589e-01 5.040443e-01
1 -2.66599 3.165589e-01 4.878450e-01
1 -2.63781 3.141662e-01 4.915612e-01
1 -2.32763 3.141662e-01 4.869125e-01
3 -1.90106 3.080048e-01 4.964820e-01
2 -1.69369 3.080048e-01 5.315210e-01
1 -1.89543 3.080048e-01 4.964171e-01
1 -2.00598 3.091034e-01 4.947108e-01
1 -2.70674 3.091034e-01 5.122398e-01
3 -2.87127 3.124251e-01 5.070807e-01
1 -2.83933 3.124251e-01 5.090300e-01
2 -2.65558 3.086961e-01 5.148218e-01
1 -2.12003 3.036202e-01 5.227054e-01
1 -2.11249 3.036202e-01 5.233975e-01
1 -2.63617 3.086013e-01 5.156610e-01
1 -2.61908 3.086013e-01 5.164375e-01
1 -2.71863 3.102212e-01 5.139217e-01
2 -2.57606 3.102212e-01 5.177748e-01
1 -2.43312 3.102212e-01 4.975375e-01
1 -2.45256 3.224363e-01 4.785656e-01
1 -2.11548 3.224363e-01 4.728888e-01
1 -2.10645 3.116033e-01 4.897140e-01
1 -1.58395 3.116033e-01 4.845488e-01
2 -1.78661 3.186655e-01 4.735802e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 284 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.002006 for Omega_m
0.000231 for b1
--> Not computing covariance matrix
4 -1.26331 3.081193e-01 4.899600e-01
5 -0.83538 3.049325e-01 4.949095e-01
3 -2.01993 3.049325e-01 5.082965e-01
4 -2.11183 3.056192e-01 5.072300e-01
6 -2.03876 3.050695e-01 5.080837e-01
1 -2.23528 3.066250e-01 5.056679e-01
1 -2.34371 3.066250e-01 5.080266e-01
2 -2.22101 3.056004e-01 5.096180e-01
1 -2.3884 3.070295e-01 5.073984e-01
1 -2.11808 3.070295e-01 5.022633e-01
1 -0.843718 2.993362e-01 5.142122e-01
1 -0.895551 2.993362e-01 5.149135e-01
2 -2.21158 3.074672e-01 5.022847e-01
2 -2.67315 3.176087e-01 4.865334e-01
1 -2.37011 3.238036e-01 4.769119e-01
1 -2.11097 3.238036e-01 4.965732e-01
1 -1.48533 3.284509e-01 4.893553e-01
1 -0.943811 3.284509e-01 4.952711e-01
1 -2.22789 3.155535e-01 5.153028e-01
1 -1.33512 3.155535e-01 5.233390e-01
3 -1.27873 3.076512e-01 5.356124e-01
1 0.404423 3.076512e-01 4.796519e-01
1 -0.314844 3.184062e-01 4.629478e-01
1 -1.88672 3.184062e-01 4.749239e-01
1 -1.85491 3.149789e-01 4.802469e-01
1 -1.03673 3.149789e-01 4.735507e-01
1 -1.02477 3.146716e-01 4.740281e-01
1 -2.91856 3.146716e-01 5.025115e-01
1 -2.88515 3.125957e-01 5.057357e-01
1 -2.80673 3.125957e-01 5.101944e-01
4 -2.50528 3.071819e-01 5.186028e-01
1 -1.54114 3.296273e-01 4.837418e-01
2 -1.29614 3.296273e-01 4.874792e-01
1 -1.25469 3.296273e-01 4.880129e-01
1 -2.62988 3.152075e-01 5.104090e-01
1 -2.91314 3.152075e-01 5.022143e-01
1 -2.09704 3.269879e-01 4.839176e-01
2 -1.72238 3.269879e-01 4.656423e-01
2 -2.15341 3.269879e-01 4.813749e-01
1 -1.78279 3.269879e-01 4.905196e-01
1 -2.57686 3.092339e-01 5.180941e-01
1 -2.70005 3.092339e-01 5.135281e-01
2 -2.83889 3.120869e-01 5.090970e-01
1 -2.81949 3.115247e-01 5.099702e-01
1 -1.84256 3.115247e-01 5.258286e-01
1 -1.37243 3.216817e-01 5.100532e-01
1 -0.856866 3.216817e-01 5.139121e-01
2 1.05489 3.330089e-01 4.963195e-01
3 -1.32709 3.154482e-01 5.235938e-01
1 -2.82771 3.154482e-01 4.934684e-01
1 -2.56823 3.227153e-01 4.821815e-01
1 -2.6074 3.227153e-01 4.880402e-01
1 -2.89827 3.130409e-01 5.030659e-01
1 -2.81906 3.130409e-01 5.093805e-01
2 -2.77947 3.174199e-01 5.025793e-01
1 -2.66689 3.092499e-01 5.152685e-01
1 -2.57836 3.092499e-01 5.034715e-01
1 -2.8173 3.178888e-01 4.900540e-01
1 -2.88477 3.178888e-01 4.944566e-01
1 -2.75484 3.207571e-01 4.900018e-01
1 -0.958001 3.207571e-01 4.638111e-01
1 -0.972692 3.201408e-01 4.647682e-01
2 -0.911495 3.201408e-01 4.643240e-01
2 -2.20875 3.201408e-01 4.762545e-01
1 -1.93541 3.201408e-01 4.730904e-01
1 -1.54711 3.262617e-01 4.635837e-01
1 -2.24172 3.262617e-01 4.771787e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 316 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.001302 for Omega_m
0.000446 for b1
--> Not computing covariance matrix
2 -1.35543 3.324146e-01 4.676223e-01
1 -2.3277 3.254760e-01 4.783989e-01
1 -1.29568 3.254760e-01 4.614522e-01
1 -1.35204 3.109632e-01 4.839928e-01
2 -2.67625 3.109632e-01 5.150489e-01
1 -2.18493 3.109632e-01 5.229780e-01
1 -2.11752 3.091792e-01 5.257488e-01
1 -1.90495 3.091792e-01 4.933719e-01
2 -1.64682 3.068163e-01 4.970419e-01
2 -1.46041 3.054189e-01 4.992121e-01
1 -1.95637 3.097459e-01 4.924918e-01
1 -1.7985 3.097459e-01 4.908322e-01
2 -1.81333 3.099140e-01 4.905710e-01
1 -0.979901 3.034286e-01 5.006439e-01
2 -1.06423 3.034286e-01 5.014468e-01
1 -0.791091 3.034286e-01 4.989471e-01
1 -1.73565 3.111088e-01 4.870186e-01
1 -2.53668 3.111088e-01 4.969038e-01
1 -2.6946 3.168012e-01 4.880625e-01
1 -2.62916 3.168012e-01 5.072627e-01
1 -2.31003 3.219456e-01 4.992728e-01
2 -2.67358 3.219456e-01 4.884311e-01
1 -2.38434 3.219456e-01 4.980381e-01
1 -1.86783 3.023597e-01 5.284580e-01
2 -1.93662 3.023597e-01 5.242363e-01
1 -1.92386 3.023597e-01 5.256799e-01
1 -2.68674 3.094579e-01 5.146553e-01
1 -2.31269 3.094579e-01 5.228872e-01
1 -2.10057 3.207357e-01 5.053712e-01
1 -2.06879 3.207357e-01 5.057379e-01
1 -1.34044 3.269345e-01 4.961102e-01
2 -1.80208 3.269345e-01 4.904235e-01
1 -1.89321 3.269345e-01 4.889249e-01
2 -2.33281 3.232672e-01 4.946207e-01
2 -2.61072 3.199007e-01 4.998494e-01
2 -2.47748 3.071455e-01 5.196601e-01
1 -2.72373 3.109503e-01 5.137507e-01
1 -2.31132 3.109503e-01 5.214056e-01
1 -1.67281 3.029911e-01 5.337675e-01
2 -1.96904 3.029911e-01 5.271613e-01
2 -2.03445 3.029911e-01 5.213680e-01
1 -1.89145 3.029911e-01 5.147597e-01
1 -2.00145 3.282978e-01 4.754546e-01
2 -1.98778 3.282978e-01 4.785995e-01
1 -0.358964 3.282978e-01 5.004816e-01
2 -1.122 3.231249e-01 5.085159e-01
1 -1.29398 3.215940e-01 5.108936e-01
4 -1.81482 3.215940e-01 5.062853e-01
1 -2.61613 3.215940e-01 4.939293e-01
1 -2.76603 3.102301e-01 5.115790e-01
1 -2.70993 3.102301e-01 5.142421e-01
1 -2.80107 3.128901e-01 5.101109e-01
1 -2.25076 3.128901e-01 5.195502e-01
1 -1.94619 3.061858e-01 5.299630e-01
1 -2.44702 3.061858e-01 5.157965e-01
3 -2.13024 3.036665e-01 5.197094e-01
1 -1.94026 3.036665e-01 5.294237e-01
2 -1.5215 3.008350e-01 5.338214e-01
2 -1.67676 3.018011e-01 5.323209e-01
2 -1.77827 3.024807e-01 5.312654e-01
2 -1.07251 2.984021e-01 5.376000e-01
1 -1.0376 2.982302e-01 5.378670e-01
2 -1.13616 2.982302e-01 5.271671e-01
1 -0.716038 2.982302e-01 5.176093e-01
2 -1.48937 3.019971e-01 5.117588e-01
1 -1.90682 3.045778e-01 5.077506e-01
1 -0.971584 3.045778e-01 4.970797e-01
2 -1.94418 3.190757e-01 4.745623e-01
3 -1.91973 3.147927e-01 4.812145e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 351 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.002483 for Omega_m
0.001701 for b1
--> Not computing covariance matrix
4 -2.65805 3.147927e-01 4.907074e-01
4 -2.89319 3.147927e-01 5.041978e-01
1 -2.91303 3.147927e-01 5.029005e-01
2 -2.91257 3.146108e-01 5.031830e-01
2 -2.6136 3.078875e-01 5.136252e-01
3 -2.46509 3.063464e-01 5.160188e-01
1 -2.31811 3.063464e-01 5.086200e-01
2 -1.66032 3.018491e-01 5.156050e-01
1 -2.83438 3.137695e-01 4.970910e-01
2 -2.90751 3.137695e-01 5.008971e-01
3 -2.82674 3.137695e-01 5.082959e-01
1 -1.47313 2.997679e-01 5.300424e-01
2 -1.41502 2.997679e-01 5.228912e-01
1 -1.16704 2.997679e-01 5.388782e-01
5 -1.97749 3.057153e-01 5.296410e-01
2 -2.06141 3.057153e-01 5.283305e-01
2 -1.06398 3.057153e-01 5.392913e-01
1 -2.31866 3.057153e-01 5.118322e-01
2 -2.87482 3.178240e-01 4.930256e-01
1 -2.81148 3.195742e-01 4.903074e-01
2 -2.75143 3.195742e-01 4.970528e-01
1 -2.6007 3.195742e-01 5.009982e-01
1 -2.17427 3.044520e-01 5.244852e-01
1 -2.21264 3.044520e-01 5.227471e-01
2 -1.94638 3.025348e-01 5.257248e-01
1 -2.41382 3.062118e-01 5.200139e-01
1 -2.4418 3.062118e-01 5.144846e-01
2 -1.30888 2.990649e-01 5.255847e-01
1 -0.812825 2.968469e-01 5.290296e-01
2 -0.853491 2.968469e-01 5.349951e-01
3 -0.035645 2.968469e-01 5.508167e-01
1 -1.55747 3.097103e-01 5.308380e-01
1 -2.13848 3.097103e-01 4.947151e-01
1 -2.078 3.090319e-01 4.957688e-01
1 -2.55333 3.090319e-01 5.036272e-01
3 -2.74898 3.197788e-01 4.869356e-01
1 -2.719 3.197788e-01 4.858766e-01
1 -2.52679 3.229782e-01 4.809075e-01
3 -2.48996 3.229782e-01 4.796816e-01
3 -2.74697 3.153004e-01 4.916063e-01
1 -2.72363 3.153004e-01 5.084423e-01
2 -2.71211 3.123279e-01 5.130589e-01
1 -2.70914 3.121961e-01 5.132637e-01
2 -2.3798 3.121961e-01 4.917746e-01
2 -2.82605 3.121961e-01 5.096986e-01
1 -2.67257 3.121961e-01 4.967240e-01
2 -2.75996 3.153303e-01 4.918562e-01
1 -2.71831 3.133476e-01 4.949357e-01
1 -1.98276 3.133476e-01 4.846413e-01
3 0.0996424 3.376484e-01 4.468985e-01
1 0.351411 3.376484e-01 4.435781e-01
1 -1.7273 3.163617e-01 4.766394e-01
1 -2.66707 3.163617e-01 4.881682e-01
1 -2.21517 3.253834e-01 4.741562e-01
1 -2.3592 3.253834e-01 4.823994e-01
2 -2.63777 3.224326e-01 4.869824e-01
1 -2.81269 3.111886e-01 5.044460e-01
2 -1.85462 3.111886e-01 5.261849e-01
2 -0.0648706 3.111886e-01 5.388756e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 381 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.005295 for Omega_m
0.001232 for b1
--> Not computing covariance matrix
1 -0.201356 3.111886e-01 5.380988e-01
1 0.0448934 3.174417e-01 5.283867e-01
1 0.189027 3.174417e-01 5.291595e-01
2 1.02624 3.245778e-01 5.180761e-01
2 1.55533 3.276585e-01 5.132913e-01
3 0.207106 3.176709e-01 5.288036e-01
1 -0.576149 3.176709e-01 5.243533e-01
1 -0.797353 3.108780e-01 5.349036e-01
1 -2.81892 3.108780e-01 5.077121e-01
2 -2.87015 3.120615e-01 5.058740e-01
2 -2.40961 3.058885e-01 5.154616e-01
1 -2.75891 3.098269e-01 5.093447e-01
1 -2.74151 3.098269e-01 5.123169e-01
2 -2.7845 3.106158e-01 5.110917e-01
1 -2.84422 3.173538e-01 5.006265e-01
1 -2.72073 3.173538e-01 5.041975e-01
1 -2.62883 3.193047e-01 5.011675e-01
1 -2.66801 3.193047e-01 5.002955e-01
2 -2.4469 3.066815e-01 5.199011e-01
1 -2.39641 3.228610e-01 4.947720e-01
1 -2.49988 3.228610e-01 4.798973e-01
1 -1.08737 2.997502e-01 5.157919e-01
1 -1.48045 2.997502e-01 5.283600e-01
1 -1.13942 2.980839e-01 5.309479e-01
1 -1.04241 2.980839e-01 5.249928e-01
1 -2.5647 3.077090e-01 5.100436e-01
1 -2.53332 3.077090e-01 5.185006e-01
1 -2.61371 3.200538e-01 4.993273e-01
2 -2.67067 3.200538e-01 4.979327e-01
1 -1.84199 3.200538e-01 5.097604e-01
4 -2.0644 3.096844e-01 5.258656e-01
2 -1.91504 3.070956e-01 5.298864e-01
1 -1.97079 3.079022e-01 5.286336e-01
1 -1.83391 3.079022e-01 4.960065e-01
1 -2.00733 3.096632e-01 4.932714e-01
1 -0.742828 3.096632e-01 4.823071e-01
1 -0.385069 3.066684e-01 4.869586e-01
1 1.23658 3.066684e-01 4.773810e-01
1 0.936318 3.298434e-01 4.413868e-01
1 0.554099 3.298434e-01 4.437631e-01
2 0.0054257 3.149667e-01 4.668688e-01
1 -0.0631787 3.207797e-01 4.578404e-01
4 -2.49836 3.207797e-01 4.801096e-01
2 -2.68721 3.207797e-01 4.849021e-01
3 -2.57559 3.207797e-01 4.979274e-01
2 -1.7006 3.284675e-01 4.859870e-01
2 -1.81347 3.277127e-01 4.871595e-01
1 -2.55277 3.210852e-01 4.974528e-01
1 -2.73275 3.210852e-01 4.900506e-01
1 -2.91586 3.140381e-01 5.009958e-01
3 -2.91897 3.140381e-01 5.018668e-01
1 -2.72592 3.094033e-01 5.090653e-01
1 -2.68653 3.094033e-01 5.145994e-01
1 -2.83034 3.129847e-01 5.090371e-01
4 -2.47952 3.129847e-01 4.914466e-01
1 -2.86574 3.129847e-01 5.004987e-01
5 -2.11786 3.274330e-01 4.780584e-01
2 -2.08197 3.274330e-01 4.814295e-01
1 -2.10074 3.274330e-01 4.803153e-01
1 -2.56611 3.232322e-01 4.868398e-01
3 -1.74909 3.232322e-01 5.026620e-01
1 -2.25347 3.166405e-01 5.128999e-01
1 -2.73993 3.166405e-01 5.053876e-01
2 -2.75264 3.161324e-01 5.061767e-01
1 -2.68523 3.181375e-01 5.030625e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 414 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.006120 for Omega_m
0.000829 for b1
--> Not computing covariance matrix
1 -2.60037 3.181375e-01 5.047360e-01
2 -2.67293 3.161278e-01 5.078574e-01
4 -0.707625 3.330412e-01 4.815885e-01
2 -0.929124 3.319117e-01 4.833427e-01
1 -2.47776 3.202074e-01 5.015212e-01
1 -2.74029 3.202074e-01 4.950332e-01
1 -2.28852 3.253021e-01 4.871204e-01
1 -2.25824 3.253021e-01 4.880506e-01
2 -2.7104 3.203110e-01 4.958026e-01
1 -2.87823 3.133397e-01 5.066299e-01
2 -1.94904 3.133397e-01 4.843158e-01
1 -2.24924 3.133397e-01 4.876058e-01
2 -2.31286 3.154758e-01 4.842883e-01
1 -2.07842 3.236299e-01 4.716236e-01
2 -2.33206 3.236299e-01 4.759825e-01
2 -2.38442 3.236299e-01 4.771858e-01
1 -2.41465 3.236299e-01 4.913586e-01
2 -1.52913 3.302190e-01 4.811247e-01
1 -2.71705 3.095431e-01 5.132375e-01
1 -2.73478 3.095431e-01 5.087412e-01
1 -2.88742 3.177990e-01 4.959186e-01
1 -2.58633 3.177990e-01 5.057858e-01
1 -2.4746 3.197998e-01 5.026782e-01
1 -2.76594 3.197998e-01 4.876669e-01
2 -2.73273 3.112290e-01 5.009786e-01
1 -2.68014 3.103553e-01 5.023357e-01
1 -2.76708 3.103553e-01 5.117618e-01
2 -2.82204 3.178104e-01 5.001828e-01
1 -2.6244 3.213328e-01 4.947121e-01
1 -2.69476 3.213328e-01 4.917767e-01
1 -2.79424 3.104133e-01 5.087362e-01
1 -2.57623 3.104133e-01 4.996237e-01
2 -2.70212 3.195375e-01 4.854524e-01
6 -2.13025 3.268479e-01 4.740984e-01
3 -2.43023 3.238846e-01 4.787007e-01
1 -2.47802 3.238846e-01 4.878001e-01
3 -2.91925 3.143158e-01 5.026619e-01
1 -2.75999 3.143158e-01 5.093230e-01
1 -2.66754 3.181906e-01 5.033049e-01
1 -2.77332 3.181906e-01 5.007092e-01
1 -2.85003 3.140982e-01 5.070653e-01
1 -2.56117 3.140982e-01 4.903783e-01
2 -2.46695 3.212884e-01 4.792108e-01
1 -2.51595 3.202621e-01 4.808049e-01
2 -1.82302 3.202621e-01 5.094538e-01
1 -2.35906 3.202621e-01 4.781975e-01
2 -2.18426 3.233989e-01 4.733256e-01
1 -2.31557 3.212484e-01 4.766657e-01
1 -2.67553 3.212484e-01 4.847898e-01
1 -2.66446 3.214289e-01 4.845095e-01
1 -2.54102 3.214289e-01 4.807222e-01
1 -1.48168 3.312221e-01 4.655118e-01
3 -1.24736 3.312221e-01 4.601588e-01
1 -1.73029 3.275692e-01 4.658323e-01
1 -2.0981 3.275692e-01 4.784724e-01
2 -2.34984 3.254852e-01 4.817092e-01
2 -1.98975 3.283698e-01 4.772291e-01
2 -2.77961 3.202914e-01 4.897760e-01
1 -2.66168 3.221139e-01 4.869454e-01
1 -2.57509 3.221139e-01 4.817528e-01
1 -1.36512 3.322323e-01 4.660373e-01
1 -1.35675 3.322323e-01 4.726396e-01
3 -1.29901 3.325526e-01 4.721421e-01
1 -0.284991 3.325526e-01 4.879224e-01
1 -0.514859 3.314035e-01 4.897072e-01
2 -0.283182 3.314035e-01 4.917490e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 446 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.007503 for Omega_m
0.002133 for b1
--> Not computing covariance matrix
3 -1.52892 3.314035e-01 4.716435e-01
3 -2.50457 3.074719e-01 5.088127e-01
1 -2.23504 3.074719e-01 5.252557e-01
4 -2.40339 3.166898e-01 5.109389e-01
1 -2.4443 3.118308e-01 5.184857e-01
2 -2.326 3.118308e-01 4.918860e-01
1 -2.83763 3.118308e-01 5.090825e-01
1 -2.65492 3.085254e-01 5.142163e-01
1 -2.64167 3.085254e-01 5.090340e-01
2 -2.77419 3.103749e-01 5.061615e-01
2 -2.69367 3.091823e-01 5.080138e-01
1 -2.87275 3.182749e-01 4.938916e-01
1 -2.86642 3.182749e-01 4.927893e-01
1 -2.89898 3.140271e-01 4.993868e-01
1 -2.10202 3.140271e-01 5.193805e-01
1 -1.524 3.033515e-01 5.359612e-01
1 -1.59338 3.033515e-01 5.350509e-01
1 -2.06291 3.177662e-01 5.126628e-01
2 -2.50628 3.177662e-01 5.071635e-01
1 -2.7835 3.177662e-01 5.015700e-01
2 -2.82533 3.126805e-01 5.094688e-01
1 -2.65438 3.202574e-01 4.977008e-01
1 -1.53657 3.202574e-01 5.120372e-01
1 -0.413982 3.287017e-01 4.989219e-01
1 -0.0593511 3.287017e-01 5.014571e-01
2 -0.641012 3.251218e-01 5.070172e-01
1 -0.585645 3.255006e-01 5.064288e-01
1 -1.48959 3.255006e-01 4.633736e-01
1 -1.83486 3.170491e-01 4.765001e-01
1 -1.97286 3.170491e-01 4.778525e-01
3 -1.95375 3.155487e-01 4.801828e-01
2 -2.91329 3.155487e-01 4.971776e-01
1 -2.75974 3.155487e-01 5.071728e-01
2 -2.76849 3.137779e-01 5.099230e-01
3 -2.51731 3.078140e-01 5.191859e-01
1 -2.55661 3.078140e-01 5.090276e-01
1 -2.61481 3.227125e-01 4.858880e-01
1 -2.25135 3.227125e-01 4.978656e-01
1 -1.89437 3.258221e-01 4.930360e-01
1 -2.30016 3.258221e-01 4.828645e-01
2 -2.72887 3.211323e-01 4.901484e-01
1 -2.83343 3.113324e-01 5.053692e-01
2 -2.65585 3.113324e-01 5.152673e-01
1 -2.3205 3.113324e-01 4.929954e-01
3 -2.48868 3.172565e-01 4.837944e-01
2 -2.89991 3.172565e-01 4.972759e-01
1 -1.72638 3.172565e-01 4.751627e-01
2 -1.69568 3.153152e-01 4.781779e-01
1 -1.67745 3.147178e-01 4.791056e-01
1 -2.89831 3.147178e-01 5.040287e-01
5 -2.66014 3.085206e-01 5.136539e-01
1 -2.31133 3.085206e-01 5.235631e-01
2 -2.368 3.176372e-01 5.094038e-01
1 -2.45709 3.123013e-01 5.176912e-01
1 -0.893161 3.123013e-01 5.320602e-01
1 -0.478555 3.035648e-01 5.456292e-01
1 -2.04741 3.035648e-01 5.263134e-01
1 -2.63795 3.185073e-01 5.031054e-01
1 -2.76324 3.185073e-01 5.001019e-01
2 -2.69802 3.197456e-01 4.981787e-01
2 -2.60722 3.210995e-01 4.960759e-01
4 -2.52915 3.072504e-01 5.175855e-01
3 -2.71703 3.097826e-01 5.136527e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 476 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.007339 for Omega_m
0.002052 for b1
--> Not computing covariance matrix
1 -2.66871 3.097826e-01 5.155280e-01
5 -1.84409 3.272986e-01 4.883231e-01
1 -1.23572 3.272986e-01 4.960427e-01
1 -2.2775 3.166856e-01 5.125263e-01
2 -2.50025 3.166856e-01 5.095928e-01
3 -2.76831 3.166856e-01 5.046105e-01
2 -2.12529 3.252466e-01 4.913140e-01
1 -1.67545 3.285114e-01 4.862432e-01
1 -0.968308 3.285114e-01 4.948554e-01
1 -2.21581 3.167268e-01 5.131588e-01
3 -2.76983 3.167268e-01 4.898938e-01
1 -1.90627 3.286469e-01 4.713802e-01
3 -1.60557 3.286469e-01 4.642257e-01
1 -2.12833 3.233124e-01 4.725109e-01
2 -2.40662 3.233124e-01 4.776091e-01
1 -2.5481 3.233124e-01 4.877316e-01
2 -2.29459 3.257505e-01 4.839449e-01
2 -2.82127 3.194202e-01 4.937767e-01
2 -2.92462 3.145980e-01 5.012665e-01
1 -2.90695 3.133376e-01 5.032240e-01
1 -2.89828 3.133376e-01 5.015641e-01
1 -2.07602 3.276776e-01 4.792920e-01
1 -1.33624 3.276776e-01 4.606309e-01
1 -0.712154 3.324057e-01 4.532874e-01
1 -1.2928 3.324057e-01 4.737648e-01
3 -2.92321 3.144347e-01 5.016765e-01
4 -2.72284 3.144347e-01 5.099660e-01
1 -2.7534 3.144347e-01 5.092874e-01
1 -2.68946 3.175053e-01 5.045183e-01
1 -2.74684 3.175053e-01 5.032184e-01
2 -2.41248 3.063608e-01 5.205274e-01
1 -1.74143 3.013247e-01 5.283493e-01
2 -1.72863 3.013247e-01 5.213166e-01
1 -1.47477 3.013247e-01 5.146213e-01
3 -0.754768 2.978962e-01 5.199463e-01
2 -0.995064 2.978962e-01 5.251330e-01
1 -0.998091 2.978962e-01 5.252257e-01
1 -2.16604 3.042928e-01 5.152908e-01
4 -2.18667 3.042928e-01 5.233134e-01
1 -0.202251 3.042928e-01 5.469272e-01
1 1.56614 2.936307e-01 5.634869e-01
1 1.18025 2.936307e-01 5.603829e-01
2 2.52117 2.889306e-01 5.676830e-01
1 2.25474 2.897748e-01 5.663717e-01
1 3.77532 2.897748e-01 5.772291e-01
1 2.03705 2.972219e-01 5.656627e-01
1 -0.12465 2.972219e-01 5.501083e-01
1 -1.60343 3.138120e-01 5.243414e-01
1 -2.9151 3.138120e-01 5.030261e-01
4 -2.89833 3.129776e-01 5.043221e-01
3 -2.8569 3.117136e-01 5.062853e-01
1 -2.7123 3.117136e-01 5.136241e-01
1 -2.73715 3.127777e-01 5.119715e-01
1 -2.61904 3.127777e-01 5.144284e-01
1 -2.55998 3.172258e-01 5.075199e-01
1 -2.80091 3.172258e-01 4.901277e-01
1 -2.79537 3.175680e-01 4.895962e-01
1 -2.7706 3.175680e-01 4.888788e-01
1 -2.37645 3.245991e-01 4.779584e-01
2 0.164159 3.245991e-01 4.514725e-01
3 1.68783 3.245991e-01 4.431656e-01
1 1.88714 3.122025e-01 4.624194e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 509 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.007776 for Omega_m
0.002042 for b1
--> Not computing covariance matrix
1 -0.933801 3.122025e-01 4.781860e-01
1 -0.908277 3.118473e-01 4.787376e-01
1 -1.31432 3.118473e-01 4.817804e-01
2 -1.42453 3.137084e-01 4.788899e-01
1 -1.43765 3.217898e-01 4.663382e-01
1 -2.65252 3.217898e-01 4.844976e-01
1 -2.54902 3.086707e-01 5.048735e-01
3 -2.46271 3.086707e-01 5.207707e-01
1 -2.61148 3.155618e-01 5.100678e-01
3 -2.70877 3.155618e-01 4.903145e-01
3 -2.69371 3.180366e-01 4.864708e-01
1 -2.80873 3.180366e-01 4.896407e-01
1 -2.69947 3.111155e-01 5.003901e-01
4 -2.7425 3.111155e-01 5.016583e-01
1 -2.83025 3.111155e-01 5.070445e-01
2 -2.65096 3.083655e-01 5.113157e-01
2 -1.49299 2.999632e-01 5.243658e-01
1 -2.89463 3.128291e-01 5.043831e-01
1 -1.51485 3.128291e-01 5.266846e-01
3 -0.885037 3.023084e-01 5.430248e-01
1 -0.74016 3.023084e-01 5.443269e-01
1 -0.128133 2.983581e-01 5.504623e-01
1 -0.365372 2.983581e-01 5.481389e-01
1 -1.63115 3.111908e-01 5.282079e-01
3 -1.85392 3.111908e-01 5.261885e-01
2 -0.449324 3.284473e-01 4.993867e-01
2 -1.86655 3.123085e-01 5.244525e-01
1 -1.81719 3.098170e-01 5.283223e-01
2 -2.46789 3.098170e-01 5.201186e-01
2 -2.75307 3.098170e-01 5.112089e-01
1 -2.66268 3.098170e-01 5.037592e-01
1 -2.48329 3.077023e-01 5.070435e-01
1 -2.22226 3.077023e-01 5.016880e-01
2 -2.40208 3.096342e-01 4.986875e-01
3 -1.97009 3.276354e-01 4.707290e-01
1 -1.99581 3.276354e-01 4.714815e-01
1 -2.22347 3.256066e-01 4.746325e-01
1 -1.43851 3.256066e-01 4.627722e-01
2 -1.76891 3.195438e-01 4.721886e-01
1 -1.74704 3.148659e-01 4.794542e-01
1 -2.65117 3.148659e-01 4.904408e-01
2 -1.67625 3.036235e-01 5.079018e-01
1 -0.926131 2.995971e-01 5.141554e-01
1 -1.25053 2.995971e-01 5.195893e-01
2 -1.79932 3.025359e-01 5.150250e-01
2 -2.19746 3.267425e-01 4.774284e-01
1 -2.33528 3.255287e-01 4.793136e-01
2 -1.28361 3.255287e-01 4.612975e-01
2 -1.49046 3.255287e-01 4.633646e-01
1 -1.37686 3.255287e-01 4.622023e-01
2 -1.62335 3.217343e-01 4.680957e-01
1 -1.55557 3.230420e-01 4.660646e-01
4 -1.36512 3.230420e-01 4.643061e-01
1 -0.398333 3.230420e-01 4.569458e-01
1 -0.183931 3.263365e-01 4.518289e-01
1 -1.90306 3.263365e-01 4.910602e-01
2 -2.74143 3.137392e-01 5.106257e-01
1 -2.64183 3.100865e-01 5.162989e-01
1 -2.48604 3.100865e-01 4.988333e-01
1 -2.53337 3.107630e-01 4.977825e-01
1 -2.80734 3.107630e-01 5.065776e-01
1 -2.80902 3.107943e-01 5.065290e-01
1 -2.76922 3.107943e-01 5.120926e-01
1 -2.05486 3.031976e-01 5.238914e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 541 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.008302 for Omega_m
0.001755 for b1
--> Not computing covariance matrix
3 -2.06588 3.031976e-01 5.223500e-01
1 -2.13858 3.037069e-01 5.215590e-01
1 -2.05539 3.037069e-01 5.152101e-01
1 -1.49713 3.004293e-01 5.203008e-01
1 -1.48166 3.004293e-01 5.337026e-01
1 -1.39632 2.999487e-01 5.344491e-01
5 -1.46186 2.999487e-01 5.230364e-01
1 -1.63268 3.008445e-01 5.216450e-01
1 -1.6366 3.008445e-01 5.218170e-01
1 -2.8508 3.116902e-01 5.049720e-01
1 -2.72671 3.116902e-01 4.993992e-01
3 -2.83178 3.161009e-01 4.925488e-01
1 -2.81256 3.161009e-01 5.046995e-01
1 -2.45048 3.065866e-01 5.194766e-01
6 -1.57487 3.065866e-01 4.969499e-01
3 -2.11325 3.065866e-01 5.036812e-01
2 -1.79927 3.042542e-01 5.073038e-01
1 -1.49012 3.023544e-01 5.102545e-01
1 -1.72312 3.023544e-01 5.142847e-01
2 -1.10733 3.337903e-01 4.654601e-01
2 -2.84358 3.159930e-01 4.931019e-01
3 -2.0854 3.046988e-01 5.106435e-01
1 -2.05312 3.046988e-01 5.099440e-01
4 -2.79747 3.139045e-01 4.956462e-01
2 -2.55224 3.228586e-01 4.817392e-01
5 -2.61643 3.100691e-01 5.016031e-01
1 -0.0562113 3.100691e-01 4.769523e-01
1 1.62995 2.999197e-01 4.927158e-01
1 -1.06297 2.999197e-01 5.146227e-01
3 -1.53436 3.023837e-01 5.107958e-01
1 -1.59345 3.023837e-01 5.117382e-01
2 -2.62027 3.210164e-01 4.827988e-01
1 -2.25119 3.256608e-01 4.755854e-01
1 -1.93394 3.256608e-01 4.930108e-01
1 -2.64927 3.170011e-01 5.064606e-01
1 -2.88169 3.170011e-01 4.998495e-01
4 -2.89237 3.132364e-01 5.056967e-01
1 -1.95058 3.024416e-01 5.224626e-01
1 -1.89212 3.024416e-01 5.184061e-01
1 -2.92058 3.157889e-01 4.976758e-01
2 -2.92366 3.157889e-01 4.995433e-01
3 -2.59455 3.157889e-01 5.099176e-01
1 -2.32868 3.208938e-01 5.019889e-01
1 -2.38544 3.208938e-01 5.011251e-01
1 -2.65949 3.130577e-01 5.132957e-01
2 -2.9005 3.130577e-01 5.037031e-01
2 -2.78869 3.130577e-01 4.974058e-01
1 -1.99755 3.130577e-01 4.853852e-01
1 -1.27044 3.054790e-01 4.971560e-01
2 -1.80576 3.054790e-01 5.320456e-01
3 -2.31526 3.054790e-01 5.220773e-01
1 -2.77658 3.124312e-01 5.112795e-01
1 -1.88567 3.124312e-01 4.855676e-01
1 -1.483 3.273176e-01 4.624468e-01
1 -2.0971 3.273176e-01 4.743806e-01
1 -2.62304 3.216970e-01 4.831103e-01
2 -2.66413 3.216970e-01 4.914418e-01
1 -2.52764 3.216970e-01 4.803612e-01
1 -1.76503 3.039645e-01 5.079024e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 569 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.004033 for Omega_m
0.001285 for b1
--> Not computing covariance matrix
1 -1.34985 3.039645e-01 5.026341e-01
2 -1.67185 3.061748e-01 4.992012e-01
1 -2.31916 3.142062e-01 4.867273e-01
2 -2.09805 3.142062e-01 4.841542e-01
4 -2.06107 3.142062e-01 5.195001e-01
1 -2.8669 3.142062e-01 5.062682e-01
2 -2.55072 3.220489e-01 4.940873e-01
1 -2.79135 3.110451e-01 5.111777e-01
1 -2.80116 3.110451e-01 5.106398e-01
2 -2.78745 3.186824e-01 4.987780e-01
2 -2.42164 3.060244e-01 5.184376e-01
1 -0.816014 2.966604e-01 5.329814e-01
1 -0.669864 2.966604e-01 5.410806e-01
1 -1.16815 2.990489e-01 5.373708e-01
2 -1.29603 2.990489e-01 5.334569e-01
1 -1.34178 2.990489e-01 5.293562e-01
1 -2.87849 3.145193e-01 5.053285e-01
1 -2.92413 3.145193e-01 5.013033e-01
1 -2.92656 3.151503e-01 5.003232e-01
1 -2.92537 3.151503e-01 4.993658e-01
1 -2.83924 3.114716e-01 5.050794e-01
1 -2.83667 3.114716e-01 5.048139e-01
1 -2.89127 3.176955e-01 4.951473e-01
2 -2.52844 3.176955e-01 4.837968e-01
4 -2.88842 3.176955e-01 4.965260e-01
1 -2.80233 3.176955e-01 4.896940e-01
2 -1.95529 3.284716e-01 4.729572e-01
1 -2.40762 3.076692e-01 5.052663e-01
2 -2.57776 3.076692e-01 5.111442e-01
1 -2.5511 3.076692e-01 5.096182e-01
1 -2.38269 3.060739e-01 5.120959e-01
1 -2.43491 3.060739e-01 5.170883e-01
1 -2.39662 3.057298e-01 5.176228e-01
1 -2.37397 3.057298e-01 5.142342e-01
1 -2.90658 3.170838e-01 4.965998e-01
1 -2.59515 3.170838e-01 4.857698e-01
1 -2.48781 3.122023e-01 4.933515e-01
2 -2.61922 3.122023e-01 5.151392e-01
2 -2.55118 3.122023e-01 4.943890e-01
1 -2.67361 3.122023e-01 5.140509e-01
2 -2.40712 3.071976e-01 5.218239e-01
1 -2.69222 3.135234e-01 5.119990e-01
1 -2.90704 3.135234e-01 5.018506e-01
1 -2.92514 3.154521e-01 4.988551e-01
1 -2.86768 3.154521e-01 5.041807e-01
1 -2.58071 3.217497e-01 4.943996e-01
1 -2.01206 3.217497e-01 5.037727e-01
1 -2.2675 3.086022e-01 5.241927e-01
2 -2.59136 3.086022e-01 5.174684e-01
1 -2.13743 3.086022e-01 4.977277e-01
8 -1.61422 3.043914e-01 5.042678e-01
1 -2.36855 3.115326e-01 4.931764e-01
3 -2.84621 3.115326e-01 5.077322e-01
1 -2.19274 3.262836e-01 4.848217e-01
1 -1.62575 3.262836e-01 4.950191e-01
1 0.844275 3.386513e-01 4.758103e-01
1 -0.0906068 3.386513e-01 4.585904e-01
2 -1.2852 3.328289e-01 4.676335e-01
2 -1.80433 3.296547e-01 4.725635e-01
3 -2.71886 3.208031e-01 4.863113e-01
1 -2.34008 3.208031e-01 4.774111e-01
1 -2.28657 3.218635e-01 4.757642e-01
1 -2.53071 3.218635e-01 4.804259e-01
2 -1.74949 3.295003e-01 4.685648e-01
1 -1.79619 3.291650e-01 4.690856e-01
1 -1.70183 3.291650e-01 4.827219e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 604 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.002865 for Omega_m
0.000523 for b1
--> Not computing covariance matrix
4 -1.81666 3.284157e-01 4.838858e-01
1 -2.15165 3.259755e-01 4.876758e-01
3 -2.0421 3.259755e-01 4.900352e-01
1 -1.99434 3.263421e-01 4.894658e-01
2 -2.16165 3.263421e-01 4.855388e-01
1 -1.64662 3.263421e-01 4.647449e-01
4 -2.0828 3.155656e-01 4.814824e-01
1 -2.08464 3.188757e-01 4.763414e-01
1 -2.81759 3.188757e-01 4.898010e-01
1 -2.78943 3.195810e-01 4.887056e-01
1 -2.17951 3.195810e-01 4.765412e-01
3 -2.20777 3.181449e-01 4.787716e-01
1 -1.8338 3.181449e-01 4.747926e-01
2 -1.47102 3.257080e-01 4.630459e-01
1 -1.59844 3.111736e-01 4.856199e-01
1 -2.47368 3.111736e-01 4.956571e-01
2 -1.1554 3.009007e-01 5.116125e-01
1 -1.54861 3.030636e-01 5.082531e-01
1 -2.03625 3.030636e-01 5.240247e-01
1 -2.04399 3.031168e-01 5.239421e-01
2 -1.54425 3.031168e-01 5.079874e-01
1 -1.18306 3.031168e-01 5.036726e-01
1 -2.30167 3.195606e-01 4.781330e-01
2 -2.81173 3.195606e-01 4.902892e-01
1 -2.66301 3.195606e-01 4.844193e-01
1 -2.6615 3.196003e-01 4.843577e-01
1 -2.817 3.196003e-01 4.927133e-01
2 -1.98065 3.282856e-01 4.792238e-01
1 -2.5663 3.232081e-01 4.871099e-01
1 -2.57279 3.232081e-01 4.860504e-01
1 -2.92087 3.153472e-01 4.982595e-01
1 -2.87907 3.153472e-01 4.955110e-01
1 -2.84324 3.132082e-01 4.988332e-01
1 -2.904 3.132082e-01 5.033640e-01
2 -2.91194 3.167403e-01 4.978780e-01
4 -2.15865 3.039786e-01 5.176989e-01
1 -1.76879 3.014988e-01 5.215505e-01
1 -1.37316 3.014988e-01 5.121474e-01
1 -1.06418 2.999330e-01 5.145792e-01
1 -1.00456 2.999330e-01 5.414901e-01
1 -0.659503 2.980579e-01 5.444023e-01
1 -0.231025 2.980579e-01 5.494029e-01
1 0.101315 2.964103e-01 5.519619e-01
1 -0.540702 2.964103e-01 5.250024e-01
2 -2.43746 3.071114e-01 5.083820e-01
1 -1.97322 3.035090e-01 5.139771e-01
1 -1.69949 3.035090e-01 5.086988e-01
6 -1.50909 3.023711e-01 5.104661e-01
1 -2.26524 3.078219e-01 5.020002e-01
1 -1.86344 3.078219e-01 4.965630e-01
3 -2.31981 3.144377e-01 4.862877e-01
2 -2.29196 3.144377e-01 4.859410e-01
1 -2.1297 3.144377e-01 4.840557e-01
1 -2.14033 3.195728e-01 4.760802e-01
1 -2.56272 3.195728e-01 4.822580e-01
1 -2.46219 3.217200e-01 4.789231e-01
2 -2.63972 3.217200e-01 4.837883e-01
1 -2.4579 3.217200e-01 4.973837e-01
4 -2.53727 3.207175e-01 4.989408e-01
5 -1.23135 3.309587e-01 4.830347e-01
1 -0.958045 3.309587e-01 4.866774e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 634 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.002349 for Omega_m
0.000222 for b1
--> Not computing covariance matrix
4 -1.28213 3.291131e-01 4.895439e-01
4 -1.24952 3.293077e-01 4.892416e-01
1 -2.07673 3.046496e-01 5.275393e-01
1 -1.07016 3.046496e-01 5.400981e-01
1 -1.04411 3.202209e-01 5.159135e-01
6 0.428675 3.202209e-01 5.247407e-01
1 -1.34209 3.202209e-01 5.136966e-01
1 -1.68906 3.136090e-01 5.239659e-01
2 -2.35695 3.136090e-01 5.171346e-01
1 -2.68528 3.136090e-01 5.120159e-01
1 -2.40803 3.072794e-01 5.218467e-01
1 -1.04114 3.072794e-01 5.379076e-01
2 -1.01641 3.170705e-01 5.227005e-01
1 -1.17267 3.111873e-01 5.318380e-01
1 -2.77036 3.111873e-01 5.023931e-01
1 -2.88735 3.161198e-01 4.947322e-01
4 -2.53791 3.161198e-01 5.101724e-01
3 -2.91141 3.161198e-01 4.963448e-01
3 -1.58398 3.008150e-01 5.201154e-01
1 -1.6008 3.008150e-01 5.315102e-01
1 -0.530222 2.956616e-01 5.395142e-01
3 -0.083015 2.956616e-01 5.217345e-01
1 0.809632 2.925980e-01 5.264926e-01
2 0.2723 2.925980e-01 5.390843e-01
1 0.483367 2.925980e-01 5.318114e-01
2 -1.04556 2.983727e-01 5.228425e-01
1 -2.07463 3.039777e-01 5.141371e-01
4 -1.41099 3.039777e-01 5.032656e-01
3 -1.48804 3.039777e-01 5.041550e-01
1 -2.39199 3.205183e-01 4.784651e-01
1 -2.66514 3.205183e-01 4.965092e-01
1 -2.81311 3.176405e-01 5.009788e-01
1 -2.78506 3.176405e-01 4.892140e-01
1 -2.6369 3.107717e-01 4.998822e-01
1 -2.42018 3.107717e-01 4.958484e-01
1 -2.60359 3.152269e-01 4.889288e-01
1 -2.58011 3.152269e-01 4.885337e-01
5 -2.44553 3.115735e-01 4.942079e-01
1 -2.81155 3.115735e-01 5.104004e-01
5 -2.57162 3.217771e-01 4.945528e-01
1 -2.68686 3.217771e-01 4.883518e-01
2 -0.956679 3.344085e-01 4.687334e-01
6 -1.71674 3.301468e-01 4.753524e-01
6 -1.22249 3.330231e-01 4.708851e-01
1 -1.83045 3.294107e-01 4.764957e-01
5 -1.57525 3.294107e-01 4.841001e-01
2 -2.36853 3.233837e-01 4.934609e-01
2 -2.60627 3.206048e-01 4.977769e-01
1 -2.77156 3.114166e-01 5.120475e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 659 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.001971 for Omega_m
0.000619 for b1
--> Not computing covariance matrix
2 -2.4931 3.114166e-01 4.953545e-01
3 -1.52523 3.114166e-01 5.287723e-01
2 -1.51303 3.139479e-01 5.248409e-01
1 0.561027 3.315247e-01 4.975415e-01
1 0.469284 3.315247e-01 4.969418e-01
4 -1.47233 3.170281e-01 5.194572e-01
1 -1.58586 3.140284e-01 5.241162e-01
1 -2.91573 3.140284e-01 5.010119e-01
1 -2.67646 3.088599e-01 5.090393e-01
1 -1.40905 3.088599e-01 4.893686e-01
1 -1.67958 3.120902e-01 4.843516e-01
1 -2.5393 3.120902e-01 4.944570e-01
1 -2.64849 3.166849e-01 4.873208e-01
2 -2.90796 3.166849e-01 4.988050e-01
1 -2.41679 3.166849e-01 4.836241e-01
1 -1.83937 3.069920e-01 4.986787e-01
1 -2.49795 3.069920e-01 5.184040e-01
1 -2.84192 3.142114e-01 5.071912e-01
1 -2.81011 3.142114e-01 4.953369e-01
4 -2.74285 3.121430e-01 4.985494e-01
2 -2.81996 3.170583e-01 4.909153e-01
2 -2.4753 3.238393e-01 4.803834e-01
1 -0.95473 3.345786e-01 4.637036e-01
1 -0.954881 3.345786e-01 4.660134e-01
1 -1.66319 3.305948e-01 4.722007e-01
1 -1.63076 3.305948e-01 4.686222e-01
2 -2.29631 3.254102e-01 4.766747e-01
1 -2.77583 3.150020e-01 4.928402e-01
2 -2.7133 3.150020e-01 4.914115e-01
1 -2.70917 3.150020e-01 5.092834e-01
2 -2.45534 3.075841e-01 5.208044e-01
1 -2.54901 3.088789e-01 5.187934e-01
1 -2.69053 3.088789e-01 5.103177e-01
1 -2.54278 3.233449e-01 4.878500e-01
1 -2.4595 3.233449e-01 4.913245e-01
1 -0.829214 3.341151e-01 4.745968e-01
1 -0.95274 3.341151e-01 4.715786e-01
4 -2.26345 3.259150e-01 4.843146e-01
5 -2.61636 3.224223e-01 4.897393e-01
1 -2.30769 3.224223e-01 4.757766e-01
2 -1.97703 3.263550e-01 4.696685e-01
1 -2.48575 3.157819e-01 4.860901e-01
3 -2.88079 3.157819e-01 5.029582e-01
3 -2.56465 3.222266e-01 4.929486e-01
1 -1.99764 3.222266e-01 5.026627e-01
1 -1.9118 3.043100e-01 5.304899e-01
1 -1.95009 3.043100e-01 5.096112e-01
1 -2.35395 3.248739e-01 4.776724e-01
1 -2.31435 3.248739e-01 4.885103e-01
1 -2.85147 3.174528e-01 5.000364e-01
1 -0.826938 3.174528e-01 5.232041e-01
1 -0.0866773 3.244154e-01 5.123902e-01
1 0.371475 3.244154e-01 5.150334e-01
1 0.825134 3.272009e-01 5.107071e-01
5 -0.161907 3.272009e-01 5.048494e-01
1 0.445454 3.305075e-01 4.997138e-01
1 -1.05363 3.305075e-01 4.872203e-01
3 -1.2244 3.295329e-01 4.887339e-01
1 -0.77749 3.295329e-01 4.542013e-01
4 -1.4219 3.218612e-01 4.661167e-01
2 -1.48116 3.201563e-01 4.687647e-01
1 -1.50245 3.190588e-01 4.704691e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 689 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.001695 for Omega_m
0.000540 for b1
--> Not computing covariance matrix
3 -2.51344 3.190588e-01 4.818811e-01
2 -2.52652 3.147073e-01 4.886397e-01
1 -2.54621 3.161292e-01 4.864313e-01
1 -2.88995 3.161292e-01 5.017262e-01
1 -2.83277 3.182109e-01 4.984931e-01
3 -2.87457 3.182109e-01 4.938931e-01
1 -2.74234 3.209583e-01 4.896259e-01
1 -2.73976 3.209583e-01 4.885542e-01
1 -2.84957 3.187443e-01 4.919929e-01
2 -2.49569 3.187443e-01 5.050279e-01
1 -2.8043 3.187443e-01 4.891654e-01
2 -2.75723 3.199230e-01 4.873348e-01
2 -2.75286 3.117061e-01 5.000967e-01
1 -2.55934 3.088176e-01 5.045830e-01
2 -2.66217 3.088176e-01 5.083801e-01
2 -2.6727 3.088176e-01 5.090723e-01
1 -1.14715 3.088176e-01 4.872907e-01
2 -1.31228 3.252290e-01 4.618014e-01
1 -0.978228 3.286387e-01 4.565057e-01
2 -0.727014 3.286387e-01 4.541651e-01
1 -1.92767 3.286387e-01 4.723982e-01
1 -1.78413 3.296576e-01 4.708157e-01
3 0.353825 3.296576e-01 5.015112e-01
1 2.48439 3.387270e-01 4.874250e-01
1 1.62365 3.387270e-01 4.819283e-01
1 1.74395 3.391749e-01 4.812328e-01
1 1.8028 3.391749e-01 4.816467e-01
2 1.63437 3.385476e-01 4.826210e-01
1 1.54018 3.381912e-01 4.831745e-01
1 -0.120881 3.381912e-01 4.636460e-01
3 -1.40695 3.319202e-01 4.733858e-01
2 -0.63508 3.319202e-01 4.523254e-01
1 0.544328 3.319202e-01 4.423417e-01
1 -0.372404 3.178453e-01 4.642021e-01
1 0.216534 3.178453e-01 4.607039e-01
1 0.512047 3.265947e-01 4.471147e-01
1 -1.06711 3.265947e-01 4.585059e-01
1 -1.46844 3.165136e-01 4.741634e-01
3 -2.27034 3.165136e-01 4.820038e-01
1 -1.53305 3.059248e-01 4.984498e-01
1 -2.3387 3.059248e-01 5.113268e-01
4 -2.79597 3.113301e-01 5.029314e-01
1 -2.56045 3.233331e-01 4.842890e-01
1 -2.29346 3.233331e-01 4.951362e-01
1 -2.70733 3.174420e-01 5.042861e-01
4 -2.56955 3.174420e-01 4.848244e-01
2 -2.79624 3.174420e-01 5.020410e-01
5 -2.84095 3.174420e-01 4.912994e-01
2 -2.84361 3.172940e-01 4.915293e-01
4 -2.84379 3.172831e-01 4.915462e-01
1 -2.64346 3.219370e-01 4.843179e-01
1 -2.41864 3.219370e-01 4.974418e-01
2 -2.76147 3.139475e-01 5.098508e-01
1 -2.73102 3.165101e-01 5.058706e-01
2 -2.61374 3.165101e-01 5.081480e-01
2 -2.91361 3.165101e-01 4.964961e-01
1 -2.81633 3.165101e-01 5.036923e-01
1 -0.371915 3.358092e-01 4.737180e-01
1 -0.677711 3.358092e-01 4.661846e-01
1 -1.10037 3.337053e-01 4.694523e-01
1 -0.773832 3.337053e-01 4.777066e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 719 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.001956 for Omega_m
0.000465 for b1
--> Not computing covariance matrix
5 -1.65701 3.288012e-01 4.853233e-01
1 -1.91457 3.288012e-01 4.779081e-01
1 -2.91977 3.144243e-01 5.002376e-01
2 -2.75286 3.144243e-01 4.934070e-01
3 -2.65227 3.144243e-01 5.113739e-01
1 -2.60287 3.168707e-01 5.075742e-01
1 -2.90854 3.168707e-01 4.978774e-01
2 -2.81326 3.107898e-01 5.073220e-01
1 -2.92262 3.159077e-01 4.993731e-01
1 -2.8596 3.159077e-01 5.035676e-01
3 -1.18321 3.321190e-01 4.783891e-01
1 -1.15505 3.321190e-01 4.789320e-01
3 -2.20125 3.252970e-01 4.895277e-01
1 -1.53318 3.252970e-01 4.990579e-01
4 -2.16053 3.077882e-01 5.262517e-01
1 -1.66625 3.029113e-01 5.338262e-01
1 -1.32607 3.029113e-01 5.059796e-01
2 -1.08123 3.015619e-01 5.080754e-01
1 -2.24998 3.104199e-01 4.943177e-01
2 -1.47768 3.104199e-01 4.862641e-01
1 -2.75793 3.104199e-01 5.049615e-01
1 -1.9649 3.030775e-01 5.163653e-01
1 -2.04771 3.030775e-01 5.226924e-01
2 -2.88704 3.149519e-01 5.042496e-01
5 -2.768 3.102675e-01 5.115252e-01
1 -2.67615 3.102675e-01 5.025250e-01
1 -2.8585 3.158326e-01 4.938816e-01
1 -2.10037 3.158326e-01 4.812050e-01
3 -1.74169 3.093174e-01 4.913241e-01
1 -2.4469 3.093174e-01 5.208116e-01
1 -2.37887 3.194076e-01 5.051400e-01
1 -2.66477 3.194076e-01 5.000729e-01
1 -2.77221 3.169730e-01 5.038541e-01
1 -2.85832 3.169730e-01 5.010830e-01
1 -2.23873 3.254388e-01 4.879344e-01
1 -1.24561 3.254388e-01 4.610103e-01
1 -0.647512 3.308933e-01 4.525387e-01
3 -1.59179 3.308933e-01 4.744710e-01
1 -1.23036 3.329531e-01 4.712718e-01
1 -0.899591 3.329531e-01 4.792657e-01
1 -2.8008 3.136902e-01 5.091839e-01
2 -2.0052 3.136902e-01 5.209296e-01
1 -2.07633 3.136902e-01 5.202089e-01
2 -1.95069 3.083763e-01 5.284621e-01
1 -2.07125 3.117725e-01 5.231873e-01
2 -2.85861 3.117725e-01 5.067031e-01
1 -2.82952 3.117725e-01 5.095301e-01
2 -2.49725 3.067603e-01 5.173147e-01
1 -2.02252 3.029181e-01 5.232822e-01
1 -1.69355 3.029181e-01 5.333851e-01
2 -0.448922 2.960909e-01 5.439888e-01
1 -1.43746 3.011704e-01 5.360995e-01
1 -0.675623 3.011704e-01 5.452887e-01
5 -0.967255 3.034364e-01 5.417694e-01
1 -2.09703 3.034364e-01 5.226369e-01
2 -2.72753 3.197308e-01 4.973293e-01
1 -2.18131 3.040475e-01 5.216877e-01
1 -2.13434 3.040475e-01 5.246685e-01
1 -2.49982 3.074665e-01 5.193583e-01
1 -2.55201 3.074665e-01 5.170334e-01
1 -2.48962 3.226222e-01 4.934943e-01
3 -2.60312 3.226222e-01 4.892004e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 751 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000339 for Omega_m
0.000111 for b1
--> Not computing covariance matrix
2 -1.44269 3.315287e-01 4.753673e-01
1 -0.308232 3.371813e-01 4.665880e-01
1 -0.327471 3.371813e-01 4.542832e-01
1 -2.40115 3.222024e-01 4.775477e-01
1 -1.89312 3.222024e-01 5.039006e-01
1 -1.89969 3.221371e-01 5.040020e-01
1 -2.64233 3.221371e-01 4.848002e-01
3 -1.9862 3.284019e-01 4.750702e-01
1 -1.97359 3.284019e-01 4.736810e-01
6 -2.47214 3.239622e-01 4.805764e-01
2 -2.81685 3.139267e-01 4.961631e-01
2 -1.92643 3.287474e-01 4.731444e-01
1 -2.83393 3.149259e-01 4.946112e-01
1 -2.92336 3.149259e-01 5.015321e-01
1 -2.32264 3.253808e-01 4.852941e-01
1 -1.89337 3.253808e-01 4.945474e-01
1 -2.40878 3.077256e-01 5.219686e-01
1 -2.59928 3.077256e-01 5.131635e-01
2 -2.43227 3.060600e-01 5.157504e-01
5 -2.25264 3.045739e-01 5.180585e-01
1 -2.21955 3.045739e-01 5.155473e-01
1 -2.61115 3.227296e-01 4.873488e-01
1 -1.72416 3.227296e-01 5.042629e-01
1 -1.4403 3.250763e-01 5.006181e-01
1 -0.679073 3.250763e-01 5.068639e-01
1 -1.53253 3.160526e-01 5.208790e-01
1 -1.75856 3.160526e-01 5.189928e-01
1 -1.73537 3.087339e-01 5.303598e-01
1 -2.55345 3.087339e-01 5.186587e-01
1 -2.69444 3.166183e-01 5.064130e-01
4 -2.68221 3.166183e-01 4.880764e-01
4 -2.36925 3.166183e-01 5.115304e-01
3 -2.1872 3.166183e-01 5.136976e-01
1 -2.25528 3.136718e-01 5.182740e-01
1 -2.91339 3.136718e-01 5.029569e-01
1 -2.61833 3.224644e-01 4.893007e-01
1 -2.2369 3.224644e-01 4.746143e-01
1 -2.31271 3.210849e-01 4.767568e-01
1 -2.63281 3.210849e-01 4.954042e-01
1 -2.45142 3.232219e-01 4.920852e-01
1 -2.21578 3.232219e-01 4.968245e-01
3 -2.18271 3.235365e-01 4.963359e-01
3 -1.74908 3.235365e-01 5.018261e-01
1 -1.75422 3.234918e-01 5.018955e-01
2 -0.836516 3.234918e-01 5.097327e-01
1 -1.73901 3.234918e-01 5.020556e-01
1 -1.71113 3.237316e-01 5.016833e-01
3 -1.26479 3.237316e-01 5.058269e-01
1 -1.5947 3.206700e-01 5.105819e-01
1 -0.868032 3.206700e-01 5.161365e-01
1 0.066336 3.275029e-01 5.055241e-01
1 -0.312322 3.275029e-01 5.030161e-01
2 0.337106 3.310063e-01 4.975747e-01
2 0.722381 3.328313e-01 4.947403e-01
3 -0.252758 3.278537e-01 5.024712e-01
1 -0.658263 3.278537e-01 4.994758e-01
1 -1.85691 3.168254e-01 5.166044e-01
1 -2.89866 3.168254e-01 4.992296e-01
1 -2.43774 3.061024e-01 5.158840e-01
1 -2.4334 3.061024e-01 5.150875e-01
4 -1.98425 3.027415e-01 5.203075e-01
1 -2.1937 3.041709e-01 5.180874e-01
1 -2.10074 3.041709e-01 5.262046e-01
1 -2.66876 3.166998e-01 5.067453e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 781 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000770 for Omega_m
0.000077 for b1
--> Not computing covariance matrix
1 -2.8529 3.166998e-01 5.020047e-01
1 -2.87677 3.149348e-01 5.047460e-01
1 -2.80715 3.149348e-01 5.070941e-01
2 -2.55575 3.209936e-01 4.976840e-01
1 -2.40352 3.227806e-01 4.949084e-01
1 -2.19981 3.227806e-01 4.984426e-01
1 -2.51423 3.187651e-01 5.046793e-01
1 -2.46894 3.187651e-01 4.814915e-01
1 -2.06567 3.254879e-01 4.710500e-01
1 0.501597 3.254879e-01 4.484113e-01
3 0.354364 3.227472e-01 4.526679e-01
1 -2.3873 3.227472e-01 4.771403e-01
1 -2.58274 3.144722e-01 4.899926e-01
2 -2.71402 3.144722e-01 4.924445e-01
1 -2.92374 3.144722e-01 5.012043e-01
3 -2.9112 3.168139e-01 4.975673e-01
2 -2.83585 3.168139e-01 5.023480e-01
3 -2.80697 3.168139e-01 5.032693e-01
2 -2.76158 3.109029e-01 5.124501e-01
2 -2.69467 3.096036e-01 5.144681e-01
1 -2.66157 3.090777e-01 5.152849e-01
2 -2.31112 3.090777e-01 5.232075e-01
1 -2.2856 3.090777e-01 5.235876e-01
3 -2.25148 3.184934e-01 5.089635e-01
4 -2.84951 3.184934e-01 4.915587e-01
1 -2.61583 3.184934e-01 4.843493e-01
1 -2.54904 3.204379e-01 4.813292e-01
1 -2.73503 3.204379e-01 4.942553e-01
1 -2.87893 3.172682e-01 4.991783e-01
2 -2.9021 3.172682e-01 4.958557e-01
1 -2.76923 3.172682e-01 4.891831e-01
1 -2.2466 3.067023e-01 5.055935e-01
1 -2.02776 3.067023e-01 5.286483e-01
1 -2.23251 3.100832e-01 5.233973e-01
1 -2.10172 3.100832e-01 5.249948e-01
2 -2.05483 3.171745e-01 5.139810e-01
1 -1.68847 3.220071e-01 5.064751e-01
1 -0.990434 3.220071e-01 5.122086e-01
1 -1.543 3.119004e-01 5.279059e-01
1 -2.66157 3.119004e-01 5.146226e-01
3 -2.642 3.112413e-01 5.156463e-01
1 -2.01503 3.112413e-01 4.895307e-01
2 -2.11776 3.129853e-01 4.868220e-01
2 -2.21402 3.164126e-01 4.814990e-01
1 -2.03924 3.227575e-01 4.716443e-01
2 -1.86144 3.227575e-01 4.695081e-01
1 -2.38375 3.227575e-01 4.770665e-01
4 -2.52205 3.202897e-01 4.808994e-01
3 -2.55622 3.193807e-01 4.823112e-01
1 -2.72152 3.193807e-01 4.860813e-01
1 -2.78372 3.163463e-01 4.907941e-01
1 -2.70172 3.163463e-01 4.888873e-01
1 -2.66015 3.189893e-01 4.847823e-01
1 -2.786 3.189893e-01 4.883820e-01
2 -2.54429 3.231327e-01 4.819467e-01
2 -2.75034 3.119400e-01 4.993306e-01
2 -2.79201 3.188154e-01 4.886521e-01
2 -2.83841 3.151192e-01 4.943928e-01
1 -2.71712 3.205474e-01 4.859621e-01
2 -2.76405 3.205474e-01 4.891616e-01
1 -2.71089 3.205474e-01 4.948378e-01
2 0.41317 2.921666e-01 5.389174e-01
2 -0.814215 2.966802e-01 5.319070e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 814 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000478 for Omega_m
0.000137 for b1
--> Not computing covariance matrix
2 -2.83748 3.181039e-01 4.986328e-01
2 -2.76747 3.101043e-01 5.110575e-01
1 -1.81966 3.016303e-01 5.242189e-01
2 -0.90937 3.016303e-01 5.059495e-01
1 -1.0602 3.016303e-01 5.413891e-01
1 -1.58393 3.063548e-01 5.340512e-01
1 -2.39642 3.063548e-01 5.211364e-01
2 -2.76878 3.158025e-01 5.064627e-01
1 -2.71444 3.109261e-01 5.140365e-01
1 -2.5046 3.109261e-01 5.185484e-01
1 -2.53247 3.119282e-01 5.169921e-01
1 -2.79564 3.119282e-01 5.008221e-01
2 -1.22915 3.331393e-01 4.678782e-01
1 -2.65078 3.220507e-01 4.851004e-01
1 -2.20162 3.220507e-01 4.743697e-01
1 -2.03055 3.095934e-01 4.937178e-01
3 -1.88259 3.095934e-01 5.279330e-01
4 -1.92322 3.146558e-01 5.200702e-01
1 -1.85503 3.166421e-01 5.169852e-01
1 -2.02801 3.166421e-01 5.153279e-01
1 -2.01644 3.169007e-01 5.149262e-01
1 -2.24667 3.169007e-01 5.124510e-01
1 -2.1118 3.074534e-01 5.271240e-01
2 -2.39362 3.074534e-01 5.057851e-01
1 -2.3839 3.074534e-01 5.055657e-01
3 -2.5018 3.086801e-01 5.036606e-01
4 -1.35862 3.086801e-01 4.893751e-01
1 0.330429 3.086801e-01 4.777323e-01
1 1.28235 3.026690e-01 4.870684e-01
1 1.21328 3.026690e-01 4.874541e-01
1 -0.323542 3.181166e-01 4.634617e-01
1 -1.4306 3.181166e-01 4.712736e-01
1 -0.76211 3.290744e-01 4.542546e-01
1 -1.84706 3.290744e-01 4.789541e-01
1 -2.82177 3.193806e-01 4.940100e-01
3 -1.99212 3.193806e-01 5.098247e-01
1 -0.872117 3.285722e-01 4.955488e-01
1 -1.90381 3.285722e-01 4.709844e-01
2 -2.67413 3.198365e-01 4.845524e-01
2 -2.73808 3.176620e-01 4.879296e-01
3 -2.59269 3.109922e-01 4.982888e-01
2 -1.90096 3.109922e-01 4.889051e-01
1 -1.21352 3.109922e-01 4.828256e-01
2 -1.36252 3.131880e-01 4.794152e-01
2 -1.48214 3.167305e-01 4.739131e-01
1 -1.23864 3.113091e-01 4.823334e-01
1 -2.83129 3.113091e-01 5.052920e-01
1 -2.7617 3.100545e-01 5.072405e-01
2 -2.63176 3.100545e-01 5.020371e-01
1 -2.26901 3.100545e-01 4.955229e-01
1 -2.00039 3.072687e-01 4.998497e-01
1 -2.52233 3.072687e-01 5.180205e-01
1 -2.50346 3.070609e-01 5.183431e-01
3 -2.35662 3.070609e-01 5.229622e-01
2 -1.89399 3.029493e-01 5.293482e-01
2 0.364146 2.924259e-01 5.456926e-01
2 -0.736512 2.966557e-01 5.391231e-01
4 -1.85023 3.026414e-01 5.298264e-01
2 -2.55597 3.178178e-01 5.062552e-01
2 -2.63437 3.152824e-01 5.101931e-01
1 -2.22568 3.224460e-01 4.990669e-01
1 -2.1727 3.224460e-01 4.998263e-01
1 -2.548 3.168546e-01 5.085105e-01
1 -1.02088 3.168546e-01 4.701656e-01
1 -1.03154 3.185972e-01 4.674592e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 846 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000020 for Omega_m
0.000355 for b1
--> Not computing covariance matrix
2 -2.15252 3.185972e-01 4.774924e-01
2 -2.16184 3.185972e-01 4.776009e-01
1 -2.79246 3.185972e-01 4.887425e-01
6 -2.3004 3.256794e-01 4.777427e-01
2 -2.34341 3.252695e-01 4.783795e-01
1 -2.24727 3.261646e-01 4.769892e-01
1 -2.18954 3.261646e-01 4.745291e-01
1 -2.73766 3.171113e-01 4.885902e-01
1 -2.54656 3.171113e-01 4.849132e-01
1 -2.29982 3.232685e-01 4.753502e-01
1 -2.05854 3.232685e-01 4.715487e-01
1 -1.89029 3.253804e-01 4.682686e-01
1 -2.36166 3.253804e-01 4.815861e-01
2 -2.09995 3.275644e-01 4.781940e-01
1 -2.80245 3.112644e-01 5.035103e-01
2 -2.79942 3.112644e-01 5.108919e-01
1 -1.70741 3.112644e-01 5.274357e-01
1 -1.43208 3.194233e-01 5.147637e-01
4 -2.30566 3.194233e-01 5.060990e-01
1 -2.79423 3.194233e-01 4.888436e-01
2 -2.52383 3.081250e-01 5.063917e-01
2 -2.86451 3.146023e-01 4.963314e-01
3 -2.87129 3.161083e-01 4.939923e-01
1 -2.91957 3.161083e-01 4.992825e-01
1 -2.66799 3.218179e-01 4.904147e-01
1 -2.49161 3.218179e-01 4.963649e-01
1 -2.56213 3.209318e-01 4.977411e-01
1 0.217252 3.209318e-01 5.220997e-01
2 0.464438 2.999908e-01 5.546241e-01
1 -0.272665 3.076929e-01 5.426617e-01
3 -1.74815 3.076929e-01 5.312676e-01
5 -1.35217 3.224486e-01 5.083498e-01
1 -2.08796 3.224486e-01 5.009473e-01
1 -2.49101 3.163356e-01 5.104417e-01
3 -2.58358 3.163356e-01 4.867077e-01
1 -2.53193 3.135595e-01 4.910194e-01
2 -2.78327 3.135595e-01 4.960396e-01
2 -2.90416 3.135595e-01 5.013158e-01
1 -2.35254 3.135595e-01 5.172694e-01
3 -2.12726 3.195532e-01 5.079602e-01
1 -1.59493 3.195532e-01 4.705749e-01
1 -1.60755 3.168325e-01 4.748005e-01
2 -2.16332 3.168325e-01 4.802353e-01
1 -2.33138 3.168325e-01 4.822552e-01
1 -0.620247 3.348909e-01 4.542079e-01
4 -0.874429 3.348909e-01 4.671842e-01
1 -0.805643 3.348909e-01 4.700671e-01
1 0.350867 3.399592e-01 4.621953e-01
1 0.962004 3.399592e-01 4.715066e-01
2 0.079371 3.364099e-01 4.770193e-01
1 -0.821036 3.322030e-01 4.835532e-01
1 -1.26323 3.322030e-01 4.761060e-01
1 -0.787886 3.346428e-01 4.723166e-01
4 -0.92018 3.346428e-01 4.616863e-01
3 -0.917723 3.346428e-01 4.615430e-01
1 -1.48389 3.314255e-01 4.665400e-01
3 -0.691717 3.314255e-01 4.529291e-01
1 0.5239 3.383654e-01 4.421503e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 876 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000138 for Omega_m
0.000249 for b1
--> Not computing covariance matrix
1 0.515259 3.383654e-01 4.422519e-01
1 -0.802037 3.307042e-01 4.541510e-01
1 -0.43823 3.307042e-01 4.506332e-01
1 0.046121 3.339876e-01 4.455336e-01
1 -0.886338 3.339876e-01 4.576749e-01
1 -1.22046 3.320119e-01 4.607434e-01
2 -1.36393 3.320119e-01 4.646230e-01
1 -1.18894 3.320119e-01 4.601010e-01
2 0.0178628 3.384154e-01 4.501555e-01
1 0.50373 3.405623e-01 4.468209e-01
1 0.636447 3.405623e-01 4.440031e-01
2 0.173658 3.384865e-01 4.472272e-01
2 -1.79288 3.258965e-01 4.667812e-01
1 -1.94326 3.241492e-01 4.694951e-01
2 -2.30836 3.241492e-01 4.755929e-01
1 -2.01099 3.241492e-01 4.704174e-01
3 -1.39929 3.298493e-01 4.615642e-01
9 -0.864976 3.298493e-01 4.549616e-01
3 -0.578158 3.319364e-01 4.517201e-01
2 -1.04036 3.319364e-01 4.816876e-01
2 -1.36572 3.319364e-01 4.643557e-01
1 -1.0796 3.319364e-01 4.580737e-01
2 -1.64019 3.278001e-01 4.644980e-01
1 -1.47333 3.291676e-01 4.623739e-01
4 -1.8648 3.291676e-01 4.770348e-01
1 -1.82428 3.291676e-01 4.791752e-01
1 -1.53073 3.309943e-01 4.763381e-01
4 -1.38845 3.309943e-01 4.800891e-01
1 -1.38315 3.309943e-01 4.801978e-01
2 -2.11672 3.035969e-01 5.227501e-01
1 -1.16066 2.981831e-01 5.311585e-01
5 -0.749383 2.981831e-01 5.183442e-01
2 -2.24408 3.257517e-01 4.755262e-01
2 -2.32162 3.249834e-01 4.767194e-01
1 -2.50809 3.228031e-01 4.801056e-01
5 -1.96096 3.228031e-01 4.706316e-01
1 -2.08901 3.144065e-01 4.836729e-01
1 -2.89324 3.144065e-01 4.980856e-01
2 -2.30188 3.056374e-01 5.117052e-01
2 -1.47971 3.004323e-01 5.197895e-01
1 -1.26205 2.993499e-01 5.214706e-01
1 -1.34984 2.993499e-01 5.332005e-01
1 -2.37372 3.220214e-01 4.979883e-01
1 -2.62318 3.220214e-01 4.917188e-01
3 -2.81191 3.190797e-01 4.962878e-01
1 -2.15749 3.190797e-01 4.769073e-01
1 -2.13125 3.200519e-01 4.753973e-01
1 -2.78701 3.200519e-01 4.894297e-01
4 -2.81942 3.118011e-01 5.022444e-01
1 -2.90085 3.149551e-01 4.973457e-01
2 -2.81612 3.149551e-01 4.940129e-01
1 -2.82842 3.149551e-01 5.064404e-01
1 -2.24017 3.246319e-01 4.914109e-01
1 -2.40129 3.246319e-01 4.866450e-01
1 -2.776 3.200731e-01 4.937255e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 904 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000538 for Omega_m
0.000130 for b1
--> Not computing covariance matrix
1 -2.79042 3.200731e-01 4.899678e-01
1 -2.44696 3.245640e-01 4.829928e-01
1 -2.35622 3.245640e-01 4.772039e-01
1 -2.75057 3.160217e-01 4.904713e-01
1 -2.91234 3.160217e-01 5.004645e-01
1 -2.77482 3.100861e-01 5.096834e-01
2 -2.19476 3.100861e-01 4.944527e-01
1 -1.43073 3.100861e-01 4.866302e-01
3 -1.72466 3.202602e-01 4.708283e-01
1 -1.70995 3.202602e-01 5.105151e-01
1 -1.76056 3.196436e-01 5.114728e-01
2 -2.69527 3.196436e-01 4.985823e-01
1 -2.31376 3.196436e-01 5.054506e-01
2 -1.3476 3.280809e-01 4.923462e-01
1 -1.99215 3.232572e-01 4.998380e-01
1 -2.20274 3.232572e-01 4.969173e-01
1 -1.69177 3.273345e-01 4.905846e-01
1 -1.11758 3.273345e-01 4.970693e-01
1 0.0790098 3.337141e-01 4.871608e-01
1 0.120998 3.337141e-01 4.875158e-01
5 0.778004 3.365530e-01 4.831066e-01
3 -0.52863 3.365530e-01 4.645113e-01
1 -2.80446 3.112022e-01 5.038849e-01
2 -2.78026 3.112022e-01 5.027335e-01
1 -2.76256 3.112022e-01 5.124125e-01
1 -2.23331 3.046393e-01 5.226057e-01
1 -2.04251 3.046393e-01 5.099894e-01
1 -2.71981 3.118264e-01 4.988267e-01
1 -2.79063 3.118264e-01 5.009667e-01
1 -2.45221 3.072824e-01 5.080242e-01
1 -1.79519 3.072824e-01 4.973221e-01
1 -1.75239 3.069239e-01 4.978789e-01
1 -1.72065 3.069239e-01 4.975272e-01
1 -2.03799 3.100220e-01 4.927153e-01
1 -1.24646 3.100220e-01 4.852564e-01
2 -1.4382 3.125214e-01 4.813745e-01
1 -0.434569 3.038389e-01 4.948597e-01
1 -2.06877 3.038389e-01 5.148050e-01
2 -2.80698 3.114502e-01 5.029835e-01
2 0.210831 2.934340e-01 5.309653e-01
1 1.97778 2.881586e-01 5.391587e-01
6 1.81111 2.881586e-01 5.432672e-01
1 1.72416 2.881586e-01 5.492561e-01
1 -2.73397 3.173323e-01 5.039451e-01
2 -2.89849 3.173323e-01 4.951562e-01
5 -2.12824 3.173323e-01 4.790575e-01
1 -2.10332 3.193309e-01 4.759534e-01
1 -1.41199 3.193309e-01 4.693218e-01
1 -1.33565 3.140522e-01 4.775204e-01
2 0.154052 3.140522e-01 4.677004e-01
1 3.57567 3.140522e-01 4.516986e-01
1 3.42943 3.165540e-01 4.478130e-01
3 3.3158 3.165540e-01 4.482716e-01
1 3.51811 3.278470e-01 4.307319e-01
2 2.69226 3.278470e-01 4.343748e-01
1 -1.34949 3.278470e-01 4.607304e-01
1 -1.27538 3.284960e-01 4.597223e-01
1 -1.96632 3.284960e-01 4.740126e-01
1 -2.83548 3.175714e-01 4.909801e-01
2 -2.81571 3.175714e-01 4.902521e-01
1 -2.79631 3.175714e-01 4.896217e-01
1 -2.79416 3.176848e-01 4.894455e-01
1 -1.79075 3.176848e-01 4.750826e-01
1 -1.73599 3.145152e-01 4.800056e-01
1 -0.98102 3.145152e-01 4.740053e-01
3 -1.06038 3.182481e-01 4.682075e-01
1 -0.463773 3.182481e-01 4.641354e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 936 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000430 for Omega_m
0.000009 for b1
--> Not computing covariance matrix
3 -0.357437 3.230920e-01 4.566122e-01
2 -2.38083 3.230920e-01 4.769846e-01
1 -2.58213 3.230920e-01 4.864337e-01
1 -2.24264 3.263666e-01 4.813478e-01
1 -1.1322 3.263666e-01 4.592644e-01
1 -1.46333 3.145050e-01 4.776872e-01
2 -1.53561 3.145050e-01 4.782845e-01
1 -0.946138 3.145050e-01 4.737776e-01
5 -0.0469155 3.053960e-01 4.879252e-01
1 -0.894534 3.053960e-01 4.940973e-01
2 -1.31657 3.087018e-01 4.889628e-01
1 -0.779528 3.312885e-01 4.538825e-01
2 -0.115466 3.312885e-01 4.476413e-01
1 -1.01923 3.312885e-01 4.567789e-01
1 -1.83895 3.109636e-01 4.883464e-01
2 -1.29663 3.109636e-01 4.835445e-01
3 -2.82233 3.109636e-01 5.070969e-01
2 -2.92476 3.146702e-01 5.013400e-01
4 -2.27575 3.048248e-01 5.166314e-01
2 -2.69495 3.214823e-01 4.907598e-01
1 -2.74956 3.206718e-01 4.920186e-01
1 -2.7422 3.206718e-01 4.926167e-01
2 -2.61336 3.224279e-01 4.898893e-01
1 -2.49946 3.236984e-01 4.879160e-01
4 -2.37005 3.236984e-01 4.922097e-01
1 -2.33302 3.236984e-01 4.760143e-01
4 -2.59666 3.141974e-01 4.907708e-01
1 -2.60814 3.146848e-01 4.900137e-01
5 -2.92431 3.146848e-01 5.003251e-01
4 -2.91309 3.167471e-01 4.971221e-01
1 -2.76498 3.205484e-01 4.912181e-01
2 -1.90055 3.205484e-01 5.080047e-01
1 -2.00893 3.205484e-01 4.734062e-01
2 -1.85657 3.234732e-01 4.688636e-01
3 -2.00204 3.207333e-01 4.731190e-01
1 -2.40226 3.207333e-01 4.784475e-01
1 -2.41031 3.129202e-01 4.905825e-01
2 -2.80697 3.129202e-01 5.098952e-01
1 -2.88014 3.129202e-01 5.066309e-01
3 -2.85992 3.121753e-01 5.077878e-01
2 -0.824638 3.121753e-01 5.327149e-01
3 -2.09606 3.121753e-01 5.223477e-01
4 -1.31089 3.018152e-01 5.384385e-01
1 1.35792 2.901533e-01 5.565512e-01
3 2.35919 2.901533e-01 5.676917e-01
2 1.72018 2.924188e-01 5.641730e-01
2 -0.55565 3.065746e-01 5.421870e-01
1 -0.640514 3.082088e-01 5.396488e-01
1 -2.54875 3.082088e-01 5.067871e-01
3 -2.67933 3.098237e-01 5.042790e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 961 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000399 for Omega_m
0.000044 for b1
--> Not computing covariance matrix
1 -2.58571 3.098237e-01 5.016751e-01
1 -2.75308 3.191768e-01 4.871483e-01
5 -2.7704 3.191768e-01 4.877551e-01
1 -2.78222 3.188418e-01 4.882754e-01
1 -1.89471 3.188418e-01 4.743822e-01
3 -1.32519 3.075795e-01 4.918743e-01
4 -0.769714 3.075795e-01 4.874219e-01
1 -2.58628 3.075795e-01 5.141522e-01
1 -0.828758 2.967797e-01 5.309258e-01
1 -0.693371 2.967797e-01 5.409787e-01
1 -2.05868 3.050184e-01 5.281828e-01
2 -2.19831 3.050184e-01 5.249996e-01
1 -2.04032 3.050184e-01 5.083224e-01
2 -2.47495 3.089091e-01 5.022794e-01
1 -1.95891 3.044403e-01 5.092202e-01
1 -2.23921 3.044403e-01 5.196898e-01
1 -2.59883 3.077480e-01 5.145525e-01
1 -2.41822 3.077480e-01 5.052042e-01
4 -1.66708 3.022300e-01 5.137745e-01
2 -2.79685 3.180292e-01 4.892361e-01
1 -2.72591 3.200453e-01 4.861048e-01
1 -2.75764 3.200453e-01 4.874391e-01
1 -2.85384 3.169142e-01 4.923021e-01
1 -2.90526 3.169142e-01 4.982013e-01
6 -2.91881 3.140860e-01 5.025939e-01
2 -1.81555 3.292259e-01 4.790794e-01
1 -2.89788 3.172339e-01 4.977048e-01
1 -2.59935 3.172339e-01 4.856298e-01
2 -2.34381 3.232999e-01 4.762084e-01
1 -1.68579 3.294571e-01 4.666454e-01
1 -1.82919 3.294571e-01 4.759065e-01
2 -2.35116 3.254630e-01 4.821099e-01
2 -2.9144 3.160874e-01 4.966716e-01
1 -2.79291 3.200742e-01 4.904796e-01
1 -1.17214 3.200742e-01 5.153137e-01
1 -0.394611 3.263206e-01 5.056121e-01
3 -0.0168107 3.263206e-01 5.080754e-01
1 -0.316784 3.243360e-01 5.111577e-01
1 0.156259 3.243360e-01 5.140113e-01
1 -0.556231 3.179179e-01 5.239796e-01
2 -1.55036 3.179179e-01 5.170273e-01
1 -2.13456 3.179179e-01 5.115753e-01
1 -2.16274 3.091269e-01 5.252290e-01
1 -2.68453 3.091269e-01 5.142204e-01
1 -2.58047 3.216585e-01 4.947570e-01
1 -1.32775 3.216585e-01 5.104708e-01
2 -1.56156 3.190600e-01 5.145066e-01
3 -1.75875 3.154863e-01 5.200571e-01
1 -2.82638 3.154863e-01 5.055317e-01
1 -2.7422 3.105874e-01 5.131404e-01
1 -2.68154 3.105874e-01 5.150872e-01
1 -2.75865 3.135693e-01 5.104558e-01
1 -2.62989 3.135693e-01 5.131239e-01
4 -2.61802 3.124439e-01 5.148718e-01
1 -2.62399 3.149268e-01 5.110156e-01
2 -2.87151 3.149268e-01 5.049804e-01
4 -2.08135 3.149268e-01 4.826173e-01
1 -2.86023 3.149268e-01 4.955171e-01
2 -2.86439 3.156764e-01 4.943528e-01
1 -2.84738 3.174947e-01 4.915286e-01
1 -2.38552 3.174947e-01 5.094822e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 991 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000612 for Omega_m
0.000056 for b1
--> Not computing covariance matrix
2 -2.42826 3.107526e-01 5.199538e-01
1 -2.46171 3.120067e-01 5.180059e-01
1 -2.46194 3.120067e-01 4.934129e-01
1 -2.30203 3.236293e-01 4.753613e-01
1 -2.39852 3.236293e-01 4.775433e-01
1 -2.65277 3.191769e-01 4.844586e-01
1 -2.77452 3.191769e-01 4.879108e-01
2 -1.84964 3.292843e-01 4.722124e-01
1 -2.72372 3.203359e-01 4.861107e-01
3 -2.76279 3.203359e-01 4.931549e-01
2 -2.06727 3.274282e-01 4.821396e-01
2 -1.48925 3.311937e-01 4.762911e-01
1 -2.92323 3.149408e-01 5.015343e-01
2 -2.23562 3.149408e-01 5.163361e-01
1 -2.91771 3.149408e-01 5.022465e-01
1 -2.90966 3.161410e-01 5.003824e-01
1 -2.61496 3.161410e-01 5.088803e-01
2 -2.60663 3.114166e-01 5.162180e-01
3 -2.55561 3.100919e-01 5.182755e-01
1 -1.21222 3.100919e-01 5.331141e-01
1 -1.13369 3.079639e-01 5.364192e-01
5 0.118794 3.079639e-01 5.446148e-01
1 0.0670386 3.112490e-01 5.395125e-01
1 0.189365 3.112490e-01 5.401761e-01
1 0.196803 3.119601e-01 5.390717e-01
1 0.0194534 3.119601e-01 5.381115e-01
1 0.125492 3.151933e-01 5.330899e-01
1 1.26092 3.151933e-01 5.386526e-01
1 2.16337 3.234579e-01 5.258164e-01
1 1.92549 3.234579e-01 5.247938e-01
2 1.09665 3.160856e-01 5.362440e-01
1 2.10901 3.246124e-01 5.230007e-01
1 1.01738 3.246124e-01 5.179515e-01
2 0.278831 3.035048e-01 5.507346e-01
2 0.271451 3.035812e-01 5.506161e-01
1 0.212761 3.179049e-01 5.283692e-01
1 -2.83583 3.179049e-01 4.993491e-01
1 -0.126031 3.374374e-01 4.690123e-01
3 -0.0632322 3.374374e-01 4.701517e-01
2 -0.48004 3.355943e-01 4.730143e-01
1 -2.34573 3.242077e-01 4.906994e-01
1 -2.00325 3.242077e-01 4.968256e-01
1 -2.45529 3.086975e-01 5.209153e-01
1 -2.57324 3.086975e-01 5.054526e-01
2 -2.50544 3.079476e-01 5.066172e-01
2 -2.566 3.230901e-01 4.830987e-01
3 -0.310397 3.376739e-01 4.604479e-01
1 0.584467 3.376739e-01 4.410352e-01
3 -0.609443 3.304235e-01 4.522962e-01
1 -1.39705 3.304235e-01 4.826883e-01
1 -1.18047 3.316408e-01 4.807977e-01
3 -1.28136 3.316408e-01 4.789203e-01
1 -0.0502319 3.375505e-01 4.697417e-01
2 -0.243445 3.375505e-01 4.654551e-01
1 0.667047 3.375505e-01 4.401633e-01
1 0.478677 3.365631e-01 4.416968e-01
1 0.551117 3.365631e-01 4.410148e-01
1 -0.770226 3.272941e-01 4.554110e-01
1 -1.59285 3.272941e-01 4.920636e-01
3 -1.67188 3.267500e-01 4.929086e-01
5 -1.27662 3.267500e-01 4.604162e-01
1 -1.54295 3.234364e-01 4.655627e-01
1 -2.00379 3.234364e-01 4.707111e-01
1 -1.37212 3.296523e-01 4.610568e-01
2 -1.39788 3.296523e-01 4.614401e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1024 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000200 for Omega_m
0.000045 for b1
--> Not computing covariance matrix
1 -1.75759 3.296523e-01 4.694455e-01
1 -1.51087 3.312776e-01 4.669213e-01
1 -0.823578 3.312776e-01 4.543765e-01
1 -1.1487 3.068068e-01 4.923832e-01
1 -0.239688 3.068068e-01 4.856374e-01
1 -0.812409 3.123646e-01 4.770053e-01
1 -1.00696 3.123646e-01 4.783794e-01
2 -0.446605 3.068330e-01 4.869709e-01
2 -1.09707 3.139203e-01 4.759633e-01
1 -1.11246 3.142496e-01 4.754517e-01
2 -2.62945 3.142496e-01 4.912413e-01
1 -2.09329 3.142496e-01 4.840191e-01
1 -2.11765 3.150751e-01 4.827369e-01
3 -2.2217 3.150751e-01 4.839090e-01
1 -2.09765 3.120550e-01 4.885998e-01
1 -2.14778 3.120550e-01 4.891686e-01
2 -2.22281 3.135775e-01 4.868039e-01
1 -2.25967 3.146728e-01 4.851027e-01
1 -2.52496 3.146728e-01 4.886810e-01
1 -2.34603 3.107744e-01 4.947358e-01
1 -2.80999 3.107744e-01 5.068494e-01
3 -2.71441 3.212842e-01 4.905261e-01
2 -2.66914 3.212842e-01 4.933162e-01
1 -2.59825 3.212842e-01 4.956548e-01
1 -1.95048 3.272748e-01 4.863506e-01
1 -2.05688 3.272748e-01 4.835348e-01
1 -2.84537 3.183225e-01 4.974390e-01
2 -2.84152 3.183225e-01 4.976582e-01
1 -2.13035 3.183225e-01 4.776196e-01
1 -1.97911 3.225412e-01 4.710674e-01
1 -1.55005 3.225412e-01 4.665229e-01
1 -1.66316 3.160253e-01 4.766431e-01
2 -2.75537 3.160253e-01 5.063330e-01
3 -1.79989 3.160253e-01 5.186805e-01
1 -1.41898 3.214148e-01 5.103097e-01
1 -2.4144 3.214148e-01 4.991347e-01
1 -2.7176 3.131604e-01 5.119550e-01
1 -1.86316 3.131604e-01 5.231550e-01
1 -0.759405 3.265408e-01 5.023733e-01
1 -1.63467 3.265408e-01 4.940762e-01
1 -2.55529 3.150571e-01 5.119120e-01
1 -2.89978 3.150571e-01 4.970841e-01
1 -2.86515 3.130911e-01 5.001376e-01
1 -2.35949 3.130911e-01 5.179051e-01
1 -2.26325 3.174083e-01 5.111999e-01
1 -2.89664 3.174083e-01 4.950200e-01
2 -2.36263 3.253405e-01 4.827000e-01
2 -2.88362 3.179033e-01 4.942511e-01
1 -2.75007 3.208350e-01 4.896978e-01
2 -2.74992 3.208350e-01 4.895175e-01
4 -0.733678 3.208350e-01 4.621008e-01
1 -2.03836 3.208350e-01 4.734209e-01
2 -2.08282 3.194658e-01 4.755474e-01
1 -1.69231 3.088280e-01 4.920696e-01
2 -1.9586 3.088280e-01 4.948947e-01
1 -0.0465247 3.088280e-01 4.796396e-01
1 -0.468934 3.234538e-01 4.569235e-01
2 -2.54897 3.234538e-01 4.839239e-01
1 -2.26029 3.234538e-01 4.745905e-01
2 -2.5142 3.158466e-01 4.864056e-01
1 -2.39447 3.213456e-01 4.778647e-01
3 -2.71573 3.213456e-01 4.895426e-01
1 -2.90275 3.172411e-01 4.959176e-01
1 -2.75846 3.172411e-01 5.035702e-01
1 -2.80376 3.151021e-01 5.068924e-01
3 -2.90045 3.151021e-01 4.970384e-01
1 -2.80585 3.196498e-01 4.899752e-01
1 -2.09468 3.196498e-01 4.754521e-01
1 -1.17418 3.046195e-01 4.987963e-01
1 -0.5662 3.046195e-01 4.936613e-01
3 -0.989973 3.076116e-01 4.890141e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1059 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000156 for Omega_m
0.000059 for b1
--> Not computing covariance matrix
1 -2.53248 3.076116e-01 5.091402e-01
1 -2.49375 3.072215e-01 5.097461e-01
1 -1.49106 3.072215e-01 4.943466e-01
2 -1.68743 3.090013e-01 4.915823e-01
1 -1.99501 3.214046e-01 4.723182e-01
1 -2.71011 3.214046e-01 4.897793e-01
3 -2.75428 3.099103e-01 5.076315e-01
1 -2.75978 3.099103e-01 5.109244e-01
1 -2.76343 3.099715e-01 5.108294e-01
1 -2.7134 3.099715e-01 5.049444e-01
1 -2.89757 3.148437e-01 4.973772e-01
1 -2.43779 3.148437e-01 4.870818e-01
2 -2.27332 3.111386e-01 4.928363e-01
4 -2.15899 3.241037e-01 4.726997e-01
2 -1.95044 3.263631e-01 4.691905e-01
2 -1.85362 3.272558e-01 4.678040e-01
2 -2.37383 3.206495e-01 4.780646e-01
2 -2.20482 3.235120e-01 4.736186e-01
1 -1.48843 3.301258e-01 4.633465e-01
2 -0.970535 3.301258e-01 4.895272e-01
1 -1.60975 3.301258e-01 4.797148e-01
1 -2.90209 3.154891e-01 5.024477e-01
1 -2.91306 3.154891e-01 5.016682e-01
3 -1.84611 3.018170e-01 5.229030e-01
1 -1.62246 3.018170e-01 5.335179e-01
3 -2.1107 3.057050e-01 5.274793e-01
1 -1.98653 3.057050e-01 5.295079e-01
1 -2.17244 3.079845e-01 5.259675e-01
1 -2.49963 3.079845e-01 5.198347e-01
1 -2.72735 3.148394e-01 5.091880e-01
1 -1.51858 3.148394e-01 5.232331e-01
3 -1.52526 3.146096e-01 5.235900e-01
1 -1.0995 3.146096e-01 5.267497e-01
3 -1.00815 3.166451e-01 5.235883e-01
1 -2.88586 3.166451e-01 4.940810e-01
3 -2.86598 3.135344e-01 4.989124e-01
1 -1.92529 3.135344e-01 5.219633e-01
1 -0.948276 3.258019e-01 5.029100e-01
1 -0.398501 3.258019e-01 5.069375e-01
2 -1.4237 3.148792e-01 5.239021e-01
1 -1.3079 3.173631e-01 5.200443e-01
1 -2.54537 3.173631e-01 5.074530e-01
3 -2.60645 3.152438e-01 5.107446e-01
1 -2.90224 3.152438e-01 5.029138e-01
2 -2.80784 3.108405e-01 5.097527e-01
2 -2.89151 3.162450e-01 5.013587e-01
3 -2.32526 3.249339e-01 4.878637e-01
1 -1.53296 3.249339e-01 4.642156e-01
1 -1.79586 3.150398e-01 4.795825e-01
1 -2.78317 3.150398e-01 4.929553e-01
2 -2.52975 3.228377e-01 4.808441e-01
2 -2.33727 3.250469e-01 4.774128e-01
2 -2.36867 3.076819e-01 5.043833e-01
1 -2.32467 3.072621e-01 5.050353e-01
1 -1.91356 3.072621e-01 4.987692e-01
2 -1.8981 3.071293e-01 4.989754e-01
1 -2.23919 3.229552e-01 4.743955e-01
1 -0.466905 3.229552e-01 4.575139e-01
2 0.240916 3.309545e-01 4.450897e-01
1 -0.462821 3.230404e-01 4.573814e-01
2 -1.71365 3.230404e-01 4.676508e-01
2 -0.636561 3.230404e-01 5.122105e-01
2 1.15809 3.230404e-01 5.222246e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1091 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000236 for Omega_m
0.000046 for b1
--> Not computing covariance matrix
1 -0.849037 3.230404e-01 4.601248e-01
2 -0.0559602 3.314305e-01 4.470938e-01
1 -0.41371 3.284933e-01 4.516556e-01
1 -1.81702 3.284933e-01 4.682136e-01
1 -2.06931 3.263499e-01 4.715426e-01
2 -1.86153 3.263499e-01 4.677187e-01
3 -2.07236 3.263499e-01 4.716118e-01
2 -1.94756 3.274583e-01 4.698904e-01
1 -2.33995 3.234400e-01 4.761314e-01
1 -2.55258 3.234400e-01 4.844878e-01
2 -2.31714 3.257830e-01 4.808487e-01
3 -2.87813 3.132765e-01 5.002732e-01
2 -2.80091 3.132765e-01 4.972191e-01
1 -2.90166 3.132765e-01 5.047002e-01
1 -2.75932 3.098309e-01 5.100516e-01
1 -2.72297 3.098309e-01 5.134225e-01
2 -2.66118 3.088634e-01 5.149252e-01
1 -2.6851 3.200457e-01 4.975574e-01
5 -0.20049 3.200457e-01 4.597422e-01
2 -0.185436 3.208823e-01 4.584428e-01
3 -0.200999 3.176640e-01 4.634414e-01
1 -2.08984 3.176640e-01 4.781291e-01
1 -2.0851 3.182678e-01 4.771913e-01
4 -2.84788 3.182678e-01 4.975018e-01
1 -2.81759 3.182678e-01 4.898510e-01
2 -2.77505 3.194907e-01 4.879516e-01
1 -2.47865 3.239751e-01 4.809867e-01
1 -2.43871 3.239751e-01 4.889650e-01
1 -2.82486 3.186831e-01 4.971842e-01
2 -2.40683 3.186831e-01 4.806567e-01
5 -2.51861 3.186831e-01 5.048096e-01
2 -2.07649 3.239388e-01 4.966468e-01
1 -2.64522 3.149136e-01 5.106642e-01
1 -2.41919 3.149136e-01 4.866945e-01
1 -2.08813 3.247505e-01 4.714163e-01
1 -2.40725 3.247505e-01 4.798886e-01
5 -2.82611 3.180460e-01 4.903017e-01
1 -2.23626 3.180460e-01 5.101435e-01
1 -2.33034 3.109857e-01 5.211091e-01
1 -2.81528 3.109857e-01 5.058006e-01
1 -2.83082 3.112981e-01 5.053154e-01
1 -2.79663 3.112981e-01 5.030873e-01
2 -2.6994 3.096993e-01 5.055704e-01
6 -2.84055 3.122755e-01 5.015692e-01
1 -2.76902 3.107875e-01 5.038802e-01
1 -2.81368 3.107875e-01 5.084973e-01
1 -2.58996 3.076202e-01 5.134166e-01
2 -1.87966 3.076202e-01 5.299131e-01
1 -2.58973 3.076202e-01 5.133061e-01
3 -2.85454 3.116812e-01 5.069988e-01
3 -2.79916 3.116812e-01 5.017818e-01
3 -2.7745 3.201551e-01 4.886206e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1116 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000132 for Omega_m
0.000062 for b1
--> Not computing covariance matrix
6 -1.69034 3.201551e-01 4.706394e-01
1 -2.32276 3.201551e-01 4.777757e-01
1 -2.38156 3.174345e-01 4.820011e-01
1 -1.71052 3.174345e-01 4.747369e-01
1 -1.71086 3.176367e-01 4.744229e-01
1 -1.58656 3.176367e-01 4.733271e-01
1 -1.37371 3.240168e-01 4.634179e-01
2 -2.35068 3.240168e-01 4.765401e-01
1 -2.35058 3.240168e-01 4.913845e-01
1 -2.82494 3.169738e-01 5.023232e-01
2 -2.4712 3.169738e-01 4.839538e-01
1 -1.68874 3.169738e-01 5.177961e-01
1 -1.79861 3.134809e-01 5.232210e-01
3 -1.64085 3.134809e-01 5.245867e-01
1 -1.4602 3.180224e-01 5.175332e-01
1 -2.67985 3.180224e-01 5.034670e-01
1 -1.65334 3.282907e-01 4.875188e-01
3 -1.89078 3.282907e-01 4.697805e-01
1 -2.16655 3.259169e-01 4.734673e-01
1 -2.30109 3.259169e-01 4.811203e-01
3 -2.11877 3.274077e-01 4.788048e-01
1 -2.05771 3.274077e-01 4.826618e-01
2 -1.85113 3.288563e-01 4.804121e-01
1 -1.78314 3.293035e-01 4.797174e-01
1 0.727832 3.293035e-01 5.047310e-01
1 -0.363911 3.224185e-01 5.154244e-01
1 -2.10735 3.224185e-01 5.007827e-01
1 -1.97965 3.041661e-01 5.291313e-01
1 -2.13959 3.041661e-01 5.248848e-01
1 -1.90664 3.265846e-01 4.900656e-01
2 -2.2236 3.265846e-01 4.791030e-01
1 -2.21267 3.265846e-01 4.773168e-01
1 -0.790905 3.354221e-01 4.635909e-01
5 -0.662954 3.354221e-01 4.564914e-01
2 -1.57303 3.299934e-01 4.649231e-01
1 -2.30677 3.231862e-01 4.754955e-01
1 -2.57193 3.231862e-01 4.843259e-01
2 -2.51182 3.238668e-01 4.832690e-01
3 -2.8774 3.175191e-01 4.931278e-01
1 -2.79749 3.175191e-01 5.018035e-01
2 -2.76534 3.107863e-01 5.122607e-01
1 -2.55795 3.216523e-01 4.953842e-01
1 -2.6864 3.216523e-01 4.901540e-01
1 -2.92327 3.159296e-01 4.990422e-01
2 -2.24482 3.159296e-01 4.826717e-01
1 -1.55319 3.159296e-01 4.758642e-01
1 -1.3529 3.241398e-01 4.631125e-01
1 -1.8875 3.241398e-01 4.687832e-01
1 -2.15432 3.175285e-01 4.790516e-01
1 -2.89406 3.175285e-01 4.966148e-01
1 -2.62398 3.224499e-01 4.889710e-01
2 -1.53118 3.224499e-01 4.664429e-01
1 -2.53615 3.224499e-01 4.928897e-01
2 -2.26038 3.046433e-01 5.205460e-01
2 -2.84953 3.123781e-01 5.085326e-01
1 -2.82851 3.117154e-01 5.095619e-01
2 -2.83554 3.117154e-01 5.091328e-01
2 -2.44923 3.117154e-01 5.185549e-01
2 -2.12064 3.117154e-01 5.227298e-01
1 -2.67096 3.117154e-01 5.145977e-01
3 -2.34364 3.064057e-01 5.228444e-01
2 -2.36182 3.064057e-01 5.223370e-01
2 -2.43279 3.064057e-01 5.121489e-01
1 -0.843412 3.064057e-01 4.909667e-01
1 -1.60854 3.181677e-01 4.726986e-01
1 -1.60072 3.181677e-01 4.726305e-01
2 -1.14013 3.269895e-01 4.589290e-01
1 -1.29754 3.105621e-01 4.844430e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1151 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000087 for Omega_m
0.000028 for b1
--> Not computing covariance matrix
1 -2.56318 3.105621e-01 4.989211e-01
1 -1.47032 3.315066e-01 4.663913e-01
1 -0.969351 3.315066e-01 4.562054e-01
3 -1.26825 3.293359e-01 4.595768e-01
2 -1.66665 3.293359e-01 4.659983e-01
1 -1.51223 3.293359e-01 4.855044e-01
1 -1.53897 3.291712e-01 4.857602e-01
2 -1.21495 3.291712e-01 4.589232e-01
1 -1.73822 3.291712e-01 4.674255e-01
2 -2.59409 3.142992e-01 4.905238e-01
4 -2.47074 3.114074e-01 4.950153e-01
2 -0.982098 3.001473e-01 5.125039e-01
2 -2.05159 3.067188e-01 5.022974e-01
1 -0.97228 3.339977e-01 4.599292e-01
1 0.226424 3.339977e-01 4.874323e-01
2 -0.846323 3.285190e-01 4.959414e-01
3 -1.84649 3.208070e-01 5.079194e-01
1 -2.12828 3.208070e-01 5.048620e-01
1 -2.01975 3.220065e-01 5.029990e-01
3 -1.53818 3.220065e-01 5.078536e-01
1 -1.97612 3.157372e-01 5.175908e-01
1 -1.91711 3.157372e-01 5.181544e-01
2 -1.61151 3.205970e-01 5.106064e-01
1 -1.81108 3.179527e-01 5.147134e-01
3 -2.71979 3.179527e-01 5.027506e-01
2 -2.78993 3.132749e-01 5.100160e-01
1 -2.7965 3.144494e-01 5.081918e-01
1 -2.87377 3.144494e-01 5.056380e-01
2 -2.83493 3.120900e-01 5.093025e-01
3 -2.87299 3.150607e-01 5.046885e-01
1 -1.90762 3.150607e-01 4.806042e-01
1 -1.40859 3.273133e-01 4.615742e-01
1 -1.18541 3.273133e-01 4.591897e-01
1 -1.47445 3.239273e-01 4.644486e-01
1 -2.09512 3.239273e-01 4.964118e-01
1 -2.47067 3.197265e-01 5.029362e-01
2 -2.76155 3.197265e-01 4.874378e-01
1 -2.13972 3.197265e-01 5.074044e-01
1 -2.37503 3.133719e-01 5.172741e-01
1 -2.90313 3.133719e-01 5.046114e-01
1 -2.85746 3.182159e-01 4.970880e-01
1 -1.71877 3.182159e-01 4.736098e-01
2 -1.60487 3.222325e-01 4.673714e-01
2 -1.70135 3.158463e-01 4.772902e-01
2 -1.71496 3.166943e-01 4.759731e-01
2 -1.6176 3.134501e-01 4.810118e-01
1 -1.67834 3.204152e-01 4.701939e-01
1 -2.55664 3.204152e-01 4.814999e-01
1 -2.45338 3.222848e-01 4.785961e-01
1 -2.63687 3.222848e-01 4.849856e-01
8 -2.81978 3.123445e-01 5.004243e-01
2 -2.88145 3.148756e-01 4.964932e-01
1 -2.83782 3.185365e-01 4.908073e-01
1 -2.80681 3.185365e-01 4.985205e-01
2 -2.87248 3.129973e-01 5.071236e-01
1 -2.52215 3.227694e-01 4.919461e-01
2 -1.60583 3.227694e-01 5.053045e-01
1 1.87829 3.227694e-01 5.261056e-01
1 1.54321 3.202353e-01 5.300413e-01
1 -0.655633 3.202353e-01 5.184976e-01
1 -0.74501 3.192734e-01 5.199916e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1181 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000122 for Omega_m
0.000078 for b1
--> Not computing covariance matrix
5 -2.64181 3.192734e-01 4.841357e-01
2 -2.66736 3.183790e-01 4.855248e-01
1 -2.69172 3.163859e-01 4.886203e-01
1 -2.88692 3.163859e-01 5.012568e-01
1 -2.87263 3.170329e-01 5.002520e-01
2 -2.80026 3.170329e-01 5.029431e-01
2 -2.42836 3.170329e-01 5.098903e-01
1 -2.70811 3.170329e-01 5.052159e-01
1 -2.74671 3.154038e-01 5.077461e-01
1 -2.16217 3.154038e-01 5.163092e-01
1 -2.01996 3.185308e-01 5.114526e-01
1 -2.07479 3.185308e-01 4.767060e-01
1 -2.04294 3.146250e-01 4.827722e-01
1 -2.03342 3.146250e-01 5.190532e-01
1 -2.02622 3.149453e-01 5.185558e-01
2 -2.82429 3.149453e-01 5.065827e-01
1 -2.84231 3.149453e-01 4.948475e-01
1 -2.74389 3.201015e-01 4.868391e-01
1 -2.78781 3.201015e-01 4.924200e-01
1 -2.92191 3.160958e-01 4.986415e-01
1 -2.89791 3.160958e-01 4.953594e-01
2 -1.61245 3.308997e-01 4.723667e-01
1 -2.74274 3.104522e-01 5.041248e-01
1 -2.47427 3.104522e-01 5.195024e-01
2 -2.50134 3.161690e-01 5.106232e-01
1 -2.3543 3.082154e-01 5.229764e-01
2 -2.50141 3.082154e-01 5.054027e-01
2 -2.62671 3.082154e-01 5.102934e-01
1 -2.6151 3.082154e-01 5.095072e-01
1 -2.72334 3.212496e-01 4.892633e-01
1 -2.71887 3.212496e-01 4.903144e-01
1 -2.73662 3.209834e-01 4.907278e-01
1 -2.21809 3.209834e-01 5.032787e-01
3 -2.1926 3.212817e-01 5.028154e-01
1 -2.63605 3.212817e-01 4.945419e-01
1 -2.23109 3.254570e-01 4.880570e-01
1 -2.15274 3.254570e-01 4.727566e-01
1 -0.518872 3.362907e-01 4.559304e-01
3 0.576849 3.362907e-01 4.407480e-01
2 -0.0227351 3.326762e-01 4.463618e-01
1 -0.316875 3.305632e-01 4.496435e-01
1 -1.60954 3.305632e-01 4.767546e-01
3 -2.91296 3.165945e-01 4.984501e-01
3 -2.19605 3.165945e-01 5.136467e-01
2 -2.26149 3.125681e-01 5.199004e-01
1 -2.18104 3.169516e-01 5.130922e-01
1 -2.39701 3.169516e-01 4.829373e-01
1 -2.39388 3.161193e-01 4.842298e-01
2 -2.23907 3.161193e-01 4.822815e-01
1 -2.84764 3.161193e-01 4.930575e-01
1 -2.45429 3.077520e-01 5.060531e-01
1 -1.53134 3.077520e-01 4.933073e-01
1 -1.95442 3.218577e-01 4.713992e-01
2 -2.67145 3.218577e-01 4.898064e-01
1 -2.50263 3.218577e-01 4.797557e-01
1 -2.4247 3.230104e-01 4.779653e-01
2 -2.369 3.230104e-01 4.767377e-01
2 -1.79046 3.230104e-01 5.028318e-01
1 -2.58986 3.230104e-01 4.863585e-01
2 -2.92088 3.154070e-01 4.981678e-01
2 -2.78454 3.202472e-01 4.906502e-01
7 -2.92081 3.154829e-01 4.980498e-01
3 -2.82167 3.154829e-01 5.056793e-01
2 -2.64777 3.200195e-01 4.986333e-01
1 -2.43611 3.227105e-01 4.944538e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1214 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000046 for Omega_m
0.000145 for b1
--> Not computing covariance matrix
2 -1.69878 3.227105e-01 4.678093e-01
2 -0.926379 3.227105e-01 4.610945e-01
1 -2.60356 3.227105e-01 4.884575e-01
1 -1.98158 3.282066e-01 4.799213e-01
4 -1.79152 3.282066e-01 4.672940e-01
1 -1.84238 3.282066e-01 4.843331e-01
3 -2.86863 3.154531e-01 5.041410e-01
2 -2.91686 3.154531e-01 4.976479e-01
2 -1.9423 3.154531e-01 5.184465e-01
1 -2.91353 3.154531e-01 4.973432e-01
1 -2.90971 3.146563e-01 4.985808e-01
3 -2.13532 3.146563e-01 4.837047e-01
3 -1.86345 3.246381e-01 4.682016e-01
1 -2.39076 3.246381e-01 4.786207e-01
1 -1.48834 3.315653e-01 4.678618e-01
1 -0.672271 3.315653e-01 4.527188e-01
1 -0.369875 3.335329e-01 4.496629e-01
1 -0.730097 3.335329e-01 4.541962e-01
1 -0.0311727 3.372946e-01 4.483537e-01
1 -0.345225 3.372946e-01 4.555954e-01
1 -2.27175 3.247634e-01 4.750582e-01
1 -2.15488 3.247634e-01 4.725876e-01
2 -2.49096 3.189219e-01 4.816604e-01
1 -2.40443 3.122155e-01 4.920763e-01
1 -2.812 3.122155e-01 5.102598e-01
1 -2.84302 3.142680e-01 5.070720e-01
2 -2.91453 3.142680e-01 5.000271e-01
1 -2.62819 3.142680e-01 4.911819e-01
1 -2.24164 3.250087e-01 4.745001e-01
5 -2.19864 3.250087e-01 4.735221e-01
2 -2.43929 3.218591e-01 4.784138e-01
1 -2.53975 3.197805e-01 4.816422e-01
1 -2.68613 3.197805e-01 4.849012e-01
1 -1.45304 3.015370e-01 5.132360e-01
4 -0.671412 3.015370e-01 5.039404e-01
6 -1.23426 3.015370e-01 5.100468e-01
1 -1.26731 3.015370e-01 5.104837e-01
3 -2.52063 3.121522e-01 4.939968e-01
3 -2.82601 3.121522e-01 5.013081e-01
2 -2.71083 3.100251e-01 5.046117e-01
5 -0.880588 2.976726e-01 5.237970e-01
2 -0.491925 2.976726e-01 5.171969e-01
1 -0.767815 2.976726e-01 5.420660e-01
1 0.482314 2.925713e-01 5.499891e-01
2 0.270472 2.925713e-01 5.410967e-01
1 0.384035 2.925713e-01 5.344705e-01
1 -2.26879 3.049074e-01 5.153107e-01
1 -2.09116 3.049074e-01 5.098144e-01
1 -2.67615 3.210954e-01 4.846721e-01
2 -2.31311 3.210954e-01 4.767540e-01
1 -2.47587 3.210954e-01 4.794883e-01
2 -2.04316 3.265036e-01 4.710885e-01
2 -2.58668 3.153978e-01 4.883376e-01
1 -2.57344 3.184217e-01 4.836409e-01
2 -2.5793 3.184217e-01 5.044208e-01
2 -2.86139 3.184217e-01 4.957345e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1241 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000160 for Omega_m
0.000320 for b1
--> Not computing covariance matrix
1 -2.74969 3.184217e-01 4.874930e-01
1 -2.76892 3.175382e-01 4.888653e-01
1 -2.74657 3.175382e-01 5.031440e-01
2 -1.68516 3.285013e-01 4.861166e-01
1 -2.63018 3.198600e-01 4.995378e-01
4 -2.67396 3.198600e-01 4.984687e-01
1 -1.61717 3.198600e-01 4.703568e-01
1 -1.23633 3.263668e-01 4.602507e-01
1 -1.41744 3.263668e-01 4.620934e-01
1 -1.77455 3.210518e-01 4.703484e-01
1 -2.70679 3.210518e-01 4.860545e-01
1 -2.69826 3.211932e-01 4.858349e-01
1 -2.38827 3.211932e-01 4.778647e-01
1 -2.13478 3.088157e-01 4.970889e-01
2 -2.17279 3.088157e-01 4.975980e-01
1 -1.8304 3.088157e-01 5.293239e-01
1 -1.26419 3.025237e-01 5.390962e-01
1 -0.835083 3.025237e-01 5.433954e-01
1 -1.13629 3.053653e-01 5.389820e-01
2 -2.35467 3.053653e-01 5.177886e-01
1 -2.10243 3.053653e-01 5.080783e-01
2 -2.75108 3.133766e-01 4.956355e-01
1 -2.57254 3.099566e-01 5.009472e-01
5 -1.73567 3.099566e-01 4.897001e-01
1 -1.8411 3.112841e-01 4.876382e-01
1 0.0598945 3.112841e-01 4.736920e-01
1 -0.205673 3.155744e-01 4.670286e-01
1 1.53483 3.155744e-01 4.577785e-01
2 2.7231 3.048780e-01 4.743916e-01
4 2.62664 3.054306e-01 4.735333e-01
1 2.53063 3.060047e-01 4.726416e-01
1 -2.06262 3.060047e-01 5.049208e-01
1 -2.69705 3.170539e-01 4.877598e-01
1 -2.88004 3.170539e-01 4.997863e-01
1 -2.81918 3.110182e-01 5.091605e-01
3 -2.08955 3.110182e-01 4.908807e-01
1 -2.2933 3.180510e-01 4.799577e-01
1 -2.86529 3.180510e-01 4.924062e-01
1 -2.86908 3.132487e-01 4.998649e-01
2 -1.08052 3.132487e-01 4.771439e-01
1 -2.21648 3.132487e-01 4.874032e-01
1 -1.60339 3.062185e-01 4.983221e-01
1 -2.44372 3.062185e-01 5.179883e-01
2 -2.69259 3.090777e-01 5.135475e-01
1 -1.86991 3.281622e-01 4.839064e-01
1 -0.200964 3.281622e-01 5.019809e-01
1 -0.574443 3.258720e-01 5.055380e-01
2 -1.20368 3.258720e-01 5.005562e-01
2 -1.78615 3.258720e-01 4.943631e-01
2 -2.28219 3.258720e-01 4.836463e-01
1 -1.6025 3.258720e-01 4.644077e-01
3 -0.208127 3.002376e-01 5.042216e-01
1 0.109728 3.002376e-01 5.016587e-01
1 -0.0917262 3.011859e-01 5.001859e-01
2 -1.01927 3.011859e-01 5.418127e-01
1 -1.6917 3.011859e-01 5.209797e-01
1 -1.72631 3.013797e-01 5.206787e-01
1 -1.75909 3.013797e-01 5.224372e-01
2 -2.91246 3.136652e-01 5.033561e-01
2 -2.31865 3.254396e-01 4.850687e-01
4 -0.735341 3.351789e-01 4.699421e-01
2 -2.09654 3.272370e-01 4.822770e-01
2 -1.63238 3.303673e-01 4.774153e-01
1 -1.66443 3.301702e-01 4.777213e-01
1 -1.62663 3.301702e-01 4.789680e-01
1 -1.5322 3.307381e-01 4.780860e-01
1 -1.63774 3.307381e-01 4.708298e-01
1 -1.77657 3.298386e-01 4.722269e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1276 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000142 for Omega_m
0.000520 for b1
--> Not computing covariance matrix
3 -1.71772 3.298386e-01 4.686337e-01
1 -2.63733 3.121516e-01 4.961042e-01
2 -2.79046 3.121516e-01 4.999482e-01
2 -2.64195 3.121516e-01 4.961970e-01
3 -2.6645 3.121516e-01 4.966649e-01
2 -2.73873 3.179956e-01 4.875884e-01
1 -2.75656 3.155836e-01 4.913346e-01
1 -2.84465 3.155836e-01 4.937864e-01
1 -2.19345 3.054918e-01 5.094604e-01
2 -1.87074 3.054918e-01 5.038536e-01
1 -2.36849 3.054918e-01 5.169683e-01
1 -2.38297 3.246789e-01 4.871679e-01
2 -2.4278 3.246789e-01 4.844556e-01
1 -2.17058 3.246789e-01 4.926064e-01
3 -2.1321 3.040268e-01 5.246820e-01
1 -2.17353 3.040268e-01 5.182816e-01
2 -1.74738 3.013165e-01 5.224912e-01
1 -2.82933 3.110900e-01 5.073115e-01
1 -2.76491 3.110900e-01 5.025366e-01
2 -2.83337 3.187447e-01 4.906478e-01
4 -2.69827 3.214299e-01 4.864773e-01
2 -2.70975 3.212508e-01 4.867555e-01
3 -2.88501 3.148809e-01 4.966489e-01
2 -2.48789 3.148809e-01 5.132349e-01
1 -2.39057 3.148809e-01 5.145618e-01
1 -2.39465 3.122657e-01 5.186235e-01
1 -2.86537 3.122657e-01 5.074283e-01
1 -2.47468 3.235370e-01 4.899224e-01
3 -2.39667 3.235370e-01 4.922127e-01
1 -2.79332 3.178509e-01 5.010439e-01
1 -2.45079 3.178509e-01 5.077964e-01
2 -2.22626 3.064551e-01 5.254958e-01
1 -0.455989 2.956832e-01 5.422262e-01
2 -0.0989184 2.956832e-01 5.218439e-01
3 -0.222651 2.956832e-01 5.237330e-01
1 -1.01066 2.989358e-01 5.186812e-01
1 -0.883277 2.989358e-01 5.166210e-01
1 -1.86951 3.042786e-01 5.083229e-01
1 -2.0018 3.042786e-01 5.107753e-01
1 -2.39188 3.247453e-01 4.789875e-01
1 -1.8018 3.247453e-01 4.673708e-01
1 -2.11255 3.171166e-01 4.792192e-01
3 -2.8266 3.171166e-01 4.910737e-01
1 -1.31174 3.326522e-01 4.669447e-01
1 -1.03628 3.326522e-01 4.784293e-01
1 0.334679 3.388705e-01 4.687713e-01
1 0.152382 3.388705e-01 4.655173e-01
5 -1.55679 3.305792e-01 4.783950e-01
1 -1.65702 3.305792e-01 4.738848e-01
1 -1.05051 3.339988e-01 4.685735e-01
1 0.0182969 3.339988e-01 4.457914e-01
1 -0.887305 3.270478e-01 4.565874e-01
1 -2.00462 3.270478e-01 4.861830e-01
2 -2.27133 3.249175e-01 4.894915e-01
1 -1.71489 3.290319e-01 4.831014e-01
3 -1.87532 3.290319e-01 4.718977e-01
4 -2.26666 3.258797e-01 4.767934e-01
2 -2.80315 3.173100e-01 4.901035e-01
2 -2.72016 3.200183e-01 4.858972e-01
1 -2.55022 3.093332e-01 5.024927e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1306 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000278 for Omega_m
0.000586 for b1
--> Not computing covariance matrix
1 -2.64445 3.093332e-01 5.161624e-01
2 -2.62048 3.198193e-01 4.998759e-01
2 -2.11695 3.252573e-01 4.914299e-01
2 -2.61905 3.198420e-01 4.998407e-01
2 -2.41374 3.224800e-01 4.957433e-01
4 -2.09522 3.037003e-01 5.249111e-01
2 -2.78417 3.129397e-01 5.105608e-01
1 -2.79531 3.145763e-01 5.080191e-01
2 -2.1987 3.145763e-01 4.845688e-01
2 -2.53037 3.145763e-01 4.889491e-01
2 -2.86051 3.145763e-01 5.059811e-01
1 -2.87556 3.145763e-01 4.968442e-01
2 -1.88704 3.029446e-01 5.149098e-01
1 -2.00515 3.037058e-01 5.137276e-01
1 -1.81032 3.037058e-01 5.096797e-01
3 -1.12439 2.999182e-01 5.155624e-01
2 -1.25717 2.999182e-01 5.178697e-01
1 -0.678294 2.999182e-01 5.453119e-01
1 -1.44091 3.061816e-01 5.355839e-01
2 -1.83762 3.061816e-01 5.313552e-01
1 -2.20485 3.061816e-01 5.258441e-01
2 -2.36681 3.081633e-01 5.227663e-01
1 -2.50391 3.107836e-01 5.186966e-01
1 -2.64696 3.107836e-01 5.158648e-01
2 -2.58677 3.095287e-01 5.178139e-01
1 -2.25965 3.055152e-01 5.240475e-01
1 -1.9622 3.055152e-01 5.298892e-01
1 -1.84284 3.043923e-01 5.316331e-01
2 -2.06909 3.043923e-01 5.117428e-01
2 -1.77326 3.043923e-01 5.326545e-01
2 -2.0257 3.043923e-01 5.283883e-01
2 -1.76776 3.043923e-01 5.327318e-01
1 -2.04174 3.043923e-01 5.111088e-01
1 -1.20497 2.996183e-01 5.185236e-01
2 -1.36078 2.996183e-01 5.222996e-01
3 -1.45208 2.996183e-01 5.293464e-01
1 -2.82721 3.168150e-01 5.026374e-01
1 -0.306509 3.168150e-01 4.654949e-01
7 0.153985 3.096313e-01 4.766522e-01
1 0.633627 3.096313e-01 4.739433e-01
2 0.124623 3.186885e-01 4.598762e-01
6 0.816762 3.304600e-01 4.415934e-01
1 0.260444 3.240397e-01 4.515650e-01
1 -1.51231 3.240397e-01 4.647176e-01
1 -1.60275 3.225781e-01 4.669878e-01
1 -2.20151 3.225781e-01 4.740096e-01
1 -2.33909 3.196704e-01 4.785257e-01
1 -2.71319 3.196704e-01 4.857228e-01
1 -2.43175 3.083464e-01 5.033105e-01
2 -2.59457 3.083464e-01 5.170720e-01
1 -2.64343 3.083464e-01 5.105859e-01
1 -2.81338 3.108425e-01 5.067091e-01
1 -2.16336 3.108425e-01 5.233816e-01
1 -2.16348 3.108468e-01 5.233750e-01
1 -2.80661 3.108468e-01 5.058850e-01
4 -2.90405 3.171858e-01 4.960396e-01
1 -2.89742 3.174679e-01 4.956015e-01
1 -2.80951 3.174679e-01 5.015621e-01
1 -2.4708 3.228013e-01 4.932785e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1336 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000261 for Omega_m
0.000600 for b1
--> Not computing covariance matrix
2 -2.26907 3.228013e-01 4.973042e-01
1 -2.58776 3.228013e-01 4.834502e-01
3 -2.82301 3.129769e-01 4.987088e-01
4 -1.95915 3.129769e-01 4.851589e-01
1 -2.8236 3.129769e-01 4.987299e-01
2 -2.83307 3.182528e-01 4.905357e-01
1 -2.84004 3.179967e-01 4.909335e-01
1 -2.37254 3.179967e-01 4.810775e-01
1 -2.23007 3.118328e-01 4.906510e-01
2 -2.35341 3.118328e-01 4.922525e-01
1 -1.58959 3.118328e-01 4.841027e-01
2 -1.74031 3.148704e-01 4.793850e-01
1 -1.70895 3.212620e-01 4.694579e-01
1 -0.302983 3.212620e-01 4.586510e-01
2 -0.128782 3.249495e-01 4.529238e-01
2 -0.324671 3.172225e-01 4.649249e-01
1 -0.337478 3.189870e-01 4.621844e-01
2 -1.67674 3.189870e-01 4.721016e-01
2 -0.681613 3.189870e-01 5.210017e-01
2 0.687982 3.189870e-01 5.286141e-01
1 -1.82164 3.189870e-01 5.123826e-01
1 -1.92254 3.085141e-01 5.286484e-01
1 -1.09137 3.085141e-01 5.360828e-01
2 -1.03602 3.074014e-01 5.378111e-01
4 -1.08864 3.154138e-01 5.253666e-01
2 -0.927054 3.181857e-01 5.210614e-01
4 -1.05277 3.161822e-01 5.241731e-01
2 -1.14136 3.100334e-01 5.337232e-01
1 0.617919 2.954418e-01 5.563860e-01
1 0.713768 2.954418e-01 5.572255e-01
1 -0.961222 3.155066e-01 5.260620e-01
1 -1.545 3.155066e-01 5.218053e-01
1 -1.5978 3.113229e-01 5.283031e-01
1 -2.83184 3.113229e-01 5.052598e-01
2 -2.86871 3.121963e-01 5.039034e-01
3 -1.2254 3.329371e-01 4.716898e-01
1 -1.18103 3.329371e-01 4.622463e-01
1 -1.54533 3.306863e-01 4.657421e-01
1 -1.50596 3.306863e-01 4.646581e-01
3 -2.53828 3.133211e-01 4.916288e-01
1 -2.90277 3.133211e-01 5.045981e-01
2 -2.91891 3.152267e-01 5.016384e-01
2 -2.75199 3.203776e-01 4.936383e-01
3 -2.6521 3.083415e-01 5.123322e-01
1 -1.8939 3.083415e-01 4.954712e-01
2 -1.76363 3.271434e-01 4.662690e-01
1 -1.43486 3.298179e-01 4.621151e-01
1 -0.2489 3.298179e-01 4.494885e-01
1 -0.529376 3.272083e-01 4.535416e-01
1 -1.67154 3.272083e-01 4.649138e-01
1 0.0702891 3.380451e-01 4.480826e-01
2 0.851338 3.380451e-01 4.385677e-01
1 -0.164126 3.380451e-01 4.536540e-01
1 -1.20252 3.326868e-01 4.619763e-01
1 -0.978675 3.326868e-01 4.792458e-01
3 -2.64998 3.197969e-01 4.992657e-01
3 -2.21288 3.197969e-01 5.063641e-01
2 -2.40616 3.160416e-01 5.121966e-01
1 -2.43952 3.143975e-01 5.147501e-01
1 -2.07645 3.143975e-01 5.190134e-01
1 -1.19251 3.254422e-01 5.018594e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1366 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000387 for Omega_m
0.000550 for b1
--> Not computing covariance matrix
1 -1.69342 3.254422e-01 4.968739e-01
1 -1.92544 3.235433e-01 4.998232e-01
2 -2.52452 3.235433e-01 4.821565e-01
1 -2.39177 3.235433e-01 4.923073e-01
3 -2.29432 3.050165e-01 5.210822e-01
1 -2.28324 3.050165e-01 5.217815e-01
1 -2.73757 3.104843e-01 5.132891e-01
1 -2.43425 3.104843e-01 5.201251e-01
1 -2.48838 3.126950e-01 5.166916e-01
1 -2.87914 3.126950e-01 5.066211e-01
1 -2.70654 3.207619e-01 4.940920e-01
1 -2.61942 3.207619e-01 4.828046e-01
2 -2.56262 3.217625e-01 4.812506e-01
2 -2.69134 3.133942e-01 4.942478e-01
1 -2.4938 3.097957e-01 4.998367e-01
1 -2.69916 3.097957e-01 5.144459e-01
1 -2.5929 3.208601e-01 4.972613e-01
1 -2.73955 3.208601e-01 4.915303e-01
1 -2.44486 3.243803e-01 4.860629e-01
1 -2.43525 3.243803e-01 4.866446e-01
1 -2.56905 3.074254e-01 5.129781e-01
1 -2.26185 3.074254e-01 5.032717e-01
4 -2.2298 3.071321e-01 5.037272e-01
1 -2.01405 3.053720e-01 5.064611e-01
1 -0.670717 3.053720e-01 4.923928e-01
2 -1.01935 3.079620e-01 4.883701e-01
1 -1.0613 3.276509e-01 4.577903e-01
4 -1.32268 3.276509e-01 4.604882e-01
1 -1.50317 3.276509e-01 4.626277e-01
1 -1.0658 3.310707e-01 4.573163e-01
1 -1.16122 3.310707e-01 4.586623e-01
2 -0.87817 3.328976e-01 4.558249e-01
1 0.829995 3.413665e-01 4.426714e-01
1 1.45759 3.413665e-01 4.344097e-01
1 0.0103457 3.339903e-01 4.458660e-01
1 1.45223 3.339903e-01 4.351143e-01
1 1.03926 3.309646e-01 4.398137e-01
1 2.73872 3.309646e-01 4.307231e-01
2 4.04285 3.395548e-01 4.173812e-01
1 3.51293 3.365612e-01 4.220307e-01
1 0.777587 3.365612e-01 4.390131e-01
1 -0.197449 3.302363e-01 4.488365e-01
1 -1.46773 3.302363e-01 4.630778e-01
1 -2.43121 3.148609e-01 4.869582e-01
3 -2.91697 3.148609e-01 5.024405e-01
1 -2.91659 3.152321e-01 5.018639e-01
2 -2.76651 3.152321e-01 4.921888e-01
1 -1.44762 3.152321e-01 4.762255e-01
1 -1.29591 3.121267e-01 4.810486e-01
1 -2.18836 3.121267e-01 4.894831e-01
1 -2.30556 3.188260e-01 4.790782e-01
3 -1.96676 3.188260e-01 5.113384e-01
1 -2.0647 3.171261e-01 5.139787e-01
1 -2.90508 3.171261e-01 4.960195e-01
1 -2.71795 3.094469e-01 5.079464e-01
2 -2.47218 3.094469e-01 5.004925e-01
1 -2.7134 3.094469e-01 5.132320e-01
1 -2.75224 3.193254e-01 4.978893e-01
1 -2.75961 3.193254e-01 4.873354e-01
1 -1.46512 3.317393e-01 4.680547e-01
1 -1.04017 3.317393e-01 4.573100e-01
1 -2.03799 3.222674e-01 4.720213e-01
1 -2.64954 3.222674e-01 4.865200e-01
1 -2.73505 3.210339e-01 4.884358e-01
5 -2.47282 3.210339e-01 4.992308e-01
3 -0.863403 2.969992e-01 5.365603e-01
2 -0.612155 2.969992e-01 5.226122e-01
2 -0.814868 2.969992e-01 5.274626e-01
2 0.077772 2.969992e-01 5.520382e-01
1 0.236151 2.969992e-01 5.535101e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1401 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000305 for Omega_m
0.000828 for b1
--> Not computing covariance matrix
2 -0.9339 3.051676e-01 5.408234e-01
1 -1.07876 3.169144e-01 5.225789e-01
1 -2.53251 3.169144e-01 4.849796e-01
1 -2.52539 3.177878e-01 4.836231e-01
1 -2.1935 3.177878e-01 5.111994e-01
2 -1.73782 3.232624e-01 5.026965e-01
1 -2.09841 3.193343e-01 5.087974e-01
1 -2.8165 3.193343e-01 4.901676e-01
2 -2.19832 3.267908e-01 4.785866e-01
1 -2.29224 3.259942e-01 4.798238e-01
4 -2.14144 3.259942e-01 4.878412e-01
1 -2.0604 3.259942e-01 4.896074e-01
4 -2.55673 3.211610e-01 4.971140e-01
2 -2.71945 3.103357e-01 5.139273e-01
3 -2.72801 3.183746e-01 5.014418e-01
3 -2.85983 3.183746e-01 4.922843e-01
1 -2.90107 3.145440e-01 4.982338e-01
4 -2.90289 3.145440e-01 4.983513e-01
3 -2.81582 3.145440e-01 5.075016e-01
2 -2.63632 3.089573e-01 5.161786e-01
1 -2.64113 3.198864e-01 4.992041e-01
2 -2.35719 3.198864e-01 4.785513e-01
1 -2.80384 3.198864e-01 4.917201e-01
1 -1.83427 3.293463e-01 4.770275e-01
6 -1.83924 3.293463e-01 4.719955e-01
6 -1.82117 3.293463e-01 4.708535e-01
1 -1.15488 3.293463e-01 4.582015e-01
3 -1.84428 3.211164e-01 4.709839e-01
2 -1.93522 3.211164e-01 4.719529e-01
1 -2.03428 3.211164e-01 4.730724e-01
1 -1.04455 3.313647e-01 4.571552e-01
1 -0.99245 3.313647e-01 4.564543e-01
2 -1.07336 3.308034e-01 4.573262e-01
4 -1.92954 3.220364e-01 4.709426e-01
2 -1.94639 3.130099e-01 4.849621e-01
2 -0.950755 3.316462e-01 4.560172e-01
1 -1.9973 3.141844e-01 4.831380e-01
1 -2.9181 3.141844e-01 5.028519e-01
1 -2.65674 3.084066e-01 5.118256e-01
1 -2.53243 3.084066e-01 5.054678e-01
1 -2.80125 3.126428e-01 4.988885e-01
3 -2.34722 3.126428e-01 4.903295e-01
2 -2.38644 3.200608e-01 4.788082e-01
1 -2.26866 3.112660e-01 4.924678e-01
1 -2.0399 3.112660e-01 4.897452e-01
1 -2.07698 3.224580e-01 4.723623e-01
3 -1.29211 3.224580e-01 5.088185e-01
1 -1.58154 3.194358e-01 5.135125e-01
1 -2.15803 3.194358e-01 5.078855e-01
3 -2.0113 3.212637e-01 5.050465e-01
3 -1.72932 3.212637e-01 5.079381e-01
1 -2.03939 3.092289e-01 5.266299e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1426 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000261 for Omega_m
0.000526 for b1
--> Not computing covariance matrix
1 -1.97735 3.092289e-01 5.273292e-01
1 -1.89514 3.077413e-01 5.296396e-01
3 -1.87303 3.077413e-01 5.298880e-01
2 -0.764176 2.988065e-01 5.437651e-01
2 -1.12717 3.009316e-01 5.404645e-01
1 -1.38323 3.027163e-01 5.376927e-01
2 -0.863803 3.027163e-01 5.430531e-01
1 -1.29554 3.027163e-01 5.387270e-01
1 -1.6046 3.055088e-01 5.343898e-01
1 -2.30563 3.055088e-01 5.225422e-01
1 -2.72208 3.112039e-01 5.136970e-01
3 -2.83144 3.112039e-01 5.083508e-01
2 -1.56607 3.002433e-01 5.253744e-01
1 -2.84008 3.114015e-01 5.080440e-01
1 -2.62536 3.114015e-01 5.158573e-01
2 -2.43645 3.078533e-01 5.213680e-01
1 -2.31119 3.063836e-01 5.236507e-01
1 -1.68938 3.063836e-01 4.987696e-01
1 -2.09155 3.237855e-01 4.717419e-01
1 -2.37561 3.237855e-01 4.770408e-01
4 -2.68574 3.157817e-01 4.894719e-01
2 -2.11094 3.065297e-01 5.038416e-01
1 -2.06821 3.061803e-01 5.043843e-01
1 -0.670153 3.061803e-01 4.902387e-01
1 -1.16461 3.105040e-01 4.835233e-01
1 0.662376 3.105040e-01 4.719342e-01
1 4.38015 2.931453e-01 4.988948e-01
1 2.16896 2.931453e-01 5.116194e-01
2 2.48562 2.921842e-01 5.131121e-01
1 -0.436047 3.037319e-01 4.951769e-01
1 -1.27193 3.037319e-01 5.025648e-01
4 -1.90022 3.084593e-01 4.952224e-01
1 -1.13012 3.028955e-01 5.038639e-01
1 -1.66802 3.028955e-01 5.337883e-01
1 -1.93032 3.219197e-01 5.042408e-01
1 -2.6757 3.219197e-01 4.871648e-01
1 -2.91133 3.157917e-01 4.966824e-01
1 -2.5745 3.157917e-01 5.102394e-01
1 -2.00068 3.240106e-01 4.974742e-01
3 -2.46872 3.240106e-01 4.874380e-01
1 -2.784 3.199732e-01 4.937086e-01
4 -2.13166 3.199732e-01 5.069017e-01
6 -1.53282 3.199732e-01 5.127162e-01
2 -2.42335 3.199732e-01 4.794675e-01
1 -1.77842 3.199732e-01 5.105512e-01
4 -1.8513 3.069985e-01 5.307029e-01
1 -2.02849 3.103311e-01 5.255268e-01
1 -2.34796 3.103311e-01 4.959151e-01
1 -0.641671 2.988614e-01 5.137293e-01
1 -0.725293 2.988614e-01 5.443112e-01
1 -1.9741 3.129780e-01 5.223859e-01
1 -2.87352 3.129780e-01 5.070667e-01
1 -2.09821 3.034191e-01 5.219132e-01
1 -2.0455 3.034191e-01 5.258484e-01
1 -2.483 3.073390e-01 5.197602e-01
1 -1.49255 3.073390e-01 4.940426e-01
1 -2.07902 3.170392e-01 4.789768e-01
1 -2.89219 3.170392e-01 4.990260e-01
3 -2.52047 3.233143e-01 4.892798e-01
1 -2.56447 3.233143e-01 4.853470e-01
2 -1.77851 3.018684e-01 5.186557e-01
1 -1.56965 3.007092e-01 5.204561e-01
3 -1.60853 3.007092e-01 5.218952e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1459 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000022 for Omega_m
0.000225 for b1
--> Not computing covariance matrix
2 -2.9258 3.152418e-01 4.993239e-01
1 -2.88136 3.180340e-01 4.949873e-01
1 -2.80894 3.180340e-01 5.000049e-01
2 -2.81154 3.179669e-01 5.001091e-01
2 -2.70965 3.094146e-01 5.133920e-01
1 -2.55131 3.221738e-01 4.935752e-01
2 -2.45744 3.221738e-01 4.958860e-01
2 -2.24231 3.221738e-01 4.996274e-01
1 -1.98112 3.221738e-01 5.029970e-01
1 -1.93072 3.226685e-01 5.022285e-01
1 -1.69816 3.226685e-01 5.046808e-01
1 -2.19159 3.108490e-01 5.230382e-01
1 -2.27783 3.108490e-01 5.219633e-01
1 -1.45187 3.016122e-01 5.363095e-01
2 -1.54219 3.016122e-01 5.347744e-01
1 -1.12269 3.016122e-01 5.406889e-01
1 -1.16559 3.019136e-01 5.402208e-01
1 -0.438235 3.019136e-01 5.470245e-01
2 -1.01991 3.145705e-01 5.273664e-01
2 -0.895339 3.171406e-01 5.233746e-01
1 -1.06608 3.119082e-01 5.315013e-01
1 -1.71072 3.119082e-01 5.264696e-01
1 -1.27359 3.211282e-01 5.121497e-01
1 -2.61544 3.211282e-01 4.826632e-01
3 -2.73261 3.141555e-01 4.934928e-01
2 -2.91888 3.141555e-01 5.010864e-01
2 -2.73801 3.141555e-01 4.936149e-01
5 -2.75364 3.141555e-01 4.939780e-01
1 -2.77564 3.161174e-01 4.909308e-01
1 -2.9124 3.161174e-01 5.001939e-01
1 -2.83238 3.188798e-01 4.959035e-01
1 -0.116806 3.188798e-01 4.609968e-01
1 -0.11565 3.193456e-01 4.602733e-01
1 1.79426 3.193456e-01 4.502350e-01
1 1.88994 3.241266e-01 4.428095e-01
2 0.244222 3.241266e-01 4.515555e-01
2 0.74103 3.241266e-01 4.486980e-01
1 -0.249772 3.241266e-01 4.546584e-01
1 -0.259499 3.135592e-01 4.710711e-01
1 -1.85459 3.135592e-01 4.829511e-01
1 -1.83317 3.218552e-01 4.700662e-01
1 -2.30934 3.218552e-01 4.995510e-01
2 -2.06195 3.040915e-01 5.271407e-01
1 -2.66857 3.138615e-01 5.119665e-01
1 -2.72754 3.138615e-01 4.940015e-01
1 -2.64156 3.117012e-01 4.973567e-01
3 -2.19427 3.117012e-01 5.219130e-01
1 -1.97626 3.070292e-01 5.291693e-01
3 -1.76985 3.070292e-01 5.315924e-01
1 -1.66121 3.056950e-01 5.336647e-01
1 -2.34791 3.056950e-01 5.131222e-01
1 -2.33777 3.056111e-01 5.132525e-01
1 -1.73849 3.056111e-01 5.328194e-01
3 -1.74316 3.056616e-01 5.327410e-01
2 -1.77183 3.056616e-01 5.323973e-01
1 -0.85101 3.056616e-01 5.410233e-01
1 -0.918562 3.065899e-01 5.395816e-01
4 -1.49495 3.065899e-01 5.347355e-01
1 -2.39172 3.065899e-01 5.095212e-01
3 -0.333685 2.955485e-01 5.266701e-01
1 0.130788 2.955485e-01 5.195357e-01
1 -0.801157 2.993388e-01 5.136487e-01
1 -0.527347 2.993388e-01 5.467610e-01
1 -0.7715 3.008489e-01 5.444156e-01
3 -1.54548 3.008489e-01 5.187766e-01
3 -2.79625 3.197572e-01 4.894093e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1491 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000072 for Omega_m
0.000197 for b1
--> Not computing covariance matrix
2 -2.64118 3.197572e-01 4.995923e-01
1 -2.62853 3.197572e-01 4.998801e-01
1 -2.79609 3.136300e-01 5.093965e-01
1 -2.43361 3.136300e-01 5.160875e-01
3 -2.33496 3.094732e-01 5.225437e-01
2 -2.7362 3.094732e-01 5.105241e-01
1 -2.67246 3.094732e-01 5.054950e-01
2 -2.73047 3.209970e-01 4.875968e-01
5 -2.82346 3.120765e-01 5.014517e-01
2 -2.56875 3.120765e-01 5.162005e-01
3 -2.80075 3.120765e-01 5.005394e-01
3 -2.5692 3.231042e-01 4.834118e-01
3 -2.48967 3.231042e-01 4.797738e-01
1 -2.76231 3.165552e-01 4.899454e-01
1 -1.51329 3.165552e-01 4.744636e-01
1 -1.48868 3.203362e-01 4.685911e-01
1 -2.57158 3.203362e-01 4.993879e-01
1 -1.4402 3.298067e-01 4.846788e-01
1 -0.747194 3.298067e-01 4.928061e-01
1 -1.1192 3.276098e-01 4.962182e-01
2 -0.984987 3.276098e-01 4.974529e-01
4 -1.54666 3.276098e-01 4.915599e-01
2 -1.9831 3.276098e-01 4.838672e-01
1 -2.04842 3.276098e-01 4.733312e-01
2 -2.77143 3.176219e-01 4.888440e-01
1 -2.46804 3.087770e-01 5.025814e-01
1 -2.49945 3.087770e-01 5.032619e-01
1 -2.81013 3.160476e-01 4.919696e-01
1 -2.46772 3.160476e-01 4.853779e-01
1 -2.47048 3.168329e-01 4.841583e-01
1 -2.45533 3.168329e-01 4.839378e-01
1 -2.38065 3.204046e-01 4.783903e-01
1 0.646693 3.204046e-01 4.543431e-01
3 0.778374 3.243681e-01 4.481872e-01
1 -0.188836 3.243681e-01 4.539774e-01
1 -0.0729627 3.260383e-01 4.513835e-01
2 0.380057 3.260383e-01 4.485152e-01
1 -0.915827 3.260383e-01 4.576178e-01
1 -0.918149 3.260110e-01 4.576601e-01
4 -1.82448 3.260110e-01 4.671952e-01
1 -2.23999 3.260110e-01 4.760273e-01
1 -2.75519 3.134906e-01 4.954733e-01
1 -2.90982 3.134906e-01 5.034315e-01
1 -2.77387 3.100764e-01 5.087344e-01
2 -0.901059 3.100764e-01 4.825057e-01
1 -1.51746 3.100764e-01 4.874035e-01
1 -1.80485 3.149350e-01 4.798574e-01
2 -2.59913 3.149350e-01 4.893876e-01
2 -2.92523 3.149350e-01 4.998213e-01
3 -2.90745 3.149350e-01 5.031109e-01
1 -1.47415 3.309768e-01 4.781956e-01
1 -1.5194 3.309768e-01 4.768617e-01
1 -2.45161 3.241336e-01 4.874902e-01
3 -1.30031 3.241336e-01 5.044725e-01
1 -1.83486 3.072354e-01 5.307179e-01
2 -1.5975 3.072354e-01 5.331868e-01
1 -0.960912 3.072354e-01 5.385638e-01
1 0.0863499 3.261047e-01 5.092569e-01
1 -1.47419 3.261047e-01 4.972634e-01
1 -1.82915 3.233001e-01 5.016193e-01
1 -2.34909 3.233001e-01 4.941781e-01
1 -2.78448 3.124545e-01 5.110230e-01
1 -2.88013 3.124545e-01 5.061078e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1524 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000184 for Omega_m
0.000064 for b1
--> Not computing covariance matrix
4 -2.89858 3.131721e-01 5.049933e-01
1 -2.77671 3.101225e-01 5.097298e-01
1 -2.63239 3.101225e-01 5.165311e-01
2 -2.72721 3.135009e-01 5.112838e-01
2 -2.58095 3.091837e-01 5.179892e-01
1 -2.71841 3.127640e-01 5.124283e-01
3 -2.70713 3.127640e-01 4.960648e-01
5 -2.68432 3.200421e-01 4.847609e-01
3 -2.71249 3.200421e-01 4.967281e-01
1 -1.90821 3.278383e-01 4.846194e-01
3 -2.06234 3.278383e-01 4.760625e-01
1 -2.87796 3.153431e-01 4.954693e-01
4 -2.5782 3.153431e-01 5.110272e-01
1 -2.92542 3.153431e-01 5.003893e-01
1 -2.68804 3.215620e-01 4.907305e-01
1 -2.3685 3.215620e-01 4.772841e-01
3 -2.39791 3.209876e-01 4.781762e-01
3 -1.20567 3.209876e-01 4.653970e-01
1 -1.12749 3.228461e-01 4.625104e-01
4 -2.55958 3.228461e-01 4.901665e-01
1 -2.39176 3.228461e-01 4.949213e-01
5 -1.6732 3.285709e-01 4.860298e-01
1 -1.36748 3.285709e-01 4.608256e-01
1 -1.93206 3.126752e-01 4.855140e-01
3 -1.86053 3.126752e-01 4.848086e-01
1 -1.6733 3.100452e-01 4.888934e-01
1 -2.76759 3.100452e-01 5.107407e-01
1 -2.64741 3.083126e-01 5.134316e-01
1 -2.64205 3.083126e-01 5.141898e-01
1 -2.43681 3.061151e-01 5.176029e-01
1 -1.90959 3.061151e-01 5.022926e-01
1 -2.51196 3.196740e-01 4.812336e-01
1 -2.81276 3.196740e-01 4.910067e-01
1 -1.74487 3.300134e-01 4.749481e-01
1 -1.57911 3.300134e-01 4.650953e-01
2 0.406402 3.404264e-01 4.489224e-01
1 -1.03737 3.334274e-01 4.597928e-01
1 -1.14354 3.334274e-01 4.634618e-01
1 -2.7043 3.190432e-01 4.858026e-01
1 -2.68311 3.190432e-01 5.006867e-01
1 -2.62961 3.089260e-01 5.164003e-01
1 -2.66353 3.089260e-01 5.149347e-01
2 -2.45894 3.228841e-01 4.932557e-01
1 -2.09393 3.261723e-01 4.881485e-01
1 -1.50248 3.261723e-01 4.967570e-01
1 -2.06545 3.213083e-01 5.043115e-01
1 -2.26969 3.213083e-01 5.016978e-01
1 -2.34439 3.203823e-01 5.031360e-01
1 -2.71355 3.203823e-01 4.857289e-01
2 -2.79011 3.134374e-01 4.965155e-01
2 -2.82567 3.163289e-01 4.920245e-01
3 -2.57578 3.094448e-01 5.027165e-01
3 -2.27351 3.094448e-01 5.234606e-01
1 -1.09148 2.992293e-01 5.393269e-01
1 -1.00894 2.992293e-01 5.407135e-01
1 -2.07194 3.077423e-01 5.274916e-01
3 -2.59101 3.077423e-01 5.115765e-01
3 -2.56497 3.074631e-01 5.120102e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1551 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000211 for Omega_m
0.000094 for b1
--> Not computing covariance matrix
1 -1.51889 3.074631e-01 4.939600e-01
2 -1.76997 3.248809e-01 4.669076e-01
1 -2.01088 3.210196e-01 4.729047e-01
1 -2.63086 3.210196e-01 4.831035e-01
2 -1.39682 3.011950e-01 5.138940e-01
1 -1.95646 3.282462e-01 4.718795e-01
1 -1.95513 3.282462e-01 4.718247e-01
3 -0.954901 3.344780e-01 4.621459e-01
1 -0.852618 3.344780e-01 4.717915e-01
1 -2.77545 3.100963e-01 5.096598e-01
1 -2.73345 3.100963e-01 5.132220e-01
4 -2.8471 3.155310e-01 5.047812e-01
1 -2.85085 3.151233e-01 5.054144e-01
1 -2.81431 3.151233e-01 5.065600e-01
2 -2.37997 3.231429e-01 4.941043e-01
1 -2.29971 3.239261e-01 4.928879e-01
1 -1.2114 3.239261e-01 4.620594e-01
3 -1.40127 3.189968e-01 4.697154e-01
3 -1.85946 3.189968e-01 4.738157e-01
1 -1.81861 3.205992e-01 4.713269e-01
2 -2.52636 3.205992e-01 4.807704e-01
1 -2.75635 3.205992e-01 4.919051e-01
2 -2.76962 3.100411e-01 5.083034e-01
2 -2.81026 3.196465e-01 4.933848e-01
2 -2.74522 3.096620e-01 5.088923e-01
1 -2.92348 3.158745e-01 4.992433e-01
3 -2.87998 3.158745e-01 4.947086e-01
2 -2.7497 3.204758e-01 4.875621e-01
1 -2.85931 3.175970e-01 4.920333e-01
1 -0.23751 3.175970e-01 4.637727e-01
1 -0.245716 3.188812e-01 4.617781e-01
1 -0.426644 3.188812e-01 4.629101e-01
6 -0.368324 3.219527e-01 4.581396e-01
1 -0.253245 3.243338e-01 4.544414e-01
3 -2.20415 3.243338e-01 4.734804e-01
2 -2.38279 3.218259e-01 4.773756e-01
2 -2.49018 3.138748e-01 4.897249e-01
1 -2.51053 3.146024e-01 4.885948e-01
3 -2.35958 3.146024e-01 5.154477e-01
2 -2.34431 3.153946e-01 5.142173e-01
1 -1.66892 3.244075e-01 5.002189e-01
1 -2.46142 3.244075e-01 4.839247e-01
2 -2.02602 3.280783e-01 4.782234e-01
1 -1.75931 3.299021e-01 4.753907e-01
1 -1.76327 3.299021e-01 4.750043e-01
1 -1.41556 3.320118e-01 4.717278e-01
2 -0.948903 3.320118e-01 4.826681e-01
2 -1.42273 3.320118e-01 4.710282e-01
1 -0.921573 3.320118e-01 4.830348e-01
1 -1.60181 3.280685e-01 4.891593e-01
1 -1.97248 3.280685e-01 4.813958e-01
1 -2.27682 3.257244e-01 4.850365e-01
3 -2.30511 3.257244e-01 4.782745e-01
6 -1.29629 3.327593e-01 4.673482e-01
2 -2.85036 3.153231e-01 4.944293e-01
1 -2.76309 3.197703e-01 4.875221e-01
2 -2.28967 3.197703e-01 4.777317e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1581 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000423 for Omega_m
0.000153 for b1
--> Not computing covariance matrix
1 -2.77145 3.197703e-01 4.879131e-01
2 -2.18446 3.052208e-01 5.105105e-01
2 -2.79817 3.191297e-01 4.889079e-01
1 -2.21828 3.265380e-01 4.774018e-01
1 -1.82547 3.265380e-01 4.915213e-01
2 -1.83285 3.264843e-01 4.916047e-01
1 -2.56365 3.190154e-01 5.032050e-01
1 -1.24609 3.190154e-01 5.170764e-01
1 -0.000803058 3.285513e-01 5.022657e-01
1 -0.650536 3.285513e-01 4.975057e-01
1 -1.94081 3.170425e-01 5.153806e-01
4 -1.37501 3.170425e-01 5.201796e-01
2 -2.74982 3.170425e-01 4.889720e-01
1 -2.67434 3.170425e-01 4.873071e-01
3 -2.6614 3.180042e-01 4.858135e-01
1 -1.86541 3.180042e-01 4.753084e-01
1 -1.54387 3.251840e-01 4.641572e-01
2 -2.37056 3.251840e-01 4.797504e-01
1 -1.75484 3.251840e-01 4.969493e-01
1 -2.50471 3.150517e-01 5.126861e-01
1 -2.91294 3.150517e-01 4.979991e-01
1 -2.6704 3.090884e-01 5.072611e-01
1 -2.67583 3.090884e-01 5.146170e-01
1 0.21303 2.927712e-01 5.399601e-01
1 0.745806 2.927712e-01 5.263535e-01
2 1.00706 2.919490e-01 5.276304e-01
2 0.119884 2.948882e-01 5.230655e-01
1 -1.13736 3.000773e-01 5.150060e-01
1 -1.52492 3.000773e-01 5.248173e-01
2 -2.07726 3.033270e-01 5.197700e-01
1 -2.75815 3.098084e-01 5.097034e-01
1 -1.414 3.098084e-01 4.871346e-01
1 -1.3836 3.094880e-01 4.876322e-01
3 -2.42023 3.094880e-01 5.211722e-01
4 -2.45128 3.172383e-01 5.091349e-01
2 -2.38685 3.185436e-01 5.071075e-01
1 -2.30409 3.198361e-01 5.051001e-01
1 -2.50359 3.198361e-01 5.020925e-01
1 -2.69592 3.147448e-01 5.100000e-01
1 -2.1987 3.147448e-01 5.171002e-01
1 -1.82796 3.212694e-01 5.069666e-01
1 -2.50614 3.212694e-01 4.978569e-01
4 -2.74944 3.168206e-01 5.047665e-01
2 -2.68619 3.102172e-01 5.150227e-01
2 -2.68669 3.102271e-01 5.150072e-01
3 -2.1987 3.244546e-01 4.929098e-01
3 -1.7119 3.244546e-01 4.996210e-01
1 -2.36786 3.108695e-01 5.207207e-01
1 -2.72423 3.108695e-01 5.137572e-01
2 -2.7875 3.131098e-01 5.102777e-01
2 -2.78159 3.159132e-01 5.059236e-01
2 -2.79629 3.144573e-01 5.081848e-01
4 -2.70808 3.182162e-01 5.023466e-01
3 -2.38484 3.061438e-01 5.210970e-01
1 -2.359 3.061438e-01 5.220318e-01
4 -2.37563 3.063105e-01 5.217727e-01
1 -2.47744 3.074242e-01 5.200430e-01
1 -1.5636 3.074242e-01 5.333360e-01
1 -1.18354 3.032596e-01 5.398043e-01
1 -2.0599 3.032596e-01 5.241103e-01
1 -2.57983 3.079101e-01 5.168874e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1611 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000336 for Omega_m
0.000149 for b1
--> Not computing covariance matrix
1 -1.8333 3.079101e-01 5.301765e-01
2 -1.7392 3.065669e-01 5.322626e-01
1 -1.30869 3.024993e-01 5.385803e-01
1 -1.9589 3.024993e-01 5.239104e-01
1 -2.37235 3.055793e-01 5.191266e-01
1 -1.82641 3.055793e-01 5.029573e-01
2 -0.918408 3.002668e-01 5.112085e-01
1 -2.2356 3.092400e-01 4.972717e-01
1 -2.69944 3.092400e-01 5.080211e-01
1 -2.4597 3.066033e-01 5.121163e-01
1 -2.19523 3.066033e-01 5.050058e-01
1 -2.49603 3.228484e-01 4.797746e-01
3 -1.99855 3.228484e-01 4.710588e-01
1 -2.17753 3.176094e-01 4.791959e-01
1 -2.8938 3.176094e-01 4.954268e-01
1 -2.19171 3.267407e-01 4.812446e-01
1 -0.442882 3.267407e-01 5.041618e-01
2 -0.331614 3.274204e-01 5.031061e-01
2 -1.18117 3.210990e-01 5.129241e-01
4 -0.635568 3.254883e-01 5.061069e-01
1 -0.620678 3.255890e-01 5.059505e-01
2 -1.00552 3.255890e-01 5.030280e-01
2 -0.782734 3.255890e-01 5.047655e-01
1 -0.340168 3.255890e-01 5.078736e-01
2 1.48057 3.348159e-01 4.935429e-01
2 -0.349828 3.255251e-01 5.079728e-01
1 -0.839665 3.217976e-01 5.137622e-01
2 -2.68443 3.217976e-01 4.873474e-01
4 -2.30255 3.217976e-01 4.760582e-01
2 -2.50571 3.217976e-01 4.798355e-01
1 -2.40218 3.217976e-01 4.777382e-01
2 -2.52009 3.141681e-01 4.895880e-01
1 -1.5398 3.036595e-01 5.059094e-01
2 -2.0139 3.036595e-01 5.142293e-01
2 0.0691117 3.036595e-01 4.917758e-01
1 -0.580289 3.036595e-01 4.965088e-01
1 -1.74671 3.186337e-01 4.732517e-01
1 -2.40816 3.186337e-01 4.807377e-01
1 -2.38549 3.141409e-01 4.877156e-01
3 -2.6764 3.141409e-01 4.923448e-01
1 -2.6962 3.151836e-01 4.907253e-01
2 -1.88612 3.151836e-01 5.194693e-01
1 -2.63062 3.151836e-01 5.104395e-01
1 -2.31988 3.066893e-01 5.236325e-01
1 -2.4923 3.066893e-01 5.172215e-01
2 -2.82267 3.179599e-01 4.997165e-01
1 -2.76521 3.192387e-01 4.977304e-01
1 -2.8343 3.192387e-01 4.932620e-01
1 -2.91079 3.168741e-01 4.969345e-01
2 -2.2828 3.168741e-01 4.815792e-01
1 -2.14791 3.168741e-01 5.136130e-01
1 -1.86477 3.055077e-01 5.312668e-01
1 -1.34814 3.055077e-01 4.978173e-01
1 -1.59773 3.074209e-01 4.948457e-01
2 -1.73239 3.074209e-01 5.316709e-01
3 -2.56333 3.074209e-01 5.123084e-01
1 -2.71574 3.092432e-01 5.094782e-01
2 -2.47117 3.092432e-01 5.011130e-01
2 -2.71268 3.092432e-01 5.091008e-01
2 -2.4786 3.092432e-01 5.012593e-01
1 -2.68984 3.092432e-01 5.074188e-01
1 -2.75686 3.207181e-01 4.895966e-01
1 -2.07192 3.207181e-01 5.057465e-01
2 -2.1521 3.196963e-01 5.073334e-01
1 -1.38651 3.008561e-01 5.365950e-01
2 -1.67699 3.008561e-01 5.241730e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1644 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000198 for Omega_m
0.000120 for b1
--> Not computing covariance matrix
1 -1.68557 3.008561e-01 5.255600e-01
1 -2.41794 3.059317e-01 5.176769e-01
1 -2.36473 3.059317e-01 5.122613e-01
2 -2.91485 3.152834e-01 4.977367e-01
1 -2.71316 3.096411e-01 5.065000e-01
1 -2.62361 3.096411e-01 5.168504e-01
2 -2.19323 3.047064e-01 5.245147e-01
1 -2.60092 3.192151e-01 5.019807e-01
1 -0.44367 3.192151e-01 4.625089e-01
1 -0.392845 3.217646e-01 4.585491e-01
1 0.35905 3.217646e-01 4.539760e-01
6 0.352604 3.167850e-01 4.617100e-01
2 0.374509 3.160701e-01 4.628204e-01
1 1.2669 3.064141e-01 4.778176e-01
1 -0.404419 3.064141e-01 4.877316e-01
2 -1.10981 3.138741e-01 4.761450e-01
4 -1.20984 3.189041e-01 4.683327e-01
1 0.0170525 3.037577e-01 4.918574e-01
1 0.407741 3.037577e-01 4.893160e-01
1 -0.60814 3.117123e-01 4.769613e-01
1 -2.60247 3.117123e-01 5.160001e-01
1 -2.47249 3.190872e-01 5.045458e-01
1 -2.61098 3.190872e-01 4.836480e-01
1 -1.85351 3.284610e-01 4.690891e-01
1 -1.72932 3.284610e-01 4.662942e-01
1 -2.41266 3.132281e-01 4.899532e-01
1 -2.87668 3.132281e-01 5.003391e-01
1 -2.89428 3.170324e-01 4.944305e-01
1 -2.88124 3.170324e-01 4.935264e-01
2 -2.84349 3.127369e-01 5.001980e-01
1 -2.39981 3.249942e-01 4.811606e-01
1 -2.27505 3.249942e-01 4.753398e-01
1 -2.68094 3.179320e-01 4.863084e-01
1 -2.88459 3.179320e-01 4.950722e-01
1 -2.92556 3.152945e-01 4.991686e-01
1 -2.88757 3.152945e-01 4.959982e-01
1 -2.83488 3.126435e-01 5.001158e-01
1 -2.48343 3.126435e-01 5.168372e-01
1 -2.46642 3.155357e-01 5.123450e-01
1 -2.85038 3.155357e-01 4.940642e-01
8 -2.74174 3.115411e-01 5.002685e-01
1 -2.83834 3.143709e-01 4.958733e-01
1 -2.39295 3.143709e-01 5.154172e-01
1 -1.40778 3.266139e-01 4.964021e-01
1 -1.65477 3.266139e-01 4.647702e-01
1 -1.61464 3.270027e-01 4.641663e-01
1 -1.65889 3.270027e-01 4.647537e-01
2 -1.02416 3.318826e-01 4.571746e-01
1 -1.08617 3.314740e-01 4.578092e-01
1 0.407756 3.314740e-01 4.435736e-01
1 1.33137 3.372745e-01 4.345645e-01
1 -0.168824 3.372745e-01 4.507510e-01
2 -0.888434 3.334554e-01 4.566827e-01
1 -1.15677 3.318123e-01 4.592347e-01
1 -1.39353 3.318123e-01 4.749022e-01
1 -1.5613 3.308395e-01 4.764130e-01
3 -1.5915 3.308395e-01 4.681726e-01
1 -1.93259 3.284834e-01 4.718320e-01
3 -1.59093 3.284834e-01 4.639225e-01
1 -2.30799 3.179113e-01 4.803426e-01
1 -1.0398 3.179113e-01 4.685852e-01
1 -0.680895 3.103847e-01 4.802750e-01
2 -2.07344 3.103847e-01 4.922234e-01
1 -2.79088 3.103847e-01 5.095392e-01
3 -2.77188 3.199302e-01 4.947137e-01
3 -2.78445 3.199302e-01 4.939224e-01
1 -1.8067 3.292148e-01 4.795020e-01
1 -1.31215 3.292148e-01 4.888060e-01
1 -1.25977 3.295262e-01 4.883224e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1679 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000119 for Omega_m
0.000212 for b1
--> Not computing covariance matrix
1 -1.82162 3.295262e-01 4.754800e-01
1 -1.88061 3.291300e-01 4.760954e-01
1 -1.88126 3.291300e-01 4.760050e-01
1 -2.48591 3.241680e-01 4.837115e-01
1 -2.46304 3.241680e-01 4.866109e-01
3 -2.8897 3.176230e-01 4.967763e-01
1 -2.78872 3.176230e-01 4.893401e-01
1 -2.78833 3.143864e-01 4.943670e-01
1 -2.41864 3.143864e-01 4.876855e-01
2 -2.42807 3.147537e-01 4.871150e-01
2 -2.44184 3.154668e-01 4.860074e-01
1 -2.43854 3.152647e-01 4.863213e-01
1 -1.97764 3.152647e-01 4.809281e-01
1 -1.73991 3.106645e-01 4.880730e-01
1 -2.02771 3.106645e-01 4.910258e-01
3 -2.16486 3.128617e-01 4.876133e-01
1 -1.74312 3.128617e-01 4.833162e-01
3 -1.82299 3.146977e-01 4.804646e-01
2 -2.53711 3.146977e-01 5.128274e-01
1 -1.89442 3.146977e-01 4.811444e-01
5 -1.91486 3.194722e-01 4.737289e-01
1 -2.72356 3.194722e-01 4.861053e-01
1 -2.51814 3.230023e-01 4.806226e-01
1 -2.58268 3.230023e-01 4.876137e-01
1 -2.72823 3.211083e-01 4.905553e-01
3 -2.5225 3.211083e-01 4.980305e-01
1 -2.49047 3.215101e-01 4.974064e-01
1 -2.62945 3.215101e-01 4.938287e-01
3 -2.18165 3.259713e-01 4.868999e-01
1 -2.23727 3.259713e-01 4.850715e-01
1 -1.96821 3.280183e-01 4.818922e-01
2 -2.0408 3.280183e-01 4.770352e-01
3 -1.9828 3.280183e-01 4.721074e-01
1 -2.35887 3.246236e-01 4.773799e-01
2 -2.1001 3.246236e-01 4.716303e-01
1 -2.42965 3.246236e-01 4.808476e-01
2 -1.74744 3.300485e-01 4.724219e-01
2 -1.38719 3.322537e-01 4.689968e-01
1 -2.3024 3.258421e-01 4.789551e-01
1 -2.26617 3.258421e-01 4.766379e-01
2 -2.38498 3.246713e-01 4.784564e-01
1 -2.79848 3.171407e-01 4.901524e-01
1 -2.85321 3.171407e-01 5.008461e-01
1 -2.79134 3.107219e-01 5.108155e-01
1 -2.46079 3.107219e-01 5.194723e-01
1 -2.50778 3.145202e-01 5.135729e-01
1 -2.66345 3.145202e-01 4.913346e-01
1 -2.54863 3.115655e-01 4.959237e-01
3 -2.31582 3.115655e-01 5.205960e-01
1 -2.30425 3.110906e-01 5.213337e-01
1 -1.58357 3.110906e-01 5.287567e-01
1 -1.41508 3.070086e-01 5.350965e-01
2 -2.48911 3.070086e-01 5.188897e-01
2 -1.81514 3.070086e-01 5.311073e-01
1 -2.11021 3.070086e-01 5.022129e-01
1 -2.61442 3.142665e-01 4.909403e-01
1 -2.86884 3.142665e-01 5.061053e-01
2 -2.39802 3.058534e-01 5.191722e-01
1 -2.04488 3.030896e-01 5.234648e-01
1 -2.00447 3.030896e-01 5.177990e-01
3 -1.39482 2.996584e-01 5.231281e-01
1 -1.44894 2.996584e-01 5.259090e-01
2 -2.84644 3.184991e-01 4.966466e-01
1 -2.91796 3.147008e-01 5.025458e-01
1 -2.89107 3.147008e-01 5.044517e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1711 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000319 for Omega_m
0.000446 for b1
--> Not computing covariance matrix
4 -2.4875 3.231536e-01 4.913233e-01
1 -2.76367 3.101432e-01 5.115304e-01
1 -2.30914 3.101432e-01 4.958509e-01
1 -1.87534 3.059576e-01 5.023517e-01
4 -1.05577 3.059576e-01 4.938896e-01
3 -2.42245 3.059576e-01 5.164029e-01
2 -2.91561 3.149084e-01 5.025011e-01
1 -1.52441 3.000296e-01 5.256100e-01
3 -1.04682 3.000296e-01 5.138918e-01
1 -1.77429 3.292227e-01 4.685506e-01
3 -1.35495 3.292227e-01 4.606975e-01
1 -2.11154 3.193784e-01 4.759872e-01
2 -2.80469 3.193784e-01 4.953888e-01
4 -0.941882 3.193784e-01 4.656400e-01
2 -2.76194 3.193784e-01 4.874143e-01
1 -2.8059 3.193784e-01 4.953135e-01
3 -2.51869 3.233518e-01 4.891423e-01
2 -2.34022 3.233518e-01 4.761344e-01
1 -2.5298 3.233518e-01 4.817890e-01
1 -2.83701 3.171695e-01 4.913910e-01
2 -2.28156 3.171695e-01 4.811048e-01
1 -2.88452 3.171695e-01 4.936713e-01
3 -2.63678 3.223800e-01 4.855785e-01
2 -2.62961 3.223800e-01 4.890846e-01
2 -0.552986 3.223800e-01 5.143189e-01
1 -1.57786 3.223800e-01 5.065612e-01
1 -1.31378 3.245927e-01 5.031246e-01
1 -2.42517 3.245927e-01 4.855778e-01
1 -0.852627 3.347332e-01 4.698281e-01
1 -0.900227 3.347332e-01 4.613907e-01
1 -2.70655 3.134482e-01 4.944494e-01
1 -2.83821 3.134482e-01 4.980138e-01
1 -2.39824 3.069160e-01 5.081593e-01
1 -2.33815 3.069160e-01 5.233210e-01
1 -1.58203 3.275699e-01 4.912425e-01
4 -0.634561 3.275699e-01 5.004693e-01
1 -2.09494 3.275699e-01 4.789560e-01
2 -2.31118 3.258141e-01 4.816829e-01
2 -2.64474 3.223438e-01 4.870728e-01
2 -2.15778 3.270850e-01 4.797091e-01
1 -2.62182 3.226328e-01 4.866241e-01
2 -2.6203 3.226328e-01 4.857376e-01
1 -2.38124 3.226328e-01 4.958678e-01
2 -2.17075 3.246381e-01 4.927532e-01
1 -2.11906 3.039421e-01 5.248973e-01
1 -1.91963 3.039421e-01 5.301214e-01
2 -2.31386 3.193257e-01 5.062283e-01
3 0.302668 3.362837e-01 4.798901e-01
1 -0.284321 3.362837e-01 4.726818e-01
1 -2.61946 3.208351e-01 4.966758e-01
1 -2.60426 3.208351e-01 4.823970e-01
2 -2.53214 3.220693e-01 4.804800e-01
1 -2.38834 3.087288e-01 5.011998e-01
1 -2.64368 3.087288e-01 5.155450e-01
1 -2.71881 3.099098e-01 5.137108e-01
3 -1.91599 3.099098e-01 4.916461e-01
1 -1.38704 3.053106e-01 4.987892e-01
1 -2.16737 3.053106e-01 5.096817e-01
1 -2.77737 3.125212e-01 4.984826e-01
1 -2.27021 3.125212e-01 5.198635e-01
1 -2.0258 3.197187e-01 5.086847e-01
1 -2.50959 3.197187e-01 4.811500e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1741 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000370 for Omega_m
0.000204 for b1
--> Not computing covariance matrix
3 -2.40689 3.218869e-01 4.777824e-01
4 -2.29076 3.218869e-01 4.997437e-01
1 -1.92921 3.218869e-01 5.043387e-01
1 -2.29609 3.103124e-01 5.223156e-01
3 -0.192781 3.103124e-01 4.772624e-01
1 -0.580259 3.173859e-01 4.662762e-01
1 -0.480528 3.173859e-01 4.656336e-01
1 -0.383648 3.230451e-01 4.568441e-01
1 -0.0461897 3.230451e-01 4.546758e-01
1 -0.141407 3.189377e-01 4.610552e-01
1 -2.08756 3.189377e-01 4.762906e-01
1 -2.09965 3.164375e-01 4.801737e-01
3 -2.61207 3.164375e-01 4.870364e-01
1 -2.37131 3.230385e-01 4.767840e-01
2 -2.30276 3.230385e-01 4.959627e-01
1 -2.47017 3.230385e-01 4.923350e-01
1 -2.44092 3.062382e-01 5.184285e-01
2 -1.53795 3.062382e-01 4.975776e-01
1 -2.45278 3.062382e-01 5.167850e-01
2 -2.90295 3.154398e-01 5.024936e-01
1 -2.90252 3.141909e-01 5.044332e-01
1 -2.8997 3.141909e-01 4.990014e-01
1 -2.8353 3.119552e-01 5.024737e-01
2 -2.82845 3.119552e-01 5.021160e-01
1 -2.74518 3.119552e-01 5.125678e-01
2 -2.758 3.124737e-01 5.117625e-01
1 -2.28763 3.053557e-01 5.228179e-01
1 -1.28568 3.053557e-01 5.376639e-01
1 -1.51021 3.086910e-01 5.324836e-01
1 -1.84354 3.086910e-01 5.293180e-01
1 0.126172 2.949506e-01 5.506588e-01
3 -0.314444 2.949506e-01 5.421506e-01
2 -1.82552 3.025723e-01 5.303129e-01
2 -2.42775 3.082013e-01 5.215703e-01
1 -1.50843 3.005707e-01 5.334217e-01
1 -1.2986 3.005707e-01 5.377359e-01
1 -1.7227 3.235664e-01 5.020203e-01
1 -2.41318 3.235664e-01 4.916685e-01
1 -2.36814 3.240059e-01 4.909859e-01
1 -2.47401 3.240059e-01 4.871783e-01
1 -2.35174 3.054058e-01 5.160670e-01
2 -1.97526 3.054058e-01 5.296954e-01
3 -1.45004 3.054058e-01 5.360584e-01
1 -1.34135 3.043003e-01 5.377754e-01
1 -1.74075 3.043003e-01 5.331062e-01
4 -1.71556 3.040803e-01 5.334479e-01
1 -2.21525 3.148843e-01 5.166677e-01
1 -2.92611 3.148843e-01 5.003854e-01
1 -2.92364 3.159286e-01 4.987634e-01
1 -2.91089 3.159286e-01 4.964835e-01
1 -2.62861 3.086099e-01 5.078506e-01
1 -2.31081 3.086099e-01 5.002490e-01
2 -2.51867 3.215274e-01 4.801862e-01
1 -2.66329 3.153595e-01 4.897658e-01
1 -2.60787 3.153595e-01 5.105076e-01
1 -2.61865 3.145151e-01 5.118191e-01
1 -2.92184 3.145151e-01 5.003104e-01
1 -2.82953 3.112728e-01 5.053462e-01
2 -2.72542 3.112728e-01 5.135669e-01
1 -2.72679 3.112728e-01 5.006633e-01
1 -2.52647 3.234161e-01 4.818030e-01
1 -1.77689 3.234161e-01 5.018639e-01
1 -1.31157 3.269375e-01 4.963946e-01
1 -0.913603 3.269375e-01 5.000271e-01
2 -1.04227 3.260895e-01 5.013443e-01
2 -1.62289 3.213541e-01 5.086991e-01
1 -1.76992 3.196862e-01 5.112895e-01
1 -1.27905 3.196862e-01 5.153732e-01
2 -1.41371 3.069343e-01 5.351789e-01
1 -0.663586 3.002912e-01 5.454965e-01
2 -1.57013 3.002912e-01 5.292827e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1779 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000648 for Omega_m
0.000397 for b1
--> Not computing covariance matrix
2 -1.46253 3.002912e-01 5.337784e-01
1 -1.24029 3.002912e-01 5.383583e-01
2 -0.59137 2.969363e-01 5.435689e-01
1 -0.342898 2.958353e-01 5.452790e-01
5 -0.370036 2.958353e-01 5.447670e-01
1 -2.35087 3.142083e-01 5.162309e-01
1 -1.92911 3.142083e-01 5.207942e-01
1 -1.65133 3.059463e-01 5.336264e-01
3 -1.17278 3.059463e-01 5.381796e-01
4 -1.41406 3.116936e-01 5.292530e-01
1 -1.34623 3.155465e-01 5.232690e-01
2 -1.67994 3.155465e-01 5.206217e-01
1 -2.86899 3.155465e-01 4.947470e-01
1 -2.86683 3.163982e-01 4.934243e-01
2 -1.93095 3.163982e-01 4.784967e-01
1 -2.37146 3.163982e-01 4.834716e-01
1 -1.60469 3.287604e-01 4.642713e-01
1 -1.90422 3.287604e-01 4.718355e-01
1 -2.67107 3.114308e-01 4.987509e-01
1 -2.82223 3.114308e-01 5.039142e-01
2 -2.5715 3.232331e-01 4.855834e-01
1 -2.87567 3.127790e-01 5.018202e-01
1 -2.63692 3.127790e-01 5.140952e-01
3 -2.59898 3.166967e-01 5.080104e-01
1 -2.27617 3.166967e-01 5.125195e-01
2 -1.76477 3.037304e-01 5.326581e-01
2 -2.17329 3.187083e-01 5.093952e-01
1 -2.30494 3.108349e-01 5.216237e-01
1 -2.79696 3.108349e-01 5.106250e-01
4 -2.87944 3.135420e-01 5.064205e-01
1 -2.7865 3.106189e-01 5.109606e-01
1 -2.79105 3.106189e-01 5.059810e-01
1 -2.70586 3.214996e-01 4.890815e-01
3 -2.57924 3.214996e-01 4.816763e-01
4 -2.73307 3.152552e-01 4.913749e-01
1 -2.73388 3.170726e-01 4.885521e-01
1 -1.67504 3.170726e-01 4.749982e-01
2 -0.609677 3.043458e-01 4.947648e-01
1 -0.409783 3.031816e-01 4.965731e-01
1 -1.52014 3.031816e-01 5.074147e-01
1 -1.87043 3.055039e-01 5.038078e-01
1 -1.40634 3.055039e-01 5.364215e-01
4 -1.31803 3.045745e-01 5.378650e-01
1 -1.70625 3.115005e-01 5.271079e-01
4 -2.40633 3.115005e-01 5.194427e-01
1 -2.79483 3.115005e-01 5.111420e-01
2 -2.77732 3.180604e-01 5.009535e-01
2 -2.63174 3.085366e-01 5.157455e-01
1 -2.52631 3.072494e-01 5.177447e-01
2 -2.46263 3.072494e-01 5.203109e-01
1 -2.31367 3.072494e-01 5.048624e-01
1 -2.37873 3.078755e-01 5.038899e-01
1 -2.26153 3.078755e-01 5.017637e-01
2 -2.66393 3.183772e-01 4.854530e-01
1 -2.5955 3.203606e-01 4.823726e-01
1 -2.73757 3.203606e-01 4.944861e-01
1 -2.88744 3.168610e-01 4.999214e-01
1 -2.67466 3.168610e-01 4.875701e-01
1 -2.66236 3.148111e-01 4.907540e-01
1 -2.88214 3.148111e-01 5.047123e-01
2 -2.13596 3.261947e-01 4.870319e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1809 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000613 for Omega_m
0.000461 for b1
--> Not computing covariance matrix
2 -1.77054 3.288066e-01 4.829752e-01
1 -0.939763 3.335318e-01 4.756363e-01
4 -0.767697 3.335318e-01 4.547642e-01
1 -0.744786 3.335318e-01 4.544144e-01
2 -1.56894 3.276915e-01 4.634852e-01
1 -1.65246 3.269235e-01 4.646781e-01
4 -0.084942 3.269235e-01 4.505813e-01
1 -0.91969 3.269235e-01 4.569584e-01
1 -0.114094 3.332910e-01 4.470687e-01
1 0.0547491 3.332910e-01 4.883856e-01
2 -1.86894 3.207165e-01 5.079157e-01
1 -2.11217 3.171058e-01 5.135236e-01
1 -2.47567 3.171058e-01 5.090694e-01
1 -1.90816 3.242261e-01 4.980105e-01
3 -2.33673 3.242261e-01 4.763159e-01
1 -2.65177 3.187568e-01 4.848106e-01
1 -2.65911 3.187568e-01 4.849697e-01
3 -2.64946 3.190822e-01 4.844642e-01
1 -2.53053 3.190822e-01 5.036122e-01
1 -2.4965 3.084997e-01 5.200484e-01
3 -2.64489 3.084997e-01 5.094198e-01
1 -2.92414 3.151649e-01 4.990677e-01
1 -2.91052 3.151649e-01 4.975937e-01
1 -2.66148 3.090358e-01 5.071131e-01
1 -2.69032 3.090358e-01 5.135643e-01
1 -2.20642 3.256618e-01 4.877417e-01
1 -1.26829 3.256618e-01 5.005688e-01
1 -0.0512475 3.326014e-01 4.897906e-01
1 -0.960654 3.326014e-01 4.568236e-01
1 -2.24067 3.187116e-01 4.783966e-01
1 -2.20432 3.187116e-01 4.779512e-01
1 -2.21418 3.180161e-01 4.790313e-01
2 -1.40736 3.180161e-01 4.712393e-01
1 -2.45163 3.180161e-01 4.821761e-01
2 -2.44274 3.185325e-01 4.813741e-01
1 -2.42783 3.191633e-01 4.803944e-01
1 -2.83438 3.191633e-01 4.940462e-01
1 -2.89911 3.130125e-01 5.035994e-01
1 -2.74648 3.130125e-01 5.114687e-01
2 -2.67838 3.106402e-01 5.151532e-01
1 -2.28124 3.054360e-01 5.232361e-01
1 -1.88974 3.054360e-01 5.043141e-01
1 -2.38949 3.101839e-01 4.969400e-01
5 -2.02042 3.101839e-01 4.921134e-01
4 -0.821535 3.336089e-01 4.557309e-01
2 -1.78177 3.266666e-01 4.665133e-01
1 -2.26255 3.193859e-01 4.778213e-01
1 -2.0692 3.193859e-01 4.754960e-01
2 -1.88207 3.234523e-01 4.691803e-01
1 -2.09014 3.163972e-01 4.801379e-01
3 -2.91799 3.163972e-01 4.973623e-01
3 -2.92509 3.151464e-01 4.993049e-01
1 -2.50399 3.151464e-01 5.125257e-01
1 -1.4714 3.272256e-01 4.937649e-01
1 -1.83808 3.272256e-01 4.887204e-01
1 -2.72113 3.110942e-01 5.137750e-01
1 -2.71339 3.110942e-01 5.008416e-01
2 -2.63161 3.220199e-01 4.838723e-01
1 -2.8075 3.184861e-01 4.893608e-01
1 -2.84136 3.184861e-01 4.910001e-01
5 -2.87626 3.142733e-01 4.975432e-01
4 -2.91575 3.142733e-01 5.031781e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1839 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000259 for Omega_m
0.000172 for b1
--> Not computing covariance matrix
3 -2.23031 3.142733e-01 4.855152e-01
1 -2.27023 3.161719e-01 4.825665e-01
1 -2.92051 3.161719e-01 4.987672e-01
2 -2.88903 3.126446e-01 5.042456e-01
1 -2.92638 3.150078e-01 5.005752e-01
2 -2.21046 3.150078e-01 4.839015e-01
1 -1.37328 3.150078e-01 4.760361e-01
1 -1.38421 3.205743e-01 4.673905e-01
2 -2.35272 3.205743e-01 4.778072e-01
1 -1.67058 3.205743e-01 4.699210e-01
3 -1.03655 3.069458e-01 4.910881e-01
1 -1.77369 3.069458e-01 4.980549e-01
1 -1.03024 3.020878e-01 5.056002e-01
2 -1.59647 3.020878e-01 5.131399e-01
7 -1.23725 3.020878e-01 5.394019e-01
1 -1.0258 3.006643e-01 5.416128e-01
1 -1.34774 3.006643e-01 5.370199e-01
1 -2.17677 3.077281e-01 5.260489e-01
1 -2.56716 3.077281e-01 5.100492e-01
3 -2.85552 3.187338e-01 4.929556e-01
1 -2.85032 3.187338e-01 4.920537e-01
1 -2.69351 3.216656e-01 4.875002e-01
1 -2.37883 3.216656e-01 4.773962e-01
1 -2.48399 3.141745e-01 4.890310e-01
2 -1.28971 3.141745e-01 4.769301e-01
4 -1.72553 3.141745e-01 4.805561e-01
2 -2.25703 3.141745e-01 4.860246e-01
2 -1.84813 3.141745e-01 4.816891e-01
1 -1.03132 3.141745e-01 4.750028e-01
1 -1.10754 3.165050e-01 4.713833e-01
1 -0.983116 3.165050e-01 4.704840e-01
1 -0.50313 3.090451e-01 4.820703e-01
3 -0.979393 3.090451e-01 4.854498e-01
4 -1.39872 3.151990e-01 4.758919e-01
1 -1.42257 3.197648e-01 4.688006e-01
1 -2.61005 3.197648e-01 4.830652e-01
2 -2.41271 3.096830e-01 4.987238e-01
2 -2.60106 3.127647e-01 4.939374e-01
1 -2.67639 3.163014e-01 4.884444e-01
1 -2.90498 3.163014e-01 5.003251e-01
1 -2.44921 3.062007e-01 5.160129e-01
1 -2.26965 3.062007e-01 5.080913e-01
4 -2.40245 3.073899e-01 5.062443e-01
1 -2.83646 3.155562e-01 4.935608e-01
1 -2.61974 3.155562e-01 5.099371e-01
2 -2.55219 3.176718e-01 5.066513e-01
1 -2.6333 3.132117e-01 5.135785e-01
1 -2.89546 3.132117e-01 5.053987e-01
7 -2.67148 3.213936e-01 4.926911e-01
2 -2.71148 3.213936e-01 4.878077e-01
3 -2.67961 3.213936e-01 4.851850e-01
1 -2.45922 3.242204e-01 4.807946e-01
2 -2.47022 3.242204e-01 4.855957e-01
2 -1.21715 3.242204e-01 5.049486e-01
1 -2.47882 3.242204e-01 4.827542e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1866 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000405 for Omega_m
0.000307 for b1
--> Not computing covariance matrix
2 -2.89044 3.143232e-01 4.981259e-01
3 -2.89422 3.165487e-01 4.946694e-01
1 -2.8825 3.165487e-01 4.939893e-01
3 -2.88312 3.148356e-01 4.966500e-01
1 -2.78943 3.148356e-01 5.077395e-01
2 -2.49392 3.073402e-01 5.193809e-01
1 -2.46175 3.218722e-01 4.968107e-01
1 -1.94393 3.218722e-01 5.042161e-01
1 -2.11517 3.198875e-01 5.072986e-01
3 -2.76549 3.198875e-01 4.952386e-01
1 -2.42284 3.059582e-01 5.168729e-01
1 -2.32111 3.059582e-01 5.105780e-01
1 -2.13546 3.045211e-01 5.128100e-01
1 -2.16549 3.045211e-01 5.137409e-01
4 -2.56726 3.080332e-01 5.082862e-01
1 -1.82196 3.022691e-01 5.172386e-01
2 -1.83635 3.022691e-01 5.176933e-01
2 -1.56576 3.022691e-01 5.350112e-01
1 -1.92185 3.022691e-01 5.244772e-01
1 -2.46429 3.064516e-01 5.179811e-01
1 -2.47122 3.064516e-01 5.145054e-01
2 -1.69531 3.010245e-01 5.229346e-01
2 -2.6659 3.085358e-01 5.112684e-01
2 -2.43658 3.243648e-01 4.866836e-01
2 -2.85594 3.185192e-01 4.957627e-01
2 -2.91206 3.136322e-01 5.033528e-01
4 -2.61139 3.078883e-01 5.122741e-01
2 -2.92401 3.153607e-01 5.006683e-01
1 -2.80923 3.195488e-01 4.941636e-01
3 -2.7369 3.195488e-01 4.976457e-01
1 -2.57526 3.218892e-01 4.940107e-01
1 -2.4906 3.218892e-01 4.961444e-01
1 -2.57941 3.081813e-01 5.174348e-01
5 -2.6268 3.081813e-01 5.105988e-01
1 -2.48381 3.066894e-01 5.129159e-01
1 -2.49951 3.066894e-01 5.161372e-01
1 -2.87991 3.168764e-01 5.003155e-01
2 -2.84471 3.168764e-01 5.018747e-01
1 -2.55809 3.168764e-01 5.083040e-01
2 -2.60288 3.125815e-01 5.149746e-01
1 -2.19247 3.056026e-01 5.258138e-01
1 -1.85492 3.056026e-01 5.032598e-01
1 -2.49022 3.127087e-01 4.922229e-01
2 -2.84491 3.127087e-01 5.086521e-01
1 -1.69585 3.127087e-01 4.832012e-01
2 -1.72849 3.133245e-01 4.822448e-01
2 -1.59731 3.112103e-01 4.855284e-01
1 -1.70428 3.128598e-01 4.829666e-01
2 -2.09674 3.128598e-01 4.868531e-01
3 -2.61123 3.128598e-01 4.939022e-01
2 -2.67422 3.175076e-01 4.866836e-01
3 -2.57646 3.120979e-01 4.950856e-01
1 -2.85543 3.120979e-01 5.080643e-01
2 -1.58735 3.003190e-01 5.263587e-01
2 -2.82624 3.113128e-01 5.092836e-01
1 -2.66889 3.086318e-01 5.134476e-01
1 -2.6033 3.086318e-01 5.170801e-01
1 -1.23344 2.986060e-01 5.326517e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1896 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000407 for Omega_m
0.000403 for b1
--> Not computing covariance matrix
3 0.0382881 2.986060e-01 5.078211e-01
1 -1.95716 3.123218e-01 4.865183e-01
1 -2.87728 3.123218e-01 5.060786e-01
1 -2.88514 3.174380e-01 4.981325e-01
1 -2.83928 3.174380e-01 5.005879e-01
2 -2.79833 3.185158e-01 4.989139e-01
1 -2.88223 3.142953e-01 5.054690e-01
1 -2.4687 3.142953e-01 5.145174e-01
1 -2.20719 3.202939e-01 5.052006e-01
3 -1.81457 3.202939e-01 5.094599e-01
1 -0.971218 2.995692e-01 5.416485e-01
1 -0.670965 2.995692e-01 5.453085e-01
1 -1.11587 3.025355e-01 5.407014e-01
1 -1.82677 3.025355e-01 5.302026e-01
1 -2.00565 3.038463e-01 5.281668e-01
1 -1.98424 3.038463e-01 5.124667e-01
2 -2.66585 3.101307e-01 5.027061e-01
1 -2.58727 3.090818e-01 5.043353e-01
2 -2.58334 3.090818e-01 5.042267e-01
1 -2.70211 3.090818e-01 5.094980e-01
1 -2.88987 3.177115e-01 4.960948e-01
2 -1.88028 3.177115e-01 4.758969e-01
2 -1.75947 3.177115e-01 4.747508e-01
2 -2.89008 3.177115e-01 4.948201e-01
1 -2.88893 3.177115e-01 4.963172e-01
1 -2.86888 3.120500e-01 5.051103e-01
1 -2.79278 3.120500e-01 5.110444e-01
4 -2.16338 3.040816e-01 5.234205e-01
1 -2.77108 3.175284e-01 5.025355e-01
1 -2.32896 3.175284e-01 4.811659e-01
1 -2.3217 3.157024e-01 4.840020e-01
2 -2.92166 3.157024e-01 4.979164e-01
1 -2.84043 3.157024e-01 4.934497e-01
2 -2.7395 3.117418e-01 4.996011e-01
2 -2.51874 3.085456e-01 5.045651e-01
1 -2.62613 3.220286e-01 4.836241e-01
2 -2.65275 3.220286e-01 4.851645e-01
1 -2.66423 3.220286e-01 4.888791e-01
1 -2.41598 3.247625e-01 4.846330e-01
2 -2.36355 3.247625e-01 4.874490e-01
1 -2.21271 3.247625e-01 4.737249e-01
2 -2.0469 3.264403e-01 4.711190e-01
1 -2.2241 3.246353e-01 4.739225e-01
3 -2.25135 3.246353e-01 4.745093e-01
2 -1.39485 3.315183e-01 4.638190e-01
1 -1.84667 3.283580e-01 4.687273e-01
1 -1.88918 3.283580e-01 4.698814e-01
1 -2.32815 3.243167e-01 4.761582e-01
2 -2.17552 3.243167e-01 4.729572e-01
1 -2.42514 3.243167e-01 4.793085e-01
1 -2.75112 3.126366e-01 4.974494e-01
1 -2.63027 3.126366e-01 4.947800e-01
1 -1.73779 3.295880e-01 4.684520e-01
1 -0.858704 3.295880e-01 4.924651e-01
1 -2.06456 3.202731e-01 5.069326e-01
1 -2.21253 3.202731e-01 5.051863e-01
1 -2.40068 3.100714e-01 5.210310e-01
1 -2.71624 3.100714e-01 5.046315e-01
1 -2.23922 3.051863e-01 5.122188e-01
1 -2.26016 3.051863e-01 5.129252e-01
2 -2.80535 3.113318e-01 5.033804e-01
2 -2.90254 3.165542e-01 4.952692e-01
1 -2.76848 3.106517e-01 5.044367e-01
1 -2.79767 3.106517e-01 5.063535e-01
2 -2.70768 3.092559e-01 5.085214e-01
1 -0.845503 2.971162e-01 5.273761e-01
1 -0.91593 2.971162e-01 5.311275e-01
1 -2.78609 3.104234e-01 5.104595e-01
1 -2.73227 3.104234e-01 5.038203e-01
1 -2.02576 3.281306e-01 4.763183e-01
2 -1.79694 3.281306e-01 4.673318e-01
1 -1.48306 3.281306e-01 4.905416e-01
1 -2.52155 3.181473e-01 5.060471e-01
2 -1.99408 3.181473e-01 5.125512e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1934 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000396 for Omega_m
0.000333 for b1
--> Not computing covariance matrix
1 -2.87365 3.181473e-01 4.934030e-01
2 -2.72061 3.097172e-01 5.064963e-01
3 -2.21508 3.047192e-01 5.142588e-01
1 -2.10449 3.047192e-01 5.109869e-01
1 -2.20779 3.054962e-01 5.097801e-01
2 -1.52642 3.054962e-01 4.996731e-01
1 -2.01772 3.054962e-01 5.060536e-01
2 -2.33574 3.082687e-01 5.017476e-01
2 -2.658 3.194605e-01 4.843651e-01
3 -2.60627 3.206637e-01 4.824964e-01
1 -2.64727 3.206637e-01 4.965129e-01
1 -2.66394 3.088806e-01 5.148137e-01
1 -2.64538 3.088806e-01 5.071846e-01
2 -2.86983 3.181060e-01 4.928562e-01
2 -2.68231 3.093567e-01 5.064452e-01
4 -1.9518 3.286521e-01 4.764767e-01
2 -1.83666 3.294428e-01 4.752485e-01
2 -2.34343 3.255469e-01 4.812994e-01
2 -1.98608 3.284081e-01 4.768556e-01
1 -1.8392 3.294259e-01 4.752748e-01
1 -1.7902 3.294259e-01 4.785530e-01
1 -2.77532 3.202234e-01 4.928458e-01
1 -2.66128 3.202234e-01 4.840616e-01
5 -2.7556 3.161091e-01 4.904517e-01
1 -2.50244 3.161091e-01 5.107255e-01
3 -1.87819 3.034172e-01 5.304380e-01
1 -1.05572 3.034172e-01 5.014007e-01
1 -2.17561 3.188854e-01 4.773762e-01
1 -2.73198 3.188854e-01 4.866567e-01
1 -2.27816 3.069874e-01 5.051361e-01
1 -2.17216 3.069874e-01 5.264095e-01
1 -2.41965 3.119876e-01 5.186435e-01
1 -2.80654 3.119876e-01 5.010434e-01
1 -2.88645 3.155939e-01 4.954422e-01
1 -2.20366 3.155939e-01 4.827718e-01
1 -1.89875 3.246965e-01 4.686341e-01
1 -2.26589 3.246965e-01 4.905773e-01
1 -2.10561 3.260327e-01 4.885021e-01
1 -0.72774 3.260327e-01 5.039939e-01
2 -0.289828 3.286956e-01 4.998580e-01
2 -0.943896 3.245227e-01 5.063390e-01
1 -1.60662 3.178546e-01 5.166957e-01
1 -2.46859 3.178546e-01 5.075295e-01
2 -2.5318 3.113058e-01 5.177007e-01
1 -2.54817 3.155703e-01 5.110774e-01
1 -2.80353 3.155703e-01 4.925541e-01
2 -2.77382 3.183222e-01 4.882800e-01
3 -2.70851 3.201111e-01 4.855015e-01
1 -2.31887 3.201111e-01 4.777660e-01
1 -2.24602 3.121474e-01 4.901347e-01
1 -2.70966 3.121474e-01 4.976950e-01
2 -2.78198 3.177121e-01 4.890523e-01
1 -2.78359 3.144375e-01 4.941381e-01
1 -2.85706 3.144375e-01 4.963922e-01
2 -2.86573 3.152379e-01 4.951491e-01
3 -2.84894 3.139915e-01 4.970850e-01
1 -2.90054 3.139915e-01 5.047572e-01
1 -2.85498 3.119522e-01 5.079246e-01
3 -2.62184 3.119522e-01 5.153721e-01
3 -2.64013 3.130081e-01 5.137321e-01
1 -1.85241 3.130081e-01 4.840417e-01
2 -1.82807 3.223766e-01 4.694909e-01
1 -1.16711 3.058446e-01 4.951677e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1964 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000792 for Omega_m
0.000537 for b1
--> Not computing covariance matrix
1 -1.97365 3.058446e-01 5.041100e-01
1 -1.65785 3.036570e-01 5.075076e-01
1 -2.02953 3.036570e-01 5.147007e-01
1 -1.69603 3.016151e-01 5.178722e-01
1 -1.44163 3.016151e-01 5.364731e-01
1 -1.89473 3.052013e-01 5.309032e-01
1 -1.89214 3.052013e-01 5.051797e-01
1 -2.43879 3.104283e-01 4.970614e-01
1 -1.29745 3.104283e-01 4.847432e-01
2 -0.20653 3.024886e-01 4.970747e-01
1 -0.668368 3.051825e-01 4.928907e-01
3 -2.21812 3.051825e-01 5.247080e-01
2 -2.26323 3.055962e-01 5.240655e-01
1 -2.19625 3.049890e-01 5.250085e-01
1 -2.18328 3.049890e-01 5.253696e-01
2 -2.46601 3.079941e-01 5.207022e-01
1 -2.14438 3.046538e-01 5.258902e-01
3 -2.10706 3.046538e-01 5.113675e-01
2 -1.94918 3.035709e-01 5.130495e-01
1 -2.80444 3.189469e-01 4.891683e-01
1 -2.64677 3.189469e-01 4.845251e-01
2 -2.68501 3.159309e-01 4.892093e-01
1 -0.135943 3.383034e-01 4.544616e-01
1 -0.0856453 3.383034e-01 4.524899e-01
1 -0.594427 3.358600e-01 4.562848e-01
2 -0.184224 3.358600e-01 4.487308e-01
1 -0.699061 3.358600e-01 4.635429e-01
1 -1.06988 3.339951e-01 4.664394e-01
3 -0.741714 3.339951e-01 4.549116e-01
1 -0.529581 3.351725e-01 4.530828e-01
1 -0.745691 3.351725e-01 4.696819e-01
1 -2.03409 3.277439e-01 4.812196e-01
1 -2.00239 3.277439e-01 4.719717e-01
2 -0.980052 3.342850e-01 4.618123e-01
4 -1.14732 3.333710e-01 4.632319e-01
3 -1.21414 3.329935e-01 4.638182e-01
3 -1.00225 3.329935e-01 4.580638e-01
1 -0.922702 3.334622e-01 4.573360e-01
1 0.268102 3.334622e-01 4.437064e-01
2 0.174482 3.328460e-01 4.446634e-01
1 -0.913876 3.162021e-01 4.705138e-01
1 -2.13997 3.162021e-01 5.150333e-01
4 -1.09141 3.270308e-01 4.982148e-01
1 -1.20088 3.263041e-01 4.993435e-01
2 -2.17459 3.263041e-01 4.853344e-01
1 -2.17634 3.263041e-01 4.743813e-01
1 -2.46862 3.231975e-01 4.792062e-01
1 -2.57466 3.231975e-01 4.855035e-01
4 -2.7546 3.207450e-01 4.893127e-01
2 -2.43175 3.247096e-01 4.831550e-01
1 -2.80225 3.198839e-01 4.906501e-01
3 -2.05451 3.198839e-01 4.747060e-01
2 -1.85499 3.108912e-01 4.886730e-01
1 -1.37935 3.063234e-01 4.957675e-01
1 -0.512268 3.063234e-01 4.887193e-01
1 -0.431767 3.057688e-01 4.895807e-01
1 -2.4003 3.057688e-01 5.164211e-01
1 -2.71451 3.091610e-01 5.111524e-01
1 -2.17792 3.091610e-01 4.967004e-01
2 -2.51127 3.170985e-01 4.843724e-01
3 -2.3161 3.225879e-01 4.758466e-01
3 -2.5169 3.225879e-01 4.928835e-01
1 -2.24843 3.251919e-01 4.888389e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 1996 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000919 for Omega_m
0.000597 for b1
--> Not computing covariance matrix
1 -1.60804 3.251919e-01 4.648492e-01
1 -1.68644 3.241972e-01 4.663942e-01
1 -1.6848 3.241972e-01 4.663762e-01
4 -1.74259 3.116765e-01 4.858227e-01
2 -1.83554 3.132706e-01 4.833468e-01
2 -1.39519 3.078767e-01 4.917244e-01
1 -1.45293 3.083923e-01 4.909235e-01
1 -1.77739 3.083923e-01 4.940673e-01
2 -2.21482 3.156895e-01 4.827337e-01
2 -1.99878 3.234977e-01 4.706064e-01
2 -1.86981 3.093262e-01 4.926169e-01
1 -2.15185 3.135195e-01 4.861040e-01
1 -1.22616 3.135195e-01 4.777012e-01
1 -1.10713 3.116409e-01 4.806190e-01
2 -1.00095 3.116409e-01 4.798350e-01
2 -0.252933 3.116409e-01 4.748381e-01
1 -0.561824 3.116409e-01 4.768038e-01
1 -0.741392 3.145544e-01 4.722787e-01
2 -0.4308 3.145544e-01 4.702611e-01
1 -0.967591 3.145544e-01 4.738374e-01
2 -1.02806 3.200373e-01 4.653216e-01
1 -1.01409 3.158942e-01 4.717565e-01
1 -2.92232 3.158942e-01 4.979481e-01
3 -2.53634 3.073021e-01 5.112929e-01
1 -2.56007 3.073021e-01 5.137663e-01
3 -2.86642 3.119903e-01 5.064849e-01
1 -2.52766 3.119903e-01 4.945035e-01
1 -1.34782 3.018695e-01 5.102226e-01
1 0.182228 3.018695e-01 4.960959e-01
2 0.659524 2.996519e-01 4.995401e-01
3 -1.28335 3.221591e-01 4.645831e-01
1 -1.68216 3.221591e-01 4.682015e-01
1 -1.75264 3.204429e-01 4.708670e-01
1 -2.00707 3.204429e-01 4.735072e-01
1 -2.05934 3.165843e-01 4.795003e-01
3 -2.38277 3.165843e-01 5.114248e-01
1 -1.69353 3.249039e-01 4.985031e-01
1 -1.816 3.249039e-01 4.970761e-01
2 -1.08758 2.986050e-01 5.379222e-01
2 -2.04968 3.048331e-01 5.282489e-01
1 -1.50232 3.271887e-01 4.935274e-01
2 -1.82738 3.271887e-01 4.673156e-01
1 -2.14912 3.271887e-01 4.780720e-01
1 -2.70886 3.213542e-01 4.871338e-01
1 -2.70454 3.213542e-01 4.867128e-01
1 -2.02029 3.281696e-01 4.761275e-01
1 -1.67853 3.281696e-01 4.652035e-01
3 -1.56781 3.290556e-01 4.638274e-01
2 -0.547289 3.290556e-01 4.523762e-01
1 -0.35773 3.290556e-01 4.508297e-01
1 -0.975035 3.191218e-01 4.662583e-01
1 -1.21731 3.191218e-01 4.680690e-01
2 -1.06529 3.234668e-01 4.613206e-01
1 -0.960251 3.113767e-01 4.800983e-01
1 -1.61235 3.113767e-01 4.852945e-01
1 -0.554374 3.029701e-01 4.983512e-01
1 -0.939627 3.029701e-01 5.017261e-01
1 -1.38042 3.057597e-01 4.973935e-01
7 -1.29059 3.057597e-01 4.965340e-01
2 -2.07075 3.158254e-01 4.809005e-01
2 -1.90938 3.118246e-01 4.871143e-01
1 -1.98075 3.130843e-01 4.851579e-01
1 -0.771381 3.130843e-01 4.752870e-01
1 -0.680786 3.250986e-01 4.566269e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 2029 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000871 for Omega_m
0.000606 for b1
--> Not computing covariance matrix
4 -0.633519 3.250986e-01 4.562738e-01
2 -1.36297 3.250986e-01 4.623884e-01
1 -0.218656 3.250986e-01 4.533538e-01
3 -0.211438 3.252025e-01 4.531924e-01
1 -1.508 3.252025e-01 4.637660e-01
1 -1.0367 3.296739e-01 4.568214e-01
1 -0.213374 3.296739e-01 4.975942e-01
3 -1.50297 3.203909e-01 5.120120e-01
2 -1.7563 3.203909e-01 5.097821e-01
2 -2.50856 3.203909e-01 4.805697e-01
1 -1.0951 3.203909e-01 4.653343e-01
1 -1.10061 3.162586e-01 4.717524e-01
1 -2.47204 3.162586e-01 5.108680e-01
1 -2.51009 3.143074e-01 5.138985e-01
1 -2.85588 3.143074e-01 4.966299e-01
2 -2.46349 3.242408e-01 4.812017e-01
1 -2.51951 3.081378e-01 5.062121e-01
1 -2.20549 3.081378e-01 5.000596e-01
1 -1.03823 3.004332e-01 5.120260e-01
1 -1.23458 3.004332e-01 5.148477e-01
1 -2.54997 3.102301e-01 4.996316e-01
3 -2.61333 3.102301e-01 5.010080e-01
1 -0.799016 2.980307e-01 5.199555e-01
1 0.968712 2.980307e-01 5.026255e-01
1 0.291524 3.009466e-01 4.980968e-01
2 0.644558 3.009466e-01 4.957020e-01
1 -1.33602 3.009466e-01 5.140606e-01
1 -2.68776 3.126862e-01 4.958273e-01
1 -2.88214 3.126862e-01 5.027716e-01
1 -2.69408 3.091479e-01 5.082671e-01
1 -2.22729 3.091479e-01 4.974133e-01
1 -2.10001 3.078470e-01 4.994338e-01
2 -1.90164 3.078470e-01 4.969326e-01
2 -1.7044 3.078470e-01 4.947696e-01
1 -2.30794 3.078470e-01 5.026516e-01
2 -2.61641 3.118723e-01 4.963998e-01
1 -2.67728 3.132824e-01 4.942096e-01
1 -1.52777 3.132824e-01 4.805779e-01
1 -1.61911 3.198013e-01 4.704530e-01
2 -0.538048 3.198013e-01 4.622469e-01
2 -2.09195 3.198013e-01 4.752342e-01
1 -2.78851 3.198013e-01 4.889224e-01
2 -2.13167 3.273144e-01 4.772535e-01
3 -1.55159 3.312831e-01 4.710895e-01
1 -1.29414 3.312831e-01 4.804868e-01
3 -2.14928 3.256326e-01 4.892629e-01
1 -2.09214 3.256326e-01 4.904408e-01
1 -1.47128 3.298800e-01 4.838439e-01
1 -1.39729 3.298800e-01 4.615507e-01
1 -1.52861 3.288792e-01 4.631052e-01
2 -1.83809 3.288792e-01 4.807021e-01
1 -1.23617 3.288792e-01 4.909025e-01
2 -1.67852 3.259533e-01 4.954467e-01
2 -2.47712 3.105560e-01 5.193610e-01
2 -2.53614 3.139562e-01 5.140801e-01
1 -2.50493 3.113983e-01 5.180529e-01
4 -2.66244 3.113983e-01 4.986436e-01
1 -2.60257 3.113983e-01 4.973720e-01
2 -2.6677 3.127247e-01 4.953119e-01
2 -2.56113 3.107228e-01 4.984211e-01
2 -2.73856 3.161699e-01 4.899609e-01
1 -2.0391 3.274484e-01 4.724438e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 2059 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000803 for Omega_m
0.000595 for b1
--> Not computing covariance matrix
5 -2.11509 3.274484e-01 4.783677e-01
4 -2.90149 3.166540e-01 4.951330e-01
3 -2.05628 3.278941e-01 4.776755e-01
1 -0.960934 3.278941e-01 4.968159e-01
1 -2.20008 3.136867e-01 5.188820e-01
1 -1.01754 3.136867e-01 5.289250e-01
1 -0.632132 3.037847e-01 5.443043e-01
1 -2.04719 3.037847e-01 5.269291e-01
1 -2.67628 3.119353e-01 5.142699e-01
1 -2.86202 3.119353e-01 5.047628e-01
1 -2.92642 3.151093e-01 4.998332e-01
1 -2.55942 3.151093e-01 4.884098e-01
1 -1.46318 3.030600e-01 5.071241e-01
1 -1.88839 3.030600e-01 5.142998e-01
1 -2.67928 3.100328e-01 5.034701e-01
2 -2.68418 3.100328e-01 5.150754e-01
3 -2.62731 3.100328e-01 5.019957e-01
1 -1.98601 3.041195e-01 5.111800e-01
2 -1.416 3.041195e-01 5.028497e-01
1 -2.18759 3.041195e-01 5.182608e-01
1 2.80393 2.856399e-01 5.469623e-01
1 2.70288 2.856399e-01 5.513381e-01
1 -0.888347 2.969690e-01 5.337424e-01
2 2.58039 2.969690e-01 5.686656e-01
2 -0.613203 2.969690e-01 5.432522e-01
2 -0.785931 2.969690e-01 5.393221e-01
1 -0.79709 2.969690e-01 5.389775e-01
1 -0.779059 2.968887e-01 5.391023e-01
4 -0.776959 2.968887e-01 5.391689e-01
1 -0.867999 2.968887e-01 5.342583e-01
1 -1.2422 2.985937e-01 5.316102e-01
3 -0.755312 2.985937e-01 5.164130e-01
1 -1.34168 3.014188e-01 5.120251e-01
1 -0.537034 3.014188e-01 5.031153e-01
4 -0.277336 3.001672e-01 5.050593e-01
6 -1.99285 3.136950e-01 4.840486e-01
1 -2.06648 3.178212e-01 4.776400e-01
1 1.03411 3.178212e-01 4.563814e-01
1 2.20835 3.346565e-01 4.302337e-01
1 0.95482 3.346565e-01 4.380661e-01
1 -0.316929 3.219102e-01 4.578630e-01
2 -2.03869 3.219102e-01 4.723449e-01
1 -2.45163 3.219102e-01 4.786432e-01
1 -2.60679 3.178820e-01 4.848996e-01
1 -2.85956 3.178820e-01 4.919782e-01
2 -2.82066 3.190817e-01 4.901149e-01
1 -2.25095 3.263365e-01 4.788472e-01
1 -2.20449 3.263365e-01 4.755408e-01
2 -2.41287 3.242849e-01 4.787272e-01
1 -2.40617 3.243583e-01 4.786133e-01
1 -2.23988 3.243583e-01 4.924751e-01
1 -2.64618 3.091986e-01 5.160202e-01
3 -2.47371 3.091986e-01 5.013052e-01
2 -2.69295 3.127446e-01 4.957978e-01
3 -0.867091 2.986796e-01 5.176429e-01
3 -1.25068 2.986796e-01 5.275861e-01
1 -2.79464 3.104434e-01 5.093151e-01
1 -2.20897 3.104434e-01 5.233022e-01
1 -2.24143 3.147284e-01 5.166469e-01
2 -1.45688 3.147284e-01 5.239163e-01
1 -0.414863 3.147284e-01 5.309067e-01
1 -0.0308021 3.200308e-01 5.226712e-01
1 -0.700253 3.200308e-01 5.186559e-01
1 -0.890112 3.060891e-01 5.403095e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 2091 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000645 for Omega_m
0.000527 for b1
--> Not computing covariance matrix
2 -2.35197 3.060891e-01 5.221662e-01
2 -1.55421 3.060891e-01 4.981842e-01
3 -1.48502 3.060891e-01 4.974723e-01
1 -1.71889 3.080017e-01 4.945017e-01
2 -0.927686 3.080017e-01 4.875646e-01
1 -0.908165 3.080017e-01 4.874164e-01
1 1.4346 2.961287e-01 5.058569e-01
2 0.852836 2.961287e-01 5.101617e-01
1 -0.681671 2.961287e-01 5.363239e-01
1 -1.5163 3.000403e-01 5.302487e-01
2 -1.53207 3.000403e-01 5.287628e-01
2 -1.52088 3.000403e-01 5.299144e-01
1 -1.49659 3.000403e-01 5.236422e-01
1 -2.70482 3.091070e-01 5.095602e-01
1 -2.62603 3.091070e-01 5.054117e-01
5 -2.87135 3.141901e-01 4.975170e-01
3 -2.0151 3.141901e-01 4.833098e-01
1 -2.06906 3.167435e-01 4.793439e-01
1 -2.78693 3.167435e-01 4.903226e-01
1 -2.78804 3.155237e-01 4.922172e-01
1 -1.95374 3.155237e-01 4.802270e-01
2 -1.97098 3.166675e-01 4.784505e-01
1 -1.86966 3.217327e-01 4.705834e-01
1 -2.48828 3.217327e-01 4.794636e-01
1 -1.39472 3.020913e-01 5.099697e-01
3 -1.61447 3.020913e-01 5.340238e-01
1 -2.43264 3.134833e-01 5.163304e-01
2 -1.86609 3.134833e-01 5.226029e-01
1 -2.76205 3.134833e-01 4.956613e-01
1 -2.77185 3.182285e-01 4.882912e-01
1 -2.69138 3.182285e-01 4.862124e-01
2 -1.94272 3.280911e-01 4.708944e-01
1 -1.29077 3.324771e-01 4.640823e-01
1 0.400189 3.324771e-01 4.936221e-01
1 -0.843584 3.255746e-01 5.043427e-01
1 -1.57876 3.255746e-01 4.977532e-01
1 -2.11445 3.206739e-01 5.053647e-01
3 -2.04365 3.206739e-01 5.061761e-01
2 -2.24148 3.177652e-01 5.106937e-01
1 -2.18049 3.188235e-01 5.090501e-01
2 -1.77599 3.188235e-01 5.131624e-01
1 -2.61462 3.188235e-01 5.027500e-01
4 -2.59919 3.093197e-01 5.175108e-01
1 -1.3429 3.299919e-01 4.854038e-01
1 -1.75673 3.299919e-01 4.727339e-01
2 -2.59894 3.088650e-01 5.055471e-01
1 -2.66019 3.096490e-01 5.043294e-01
4 -2.73347 3.096490e-01 5.123836e-01
2 -2.66257 3.096490e-01 5.156907e-01
2 -1.22142 3.096490e-01 5.336436e-01
2 0.570084 3.096490e-01 5.446383e-01
3 -1.37796 3.096490e-01 4.872035e-01
1 -1.7508 3.171903e-01 4.754908e-01
2 -2.67028 3.171903e-01 4.870221e-01
1 -2.88445 3.171903e-01 4.990762e-01
3 -2.91385 3.152038e-01 5.021616e-01
1 -2.79122 3.152038e-01 5.070422e-01
1 -2.79371 3.137401e-01 5.093155e-01
1 -2.88884 3.137401e-01 4.995347e-01
2 -2.02034 3.281628e-01 4.771341e-01
1 -2.32301 3.257308e-01 4.809113e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 2121 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000764 for Omega_m
0.000490 for b1
--> Not computing covariance matrix
1 -2.29947 3.257308e-01 4.779369e-01
1 -2.67157 3.213532e-01 4.847360e-01
1 -2.67077 3.213532e-01 4.929206e-01
1 -2.27936 3.254645e-01 4.865352e-01
1 -2.3525 3.254645e-01 4.813311e-01
3 -2.58918 3.082438e-01 5.080774e-01
1 -1.60671 3.082438e-01 5.321084e-01
1 -1.61086 3.083226e-01 5.319860e-01
1 -1.73897 3.083226e-01 5.307556e-01
2 -1.63693 3.067373e-01 5.332178e-01
2 -1.78027 3.091703e-01 5.294390e-01
1 -1.46707 3.207821e-01 5.114042e-01
1 -2.45094 3.207821e-01 4.792357e-01
1 -2.15771 3.084892e-01 4.983283e-01
1 -2.29819 3.084892e-01 5.004169e-01
2 -2.51349 3.112459e-01 4.961354e-01
5 -2.667 3.159174e-01 4.888798e-01
2 -2.90667 3.159174e-01 4.961626e-01
1 -2.49353 3.159174e-01 5.112305e-01
1 -1.77972 3.027644e-01 5.316591e-01
1 -1.82881 3.027644e-01 5.305960e-01
1 -2.57681 3.122910e-01 5.157997e-01
1 -2.17342 3.122910e-01 4.889436e-01
2 -1.47479 3.052500e-01 4.998794e-01
1 -2.28395 3.151964e-01 4.844312e-01
1 -2.92038 3.151964e-01 4.984553e-01
1 -2.91698 3.161627e-01 4.969545e-01
1 -2.64212 3.161627e-01 5.083587e-01
1 -2.4147 3.075172e-01 5.217864e-01
1 -2.55371 3.075172e-01 5.171190e-01
2 -2.84893 3.156412e-01 5.045012e-01
1 -2.62879 3.084431e-01 5.156808e-01
3 -2.64797 3.084431e-01 5.101053e-01
2 -1.55543 3.310270e-01 4.750291e-01
2 -2.00916 3.280748e-01 4.796144e-01
2 -2.38029 3.250826e-01 4.842616e-01
4 -2.36982 3.251785e-01 4.841127e-01
1 -2.8543 3.187690e-01 4.940677e-01
1 -2.42179 3.187690e-01 4.807697e-01
1 -2.34519 3.126706e-01 4.902414e-01
1 -2.26756 3.126706e-01 4.892466e-01
1 -1.91633 3.081390e-01 4.962849e-01
3 -2.55824 3.081390e-01 5.074248e-01
2 -2.71818 3.101805e-01 5.042540e-01
2 -2.80971 3.118360e-01 5.016829e-01
2 -2.89408 3.154172e-01 4.961207e-01
3 -2.82199 3.121191e-01 5.012432e-01
1 -2.33515 3.121191e-01 5.196156e-01
1 -2.02114 3.207773e-01 5.061682e-01
1 -1.66425 3.207773e-01 5.097122e-01
1 -1.49109 3.224988e-01 5.070384e-01
3 -1.90001 3.224988e-01 5.030340e-01
1 -0.503381 3.317356e-01 4.886879e-01
1 -1.08983 3.317356e-01 4.818215e-01
2 0.268422 3.380385e-01 4.720322e-01
1 -1.43642 3.297777e-01 4.848625e-01
1 -1.55625 3.297777e-01 4.827572e-01
1 -1.85693 3.278359e-01 4.857731e-01
3 -2.03833 3.278359e-01 4.739140e-01
2 -2.77632 3.132694e-01 4.965379e-01
2 -1.39288 3.321551e-01 4.672056e-01
1 -1.05855 3.340230e-01 4.643045e-01
1 -1.06474 3.340230e-01 4.654211e-01
2 -2.67825 3.213686e-01 4.850752e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 2154 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000851 for Omega_m
0.000504 for b1
--> Not computing covariance matrix
3 -2.85002 3.151304e-01 4.947642e-01
1 -2.70748 3.151304e-01 5.090882e-01
1 -2.65375 3.109289e-01 5.156136e-01
1 -2.80195 3.109289e-01 5.104366e-01
1 -2.81572 3.112420e-01 5.099504e-01
4 -2.8043 3.112420e-01 5.106293e-01
1 -2.75578 3.112420e-01 5.126395e-01
2 -2.75009 3.177428e-01 5.025428e-01
1 -2.79191 3.124063e-01 5.108311e-01
4 -2.77807 3.124063e-01 5.112572e-01
2 -2.66585 3.124063e-01 4.960507e-01
1 -2.83858 3.124063e-01 5.010283e-01
2 -2.66095 3.092897e-01 5.058688e-01
1 -2.86391 3.131681e-01 4.998451e-01
1 -2.73484 3.131681e-01 4.957330e-01
1 -2.3431 3.249534e-01 4.774286e-01
1 -2.34024 3.249534e-01 4.872366e-01
1 -2.53041 3.230810e-01 4.901447e-01
1 -2.55986 3.230810e-01 4.826584e-01
1 -2.738 3.204102e-01 4.868066e-01
1 -2.7606 3.204102e-01 4.881890e-01
1 -2.8049 3.118236e-01 5.015253e-01
1 -2.81148 3.118236e-01 5.104113e-01
1 -2.85259 3.137656e-01 5.073952e-01
1 -2.01452 3.137656e-01 5.207119e-01
1 -1.73035 3.198709e-01 5.112294e-01
1 -2.47309 3.198709e-01 5.025136e-01
3 -0.942481 3.316499e-01 4.842192e-01
2 -1.31987 3.316499e-01 4.622350e-01
1 -0.337998 3.316499e-01 4.494250e-01
2 0.658508 3.375580e-01 4.402487e-01
1 -1.3234 3.188875e-01 4.692468e-01
1 -2.80582 3.188875e-01 4.973413e-01
2 -2.52825 3.229090e-01 4.910954e-01
1 -2.33536 3.248195e-01 4.881279e-01
2 -2.39485 3.248195e-01 4.856280e-01
1 -2.31724 3.248195e-01 4.886899e-01
1 -2.85512 3.172610e-01 5.004295e-01
1 -2.49936 3.172610e-01 4.839506e-01
1 -2.47225 3.144592e-01 4.883022e-01
1 -2.616 3.144592e-01 4.905871e-01
2 -2.55432 3.202878e-01 4.815345e-01
1 -2.61928 3.146069e-01 4.903577e-01
1 -2.68848 3.146069e-01 4.916538e-01
3 -2.61886 3.201724e-01 4.830098e-01
1 -2.6626 3.201724e-01 4.841132e-01
2 -1.97326 3.048032e-01 5.079840e-01
2 -2.5899 3.108822e-01 4.985424e-01
1 -2.64057 3.206324e-01 4.833989e-01
2 -2.51777 3.206324e-01 4.805798e-01
1 -2.38136 3.206324e-01 5.019135e-01
1 -2.60499 3.113779e-01 5.162870e-01
1 -2.54029 3.113779e-01 5.174785e-01
5 -2.36259 3.197874e-01 5.044172e-01
1 -2.37917 3.197874e-01 4.789789e-01
2 1.01214 3.426290e-01 4.435026e-01
1 -0.0968636 3.378590e-01 4.509111e-01
2 0.688843 3.378590e-01 4.774743e-01
2 0.166809 3.378590e-01 4.715135e-01
1 0.628599 3.378590e-01 4.768900e-01
4 -1.18285 3.292318e-01 4.902893e-01
2 -2.19014 3.214646e-01 5.023529e-01
1 -2.09654 3.224583e-01 5.008096e-01
3 -2.34963 3.224583e-01 4.764940e-01
1 -2.10002 3.255382e-01 4.717104e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 2186 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.001115 for Omega_m
0.000686 for b1
--> Not computing covariance matrix
1 -2.18565 3.255382e-01 4.735648e-01
1 -2.50024 3.215371e-01 4.797791e-01
1 -2.60315 3.215371e-01 4.823679e-01
1 -2.74559 3.181687e-01 4.875996e-01
2 -2.57926 3.181687e-01 5.050356e-01
2 -2.87452 3.181687e-01 4.936302e-01
3 -2.87043 3.181687e-01 4.961598e-01
1 -2.62956 3.081064e-01 5.117880e-01
2 -2.60499 3.081064e-01 5.096464e-01
1 -2.53571 3.081064e-01 5.188664e-01
1 -2.51285 3.078114e-01 5.193247e-01
3 -2.58468 3.078114e-01 5.104923e-01
1 -2.34274 3.055420e-01 5.140170e-01
3 -2.12776 3.055420e-01 5.078469e-01
1 -2.77769 3.143476e-01 4.941705e-01
1 -1.82617 3.143476e-01 4.811517e-01
5 -1.86952 3.159376e-01 4.786822e-01
2 -2.83439 3.159376e-01 5.043792e-01
2 0.123968 3.159376e-01 4.644550e-01
1 -0.379722 3.159376e-01 4.674555e-01
1 -0.188055 3.122954e-01 4.731123e-01
1 -2.76695 3.122954e-01 5.116771e-01
1 -2.75191 3.169031e-01 5.045208e-01
1 -0.404932 3.169031e-01 5.268963e-01
1 -0.199628 3.035762e-01 5.475949e-01
1 0.247833 3.035762e-01 5.504769e-01
2 -0.104459 3.109743e-01 5.389866e-01
2 0.0868245 3.165952e-01 5.302565e-01
2 1.66316 3.284578e-01 5.118321e-01
1 0.267455 3.188432e-01 5.267650e-01
1 -1.46359 3.188432e-01 5.157734e-01
1 0.440521 3.320033e-01 4.953338e-01
3 -1.41548 3.320033e-01 4.671810e-01
2 -2.62663 3.216739e-01 4.832240e-01
1 -1.55868 3.311316e-01 4.685347e-01
3 -1.54852 3.311316e-01 4.743073e-01
2 -2.37154 3.057770e-01 5.136868e-01
3 -2.83623 3.114558e-01 5.048668e-01
1 -2.70238 3.114558e-01 5.140707e-01
1 -2.70717 3.116054e-01 5.138384e-01
1 -2.4882 3.116054e-01 4.948009e-01
1 -2.45881 3.111204e-01 4.955542e-01
1 -2.58371 3.111204e-01 5.169393e-01
5 -2.25272 3.060644e-01 5.247919e-01
4 -1.87194 3.060644e-01 5.019581e-01
1 -2.0711 3.060644e-01 5.048434e-01
1 -2.40011 3.091788e-01 5.000063e-01
1 -2.69329 3.091788e-01 5.080113e-01
3 -2.87271 3.182754e-01 4.938830e-01
2 -2.8113 3.182754e-01 4.895977e-01
1 -2.2104 3.182754e-01 5.099394e-01
1 -2.19817 3.184839e-01 5.096155e-01
2 -2.79916 3.184839e-01 4.989845e-01
1 -2.6826 3.184839e-01 5.022256e-01
1 -2.30331 3.054488e-01 5.224711e-01
1 -2.29206 3.054488e-01 5.228901e-01
1 -2.47597 3.213568e-01 4.981827e-01
2 -1.85351 3.213568e-01 4.708124e-01
1 -2.48367 3.213568e-01 4.980321e-01
1 -2.15904 3.246524e-01 4.929135e-01
1 -2.43692 3.246524e-01 4.821939e-01
1 -2.84743 3.186283e-01 4.915502e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 2216 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000873 for Omega_m
0.000511 for b1
--> Not computing covariance matrix
3 -1.96974 3.186283e-01 5.117467e-01
3 -2.14432 3.118158e-01 5.223275e-01
1 -2.06585 3.118158e-01 4.887798e-01
2 -1.75798 3.081828e-01 4.944225e-01
4 -1.46349 3.289570e-01 4.621570e-01
1 -1.70416 3.268760e-01 4.653892e-01
5 -2.09701 3.268760e-01 4.730048e-01
1 -1.73601 3.296688e-01 4.686672e-01
1 -1.28986 3.296688e-01 4.599052e-01
4 -1.76283 3.253749e-01 4.665741e-01
4 -1.49754 3.279832e-01 4.625231e-01
1 -0.880815 3.324881e-01 4.555263e-01
2 -0.976115 3.324881e-01 4.569554e-01
2 -1.34607 3.324881e-01 4.684480e-01
2 2.3185 3.324881e-01 4.313657e-01
1 0.89795 3.324881e-01 4.395960e-01
1 0.98996 3.331355e-01 4.385905e-01
1 2.16163 3.331355e-01 4.316455e-01
1 1.20868 3.201985e-01 4.517386e-01
1 0.135133 3.201985e-01 4.575098e-01
1 0.216586 3.230690e-01 4.530515e-01
2 1.27913 3.230690e-01 4.472433e-01
1 2.78979 3.230690e-01 4.401810e-01
2 2.75859 3.188933e-01 4.466665e-01
1 2.82081 3.166560e-01 4.501413e-01
2 -2.48754 3.166560e-01 4.846851e-01
1 -2.36068 3.166560e-01 5.115635e-01
2 -2.42064 3.136695e-01 5.162020e-01
2 -2.14532 3.203364e-01 5.058473e-01
2 -0.248228 3.332682e-01 4.857623e-01
2 -2.20205 3.195796e-01 5.070227e-01
2 -1.20736 3.281099e-01 4.937739e-01
2 -1.87495 3.231909e-01 5.014138e-01
1 -0.992526 3.293950e-01 4.917779e-01
1 -1.43844 3.293950e-01 4.619394e-01
3 -2.21333 3.201393e-01 4.763149e-01
1 -2.77351 3.201393e-01 4.885088e-01
2 -2.88411 3.165667e-01 4.940576e-01
1 -2.15136 3.046475e-01 5.125699e-01
1 -2.11465 3.046475e-01 5.115866e-01
1 -2.57731 3.229221e-01 4.832034e-01
1 -2.27425 3.229221e-01 4.968338e-01
1 -2.19743 3.049042e-01 5.248183e-01
1 -1.45419 3.049042e-01 5.007358e-01
1 -0.1794 2.982993e-01 5.109942e-01
1 -1.14926 2.982993e-01 5.269558e-01
2 -2.59293 3.076966e-01 5.123604e-01
1 -2.76901 3.100009e-01 5.087815e-01
1 -2.49497 3.100009e-01 4.992473e-01
3 -2.7084 3.179522e-01 4.868978e-01
1 -2.3084 3.179522e-01 5.094747e-01
1 -2.42463 3.140280e-01 5.155695e-01
3 -2.53526 3.140280e-01 5.139780e-01
1 -2.53536 3.140028e-01 5.140171e-01
1 -2.48836 3.140028e-01 5.147187e-01
1 -2.35612 3.183522e-01 5.079636e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 2244 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000780 for Omega_m
0.000465 for b1
--> Not computing covariance matrix
11 -2.40374 3.183522e-01 5.073186e-01
2 -1.98637 3.234112e-01 4.994611e-01
1 -1.91135 3.240725e-01 4.984340e-01
1 -1.58174 3.240725e-01 5.020503e-01
1 -2.01097 3.197557e-01 5.087550e-01
2 -0.687434 3.197557e-01 5.193329e-01
1 -2.23702 3.197557e-01 5.061661e-01
2 -2.28253 3.190871e-01 5.072045e-01
1 -2.27684 3.080428e-01 5.243580e-01
2 -2.47834 3.080428e-01 5.204131e-01
2 -2.09876 3.080428e-01 5.269344e-01
3 -2.0857 3.080428e-01 5.271045e-01
1 -2.16867 3.095678e-01 5.247359e-01
1 -2.14431 3.095678e-01 5.250387e-01
1 -2.12316 3.172543e-01 5.131004e-01
1 -2.31591 3.172543e-01 5.108867e-01
2 -2.39929 3.127508e-01 5.178813e-01
3 -2.37222 3.156789e-01 5.133336e-01
2 -2.59883 3.156789e-01 5.100579e-01
1 -2.70217 3.156789e-01 4.899775e-01
1 -2.0945 3.267792e-01 4.727372e-01
1 -2.17743 3.267792e-01 4.760926e-01
3 -2.82727 3.171233e-01 4.910896e-01
1 -2.76485 3.171233e-01 4.892458e-01
1 -1.72861 3.030462e-01 5.111096e-01
2 -2.04216 3.030462e-01 5.229605e-01
1 -1.93758 3.030462e-01 5.283667e-01
2 -2.38421 3.069760e-01 5.222633e-01
2 -2.34963 3.065928e-01 5.228584e-01
2 -2.44477 3.205055e-01 5.012498e-01
2 -2.68806 3.144239e-01 5.106955e-01
2 -1.40047 2.997443e-01 5.334951e-01
5 -2.3067 3.061440e-01 5.235554e-01
1 -2.35837 3.061440e-01 5.220530e-01
1 -2.73468 3.162177e-01 5.064071e-01
1 -2.64179 3.162177e-01 5.082532e-01
2 -2.1238 3.237494e-01 4.965554e-01
2 -2.13092 3.236844e-01 4.966564e-01
1 -1.75888 3.266670e-01 4.920239e-01
1 -1.18713 3.266670e-01 4.984102e-01
1 -0.926223 3.283146e-01 4.958512e-01
1 -1.16869 3.283146e-01 4.935133e-01
5 -1.35536 3.271255e-01 4.953602e-01
3 -0.105826 3.271255e-01 5.054174e-01
1 -1.3438 3.091761e-01 5.332954e-01
3 -2.53466 3.091761e-01 5.026724e-01
1 -2.80987 3.155080e-01 4.928381e-01
1 -2.89656 3.155080e-01 4.961073e-01
1 -2.78657 3.199814e-01 4.891594e-01
3 -2.54249 3.199814e-01 5.009920e-01
1 -0.706662 3.333755e-01 4.801891e-01
4 0.491299 3.333755e-01 4.914856e-01
2 -1.00198 3.333755e-01 4.752149e-01
1 -1.18081 3.333755e-01 4.684696e-01
2 -0.78129 3.354192e-01 4.652954e-01
1 -1.08251 3.338969e-01 4.676596e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 2274 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.001049 for Omega_m
0.000498 for b1
--> Not computing covariance matrix
3 -1.03655 3.338969e-01 4.617124e-01
2 -1.43104 3.018549e-01 5.114784e-01
1 -2.54263 3.110257e-01 4.972348e-01
1 -1.39013 3.110257e-01 4.841670e-01
3 -0.813222 3.058507e-01 4.922046e-01
2 -0.726778 3.058507e-01 4.915350e-01
1 -1.58484 3.058507e-01 4.992236e-01
6 -1.61681 3.060884e-01 4.988544e-01
1 -2.26296 3.137090e-01 4.870184e-01
1 -2.75635 3.137090e-01 4.950078e-01
3 -2.73791 3.131173e-01 4.959268e-01
1 -2.74144 3.131173e-01 5.114618e-01
4 -2.5978 3.092049e-01 5.175383e-01
2 -2.62921 3.097500e-01 5.166917e-01
1 -2.03176 3.254051e-01 4.923769e-01
3 -0.617224 3.254051e-01 5.064536e-01
1 -1.05355 3.220277e-01 5.116992e-01
1 -1.08036 3.220277e-01 5.115007e-01
1 -0.759054 3.007530e-01 5.445435e-01
1 -0.127215 3.007530e-01 5.500140e-01
1 -0.865329 3.137840e-01 5.297749e-01
1 -1.15444 3.137840e-01 5.278074e-01
5 -0.206239 3.248180e-01 5.106701e-01
2 -1.62587 3.248180e-01 4.994892e-01
1 -2.14724 3.248180e-01 4.925204e-01
2 -2.19267 3.244244e-01 4.931318e-01
1 -2.74761 3.119524e-01 5.125026e-01
2 -1.76522 3.119524e-01 5.259188e-01
4 -2.40673 3.119524e-01 5.188717e-01
1 -2.59181 3.119524e-01 5.159352e-01
2 -2.61178 3.133250e-01 5.138032e-01
2 -2.27764 3.214549e-01 5.011764e-01
1 -2.47871 3.091449e-01 5.202955e-01
1 -2.68359 3.091449e-01 5.076362e-01
4 -2.794 3.108302e-01 5.050187e-01
1 -2.85526 3.121331e-01 5.029951e-01
2 -2.6171 3.121331e-01 5.152594e-01
3 -2.85665 3.121331e-01 5.080031e-01
2 -2.7143 3.204577e-01 4.950738e-01
1 -2.3101 3.249972e-01 4.880232e-01
1 -2.39828 3.249972e-01 4.809612e-01
5 -2.88041 3.144398e-01 4.973585e-01
1 -2.92225 3.144398e-01 5.020448e-01
2 -2.90217 3.131363e-01 5.040693e-01
2 -2.88688 3.125629e-01 5.049598e-01
1 -2.238 3.045067e-01 5.174723e-01
1 -1.54538 3.045067e-01 5.355020e-01
1 -1.97723 3.123684e-01 5.232916e-01
3 -2.83659 3.123684e-01 5.091746e-01
1 -2.67554 3.203582e-01 4.967654e-01
1 -2.6624 3.203582e-01 4.840594e-01
2 -2.32863 3.249583e-01 4.769147e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 2299 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000769 for Omega_m
0.000330 for b1
--> Not computing covariance matrix
2 -2.3165 3.250827e-01 4.767215e-01
4 -2.65919 3.204249e-01 4.839558e-01
1 -2.69737 3.127562e-01 4.958664e-01
1 -2.89171 3.127562e-01 5.050072e-01
1 -2.92281 3.150352e-01 5.014676e-01
2 -2.46203 3.150352e-01 5.133256e-01
1 -2.69716 3.150352e-01 5.094669e-01
1 -2.64028 3.108395e-01 5.159834e-01
3 -2.27561 3.108395e-01 5.220031e-01
2 -2.30826 3.124855e-01 5.194466e-01
1 -2.29307 3.115162e-01 5.209520e-01
3 -2.76776 3.115162e-01 5.121475e-01
1 -2.77835 3.118378e-01 5.116480e-01
1 -2.6719 3.118378e-01 5.144615e-01
1 -2.49417 3.200212e-01 5.017513e-01
2 -2.77939 3.200212e-01 4.937758e-01
3 -2.75675 3.200212e-01 4.950785e-01
1 -2.29124 3.048464e-01 5.186474e-01
1 -1.78371 3.048464e-01 5.324844e-01
1 -2.17274 3.105619e-01 5.236072e-01
1 -1.2961 3.105619e-01 5.318206e-01
1 -1.24156 3.087393e-01 5.346515e-01
1 -1.76357 3.087393e-01 5.300773e-01
2 -1.21515 3.025833e-01 5.396384e-01
4 -1.69017 3.074539e-01 5.320737e-01
2 -1.09623 3.241256e-01 5.061801e-01
1 -1.39725 3.041015e-01 5.372805e-01
1 -1.74513 3.041015e-01 5.330339e-01
2 -2.24662 3.149873e-01 5.161268e-01
2 -2.1258 3.180748e-01 5.113313e-01
2 -0.750958 2.978592e-01 5.427291e-01
1 -1.8907 3.054599e-01 5.309242e-01
2 -1.04301 3.054599e-01 5.396871e-01
1 0.321597 3.054599e-01 5.489074e-01
3 0.355434 3.049897e-01 5.496376e-01
1 0.281638 3.049897e-01 5.492103e-01
1 1.08678 3.240327e-01 5.196337e-01
1 1.30505 3.240327e-01 5.206842e-01
1 1.47075 3.250768e-01 5.190624e-01
2 0.705968 3.250768e-01 5.152635e-01
4 0.197472 3.250768e-01 5.124617e-01
2 -1.89768 3.250768e-01 4.954843e-01
2 1.22472 3.250768e-01 5.178865e-01
1 0.810443 3.250768e-01 5.158090e-01
2 0.185916 3.204047e-01 5.230656e-01
1 -0.143767 3.166202e-01 5.289434e-01
1 -2.50004 3.166202e-01 5.097307e-01
1 -2.55004 3.138241e-01 5.140736e-01
1 -2.80231 3.138241e-01 5.089602e-01
1 -2.73055 3.178981e-01 5.026327e-01
1 -2.8852 3.178981e-01 4.954829e-01
4 -2.30101 3.051137e-01 5.153390e-01
1 -1.87169 3.021698e-01 5.199112e-01
1 -1.13793 3.021698e-01 5.064828e-01
1 -1.85535 3.069052e-01 4.991280e-01
1 -2.50366 3.069052e-01 5.123898e-01
1 -2.40868 3.060308e-01 5.137480e-01
2 -2.38533 3.060308e-01 5.207582e-01
2 -2.01332 3.060308e-01 5.290602e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 2329 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000601 for Omega_m
0.000249 for b1
--> Not computing covariance matrix
7 -2.38045 3.060308e-01 5.122814e-01
1 -2.59361 3.081025e-01 5.090638e-01
5 -2.44179 3.081025e-01 5.044026e-01
1 -2.81313 3.161712e-01 4.918707e-01
2 -2.88187 3.161712e-01 5.020380e-01
1 -2.86738 3.161712e-01 4.937417e-01
2 -2.10819 3.045857e-01 5.117357e-01
2 -2.82572 3.184797e-01 4.901563e-01
1 -2.4438 3.073618e-01 5.074239e-01
2 -1.9058 3.073618e-01 5.298111e-01
1 -1.56603 3.073618e-01 5.333719e-01
1 -1.53394 3.068886e-01 5.341071e-01
2 -1.96316 3.068886e-01 5.294162e-01
1 -2.05319 3.068886e-01 5.017668e-01
1 -1.93927 3.059646e-01 5.032018e-01
1 -2.18947 3.059646e-01 5.073519e-01
1 -2.80024 3.161263e-01 4.915694e-01
1 -2.65406 3.161263e-01 5.082144e-01
2 -2.47809 3.082418e-01 5.204601e-01
1 -1.15238 3.305558e-01 4.858032e-01
1 -0.998626 3.305558e-01 4.876872e-01
2 0.248388 3.365154e-01 4.784311e-01
1 0.456109 3.373797e-01 4.770885e-01
2 0.133916 3.373797e-01 4.733767e-01
1 0.610804 3.373797e-01 4.406525e-01
1 1.47989 3.414857e-01 4.342753e-01
2 0.753691 3.414857e-01 4.446668e-01
3 0.753332 3.414857e-01 4.446753e-01
1 -2.29777 3.208235e-01 4.767668e-01
2 -2.50676 3.208235e-01 4.802456e-01
5 -2.43423 3.208235e-01 4.789137e-01
2 -2.20372 3.243271e-01 4.734721e-01
1 -2.52953 3.158296e-01 4.866699e-01
2 -2.21377 3.158296e-01 4.824788e-01
1 -2.92171 3.158296e-01 4.998479e-01
1 -2.26024 3.259641e-01 4.841075e-01
1 -2.00282 3.259641e-01 4.700178e-01
3 -1.57354 3.295897e-01 4.643866e-01
1 -1.81404 3.295897e-01 4.751067e-01
1 -2.4636 3.243964e-01 4.831728e-01
1 0.304044 3.243964e-01 4.508696e-01
1 0.250025 3.148074e-01 4.657628e-01
2 -0.755027 3.148074e-01 4.719046e-01
1 -2.30688 3.148074e-01 4.854273e-01
2 -1.75863 3.071301e-01 4.973511e-01
1 -2.28723 3.198177e-01 4.776455e-01
1 -2.60541 3.198177e-01 5.002062e-01
1 -2.65396 3.096677e-01 5.159706e-01
1 -2.67825 3.096677e-01 5.048769e-01
1 -2.48375 3.241379e-01 4.824027e-01
1 -1.29437 3.241379e-01 5.045123e-01
1 -1.81419 3.070068e-01 5.311193e-01
1 -1.98182 3.070068e-01 5.291111e-01
2 -2.21195 3.138299e-01 5.185137e-01
4 -1.74224 3.044501e-01 5.330820e-01
2 -2.17029 3.104407e-01 5.237778e-01
1 -1.52378 3.026695e-01 5.358476e-01
2 -1.47322 3.026695e-01 5.365393e-01
2 -0.397351 3.026695e-01 5.468844e-01
1 -1.98007 3.026695e-01 5.243835e-01
1 -1.16241 2.981931e-01 5.313359e-01
1 -0.848337 2.981931e-01 5.417035e-01
4 -1.89266 3.051243e-01 5.309383e-01
1 -1.89081 3.051065e-01 5.309660e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 2361 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000803 for Omega_m
0.000322 for b1
--> Not computing covariance matrix
1 -2.26504 3.051065e-01 5.136246e-01
2 -2.59076 3.080918e-01 5.089878e-01
1 -2.8975 3.136707e-01 5.003231e-01
5 -1.74184 3.136707e-01 5.234075e-01
6 -1.64054 3.168019e-01 5.185442e-01
2 -1.74646 3.132634e-01 5.240401e-01
1 -1.12149 3.229045e-01 5.090659e-01
1 -2.36002 3.229045e-01 4.953529e-01
1 -2.02976 3.258389e-01 4.907955e-01
3 -1.26901 3.258389e-01 5.000578e-01
1 -2.13785 3.162802e-01 5.149039e-01
1 -2.92 3.162802e-01 4.981679e-01
2 -2.92493 3.146643e-01 5.006775e-01
1 -2.88185 3.124617e-01 5.040986e-01
1 -2.80432 3.124617e-01 4.995048e-01
1 -2.22852 3.054889e-01 5.103346e-01
1 -2.2938 3.054889e-01 5.122907e-01
1 -2.68763 3.094777e-01 5.060954e-01
2 -2.62709 3.094777e-01 5.167453e-01
1 -2.72763 3.094777e-01 5.085497e-01
2 -2.50114 3.068600e-01 5.126153e-01
2 -2.8454 3.189783e-01 4.937939e-01
1 -2.21184 3.044327e-01 5.163853e-01
2 -1.83398 3.044327e-01 5.317744e-01
1 -2.23789 3.044327e-01 5.199226e-01
3 -1.98367 3.026462e-01 5.226972e-01
1 -1.72712 3.026462e-01 5.129179e-01
1 -2.55886 3.227034e-01 4.817662e-01
1 -2.28964 3.227034e-01 4.753432e-01
1 -1.99348 3.261979e-01 4.699157e-01
2 -2.10545 3.261979e-01 4.877692e-01
1 -2.05836 3.261979e-01 4.888041e-01
1 -1.57922 3.294815e-01 4.837040e-01
2 -1.20618 3.294815e-01 4.891379e-01
2 -1.74323 3.294815e-01 4.683023e-01
2 -1.83305 3.294815e-01 4.747287e-01
1 -1.83371 3.294815e-01 4.744994e-01
2 -2.60484 3.085975e-01 5.069354e-01
1 -2.81334 3.194333e-01 4.901058e-01
2 -1.3622 3.194333e-01 5.152911e-01
1 -1.01032 3.194333e-01 5.178720e-01
3 -1.3322 3.119467e-01 5.294998e-01
1 -1.38433 3.119467e-01 5.290998e-01
3 -1.27461 3.164031e-01 5.221783e-01
1 -2.90276 3.164031e-01 4.953870e-01
4 -2.44058 3.067392e-01 5.103964e-01
1 -2.17335 3.269936e-01 4.789384e-01
1 -2.08373 3.269936e-01 4.843227e-01
2 -2.64518 3.216448e-01 4.926302e-01
1 -2.89715 3.162515e-01 5.010068e-01
2 -1.99112 3.162515e-01 5.164609e-01
2 -2.88835 3.162515e-01 5.015161e-01
1 -2.75057 3.162515e-01 5.059770e-01
1 -1.40876 3.299020e-01 4.847758e-01
1 -0.720231 3.299020e-01 4.927475e-01
3 -2.23 3.102891e-01 5.232093e-01
1 -2.76416 3.102891e-01 5.059686e-01
1 -2.91898 3.157349e-01 4.975105e-01
3 -2.63682 3.157349e-01 5.092974e-01
1 -1.68401 3.015030e-01 5.314017e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 2391 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.001076 for Omega_m
0.000382 for b1
--> Not computing covariance matrix
2 -1.69226 3.015030e-01 5.185134e-01
1 -1.47083 3.015030e-01 5.136938e-01
1 -2.20635 3.063484e-01 5.061681e-01
1 -1.31546 3.063484e-01 4.951003e-01
2 -2.00512 3.150883e-01 4.815260e-01
1 -2.0065 3.151422e-01 4.814423e-01
4 -2.34985 3.151422e-01 4.853546e-01
2 -1.69081 3.151422e-01 4.784463e-01
1 -2.06882 3.151422e-01 5.177701e-01
2 -1.94502 3.180356e-01 5.132763e-01
1 -0.637754 3.290164e-01 4.962215e-01
2 -1.27506 3.290164e-01 4.899719e-01
1 -1.71396 3.290164e-01 4.831988e-01
1 -2.05114 3.266781e-01 4.868306e-01
1 -2.20975 3.266781e-01 4.801602e-01
2 -2.82739 3.115645e-01 5.036340e-01
1 -1.64024 3.306690e-01 4.739618e-01
1 -1.51438 3.306690e-01 4.648349e-01
1 -1.44789 3.311070e-01 4.641546e-01
1 0.67416 3.311070e-01 4.420069e-01
2 -0.0757847 3.161853e-01 4.651825e-01
2 0.227323 3.268806e-01 4.485711e-01
1 -0.0896717 3.211119e-01 4.575308e-01
1 0.221811 3.211119e-01 4.556817e-01
1 0.216055 3.208356e-01 4.561109e-01
1 -2.26336 3.208356e-01 4.762669e-01
1 -1.98824 3.091180e-01 4.944659e-01
1 -2.64522 3.091180e-01 5.060427e-01
1 -2.88836 3.143986e-01 4.978412e-01
6 -2.80728 3.143986e-01 5.079759e-01
3 -2.79028 3.143986e-01 5.084373e-01
3 -2.28053 3.052166e-01 5.226983e-01
1 -2.22529 3.052166e-01 5.116293e-01
1 -1.56509 3.010295e-01 5.181324e-01
1 -1.71306 3.010295e-01 5.269143e-01
2 -2.71741 3.096780e-01 5.134820e-01
1 -2.83136 3.169277e-01 5.022221e-01
1 -2.90858 3.169277e-01 4.975087e-01
3 -2.5491 3.072765e-01 5.124985e-01
1 -2.29907 3.072765e-01 5.044784e-01
1 -2.2757 3.255171e-01 4.761481e-01
1 -2.3294 3.255171e-01 4.787430e-01
1 -2.57955 3.228053e-01 4.829548e-01
1 -2.5443 3.228053e-01 4.910088e-01
1 -1.17453 3.326155e-01 4.757722e-01
1 -1.04109 3.326155e-01 4.785262e-01
2 -1.95801 3.270614e-01 4.871525e-01
1 -2.7584 3.183596e-01 5.006676e-01
1 -2.54061 3.183596e-01 4.831437e-01
1 -1.93546 3.272239e-01 4.693762e-01
2 -1.76225 3.272239e-01 4.899526e-01
1 -2.06997 3.272239e-01 4.834012e-01
2 -2.78379 3.197118e-01 4.950686e-01
2 -2.19201 3.262807e-01 4.848660e-01
1 -0.894863 2.970734e-01 5.302292e-01
1 -0.647564 2.970734e-01 5.228195e-01
2 -2.74141 3.114821e-01 5.004407e-01
3 -2.19756 3.266796e-01 4.768368e-01
1 -1.36656 3.266796e-01 4.613867e-01
1 -0.326811 3.343576e-01 4.494616e-01
2 -0.571995 3.343576e-01 4.777034e-01
1 -0.162137 3.343576e-01 4.476204e-01
1 -1.29386 3.254506e-01 4.614544e-01
1 -2.34396 3.254506e-01 4.833110e-01
2 -2.32737 3.255978e-01 4.830823e-01
2 -2.88331 3.126239e-01 5.032326e-01
1 -2.84878 3.189227e-01 4.934497e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 2424 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000917 for Omega_m
0.000302 for b1
--> Not computing covariance matrix
1 -2.72649 3.189227e-01 4.864791e-01
3 -1.92195 3.285291e-01 4.715590e-01
1 -1.0872 3.285291e-01 4.936496e-01
1 -1.97208 3.217928e-01 5.041120e-01
3 -2.01227 3.217928e-01 5.036561e-01
1 -1.83279 3.235115e-01 5.009868e-01
2 -2.46445 3.235115e-01 4.904015e-01
1 -2.54557 3.235115e-01 4.841788e-01
1 -2.81261 3.195466e-01 4.903368e-01
1 -2.42065 3.195466e-01 5.041822e-01
1 -2.07057 3.235347e-01 4.979881e-01
1 -0.831681 3.235347e-01 5.096616e-01
1 -1.55917 3.133229e-01 5.255220e-01
1 -1.86746 3.133229e-01 5.228523e-01
3 -1.75072 3.082861e-01 5.306753e-01
1 -2.32815 3.082861e-01 5.234027e-01
1 -1.76561 3.027778e-01 5.319579e-01
3 -1.58495 3.027778e-01 5.099220e-01
1 -2.03451 3.057901e-01 5.052434e-01
1 -1.86898 3.057901e-01 5.311264e-01
1 -2.19267 3.144849e-01 5.176221e-01
1 -1.67703 3.144849e-01 5.225663e-01
1 -1.05986 3.229564e-01 5.094089e-01
1 -2.51499 3.229564e-01 4.804613e-01
1 -2.77161 3.147696e-01 4.931765e-01
2 -2.89618 3.147696e-01 4.974511e-01
1 -1.90053 3.147696e-01 4.810701e-01
1 -1.80639 3.126138e-01 4.844184e-01
1 -2.8313 3.126138e-01 5.092821e-01
1 -2.8534 3.143426e-01 5.065970e-01
1 -2.02643 3.143426e-01 5.196155e-01
1 -1.97453 3.096512e-01 5.269019e-01
1 -1.28019 3.096512e-01 5.331876e-01
1 -1.20476 3.078349e-01 5.360086e-01
3 -1.27006 3.078349e-01 5.354817e-01
1 -0.998916 3.043158e-01 5.409473e-01
3 -1.14401 3.043158e-01 5.396640e-01
2 -0.615971 3.002595e-01 5.459641e-01
1 -0.39827 2.989601e-01 5.479824e-01
1 0.534391 2.989601e-01 5.556017e-01
2 -0.0279695 3.031239e-01 5.491347e-01
1 -0.413199 3.087427e-01 5.404078e-01
2 -2.54589 3.087427e-01 5.188587e-01
6 -2.44402 3.087427e-01 5.022073e-01
1 -1.31629 3.087427e-01 4.888601e-01
4 -1.52164 3.109697e-01 4.854013e-01
4 -1.6915 3.137211e-01 4.811280e-01
2 -1.31501 3.268312e-01 4.607661e-01
1 -1.72737 3.206492e-01 4.703676e-01
1 -2.12826 3.206492e-01 4.746923e-01
1 -2.19182 3.181419e-01 4.785866e-01
1 -1.70656 3.181419e-01 4.736098e-01
1 -1.66665 3.150084e-01 4.784766e-01
1 -1.08212 3.150084e-01 4.738258e-01
5 -1.10963 3.158877e-01 4.724601e-01
1 -2.92389 3.158877e-01 4.985364e-01
1 -2.8576 3.118391e-01 5.048246e-01
1 -2.59175 3.118391e-01 4.960121e-01
2 -2.55225 3.111453e-01 4.970895e-01
1 -2.66939 3.188650e-01 4.850997e-01
1 -2.04137 3.188650e-01 4.758791e-01
1 -1.94586 3.129780e-01 4.850224e-01
1 -2.88974 3.129780e-01 5.022052e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 2456 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.001069 for Omega_m
0.000321 for b1
--> Not computing covariance matrix
4 -2.78159 3.104798e-01 5.060854e-01
2 -2.78891 3.201693e-01 4.910361e-01
2 -2.92215 3.156683e-01 4.980269e-01
1 -2.8161 3.196465e-01 4.918480e-01
2 -2.17815 3.196465e-01 4.764452e-01
1 -2.31216 3.196465e-01 4.781776e-01
1 -1.82454 3.267355e-01 4.671674e-01
1 -1.83309 3.267355e-01 4.906836e-01
2 -2.0067 3.254224e-01 4.927231e-01
1 -1.37972 2.995081e-01 5.329718e-01
2 -1.27355 2.995081e-01 5.206845e-01
2 -0.843969 2.995081e-01 5.134619e-01
2 -0.752057 2.995081e-01 5.123245e-01
1 -1.11587 2.995081e-01 5.174780e-01
1 -1.50276 3.014654e-01 5.144381e-01
1 -1.79206 3.014654e-01 5.251956e-01
2 -0.944107 2.972143e-01 5.317982e-01
4 -2.85123 3.172073e-01 5.007462e-01
1 -2.87061 3.164111e-01 5.019828e-01
1 -2.73303 3.164111e-01 5.060376e-01
1 -2.60667 3.193720e-01 5.014389e-01
1 -2.72392 3.193720e-01 4.861564e-01
2 -2.65447 3.208834e-01 4.838090e-01
1 -2.76708 3.142400e-01 4.941272e-01
3 -1.25379 3.142400e-01 4.765299e-01
1 -1.16438 3.235992e-01 4.619937e-01
1 -2.23162 3.235992e-01 4.740511e-01
1 -0.729097 3.349058e-01 4.564903e-01
2 -0.877344 3.349058e-01 4.667604e-01
1 -0.555673 3.349058e-01 4.753270e-01
1 -0.99912 3.327269e-01 4.787112e-01
1 -1.28564 3.327269e-01 4.707956e-01
1 -1.71123 3.302237e-01 4.746833e-01
1 1.52192 3.302237e-01 5.066129e-01
1 -0.462609 3.144931e-01 5.310448e-01
1 0.182282 3.144931e-01 5.346590e-01
1 0.272644 3.161511e-01 5.320839e-01
2 -1.72329 3.161511e-01 5.191103e-01
2 -1.60868 3.161511e-01 5.200742e-01
1 -2.82898 3.161511e-01 5.040976e-01
1 -2.14151 3.256557e-01 4.893356e-01
1 -2.04702 3.256557e-01 4.911869e-01
1 -1.6329 3.007566e-01 5.298588e-01
1 -1.55412 3.007566e-01 5.327481e-01
5 -2.27141 3.061270e-01 5.244071e-01
2 -2.20702 3.061270e-01 5.257844e-01
1 -1.27576 3.061270e-01 5.371332e-01
2 -1.2207 3.054582e-01 5.381719e-01
1 -1.24834 3.057849e-01 5.376646e-01
1 -2.38375 3.057849e-01 5.143671e-01
3 -2.72007 3.212284e-01 4.903811e-01
2 -2.57803 3.212284e-01 4.963780e-01
1 -2.72246 3.212284e-01 4.899972e-01
1 -1.50649 3.001757e-01 5.226950e-01
1 -1.27251 3.001757e-01 5.376496e-01
1 -2.29372 3.095605e-01 5.230737e-01
1 -2.69195 3.095605e-01 5.058926e-01
1 -2.79703 3.112621e-01 5.032498e-01
1 -2.81984 3.112621e-01 5.096921e-01
3 -2.89124 3.153036e-01 5.034150e-01
1 -2.84072 3.153036e-01 5.054264e-01
5 -2.449 3.064721e-01 5.191430e-01
5 -2.25105 3.064721e-01 5.065711e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 2486 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000822 for Omega_m
0.000219 for b1
--> Not computing covariance matrix
2 -1.8278 3.033947e-01 5.113507e-01
2 -1.99573 3.045104e-01 5.096179e-01
1 -0.617459 2.973340e-01 5.207640e-01
3 -0.381056 2.973340e-01 5.472701e-01
1 -1.43952 3.040486e-01 5.368413e-01
1 -2.18576 3.040486e-01 5.195356e-01
2 -1.94943 3.024475e-01 5.220224e-01
3 -1.97299 3.025971e-01 5.217901e-01
3 -1.80156 3.025971e-01 5.147423e-01
1 -2.75209 3.113767e-01 5.011063e-01
1 -2.3363 3.113767e-01 4.931042e-01
1 -2.33583 3.221319e-01 4.763997e-01
2 -2.35538 3.221319e-01 4.979617e-01
1 -2.65048 3.221319e-01 4.854382e-01
3 -2.16387 3.270618e-01 4.777814e-01
1 -1.79824 3.270618e-01 4.900061e-01
1 -2.49394 3.206598e-01 4.999493e-01
1 -2.31968 3.206598e-01 5.027525e-01
3 -2.30522 3.069587e-01 5.240324e-01
1 -2.5185 3.069587e-01 5.168140e-01
1 -2.60366 3.079069e-01 5.153412e-01
1 -2.2668 3.079069e-01 5.017488e-01
2 -1.33686 3.014656e-01 5.117531e-01
4 -2.68739 3.156831e-01 4.896713e-01
2 -2.67008 3.144823e-01 4.915363e-01
2 -1.57296 3.306353e-01 4.664482e-01
1 -2.19959 3.257092e-01 4.740992e-01
1 -1.74062 3.257092e-01 4.661553e-01
1 -1.60373 3.270914e-01 4.640085e-01
1 -1.71235 3.270914e-01 4.654973e-01
2 -1.72084 3.074751e-01 4.959643e-01
2 -1.11919 3.032752e-01 5.024873e-01
1 -2.22157 3.142920e-01 4.853766e-01
1 -1.17766 3.142920e-01 5.267619e-01
2 -1.0761 3.073133e-01 5.376008e-01
1 -1.13482 3.084596e-01 5.358204e-01
2 -2.00696 3.084596e-01 5.277380e-01
1 -2.66162 3.084596e-01 5.123325e-01
1 -2.7086 3.209963e-01 4.928611e-01
1 -2.68627 3.209963e-01 4.850061e-01
1 -2.80412 3.136510e-01 4.964145e-01
2 -1.95326 3.136510e-01 4.837349e-01
1 -2.91308 3.136510e-01 5.029353e-01
1 -2.24387 3.261477e-01 4.835260e-01
1 -2.15599 3.261477e-01 4.867277e-01
3 -1.6979 3.293749e-01 4.817154e-01
1 -1.57358 3.293749e-01 4.641717e-01
2 -2.20167 3.232680e-01 4.736567e-01
2 -1.71286 3.058251e-01 5.007481e-01
2 -2.29501 3.119062e-01 4.913033e-01
1 -2.14583 3.097986e-01 4.945767e-01
1 -2.39992 3.097986e-01 4.981797e-01
1 -1.22108 3.010915e-01 5.117030e-01
4 -1.18619 3.010915e-01 5.112291e-01
2 -1.42497 3.010915e-01 5.148753e-01
3 -1.72627 3.010915e-01 5.263493e-01
1 -1.76025 3.012883e-01 5.260437e-01
1 -1.64691 3.012883e-01 5.318034e-01
4 -2.59485 3.108538e-01 5.169468e-01
1 -2.25513 3.059118e-01 5.246225e-01
2 -1.57914 3.059118e-01 4.989776e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 2516 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000895 for Omega_m
0.000464 for b1
--> Not computing covariance matrix
1 -2.17597 3.059118e-01 5.263193e-01
1 -2.55248 3.134703e-01 5.145798e-01
2 -2.85014 3.134703e-01 5.078196e-01
1 -2.89429 3.134703e-01 5.007270e-01
1 -2.71704 3.213419e-01 4.885013e-01
1 -1.89174 3.213419e-01 5.061363e-01
1 -2.01857 3.067911e-01 5.287359e-01
1 -2.49916 3.067911e-01 5.131401e-01
1 -2.92645 3.149703e-01 5.004366e-01
1 -1.6549 3.149703e-01 5.218877e-01
1 -1.57659 3.168698e-01 5.189374e-01
1 -2.8817 3.168698e-01 5.002350e-01
4 -1.79247 3.014758e-01 5.241441e-01
3 -2.87495 3.171390e-01 4.998169e-01
1 -2.89905 3.171390e-01 4.949321e-01
1 -2.1915 3.045513e-01 5.144826e-01
1 -2.19745 3.045513e-01 5.239045e-01
1 -2.33111 3.057130e-01 5.221003e-01
1 -1.41995 3.057130e-01 5.361417e-01
2 -0.462519 2.985904e-01 5.472041e-01
3 -0.903923 3.012623e-01 5.430544e-01
1 -1.59242 3.012623e-01 5.331422e-01
5 -2.4696 3.095584e-01 5.202571e-01
1 -0.852427 3.095584e-01 5.364297e-01
2 -0.477388 3.198512e-01 5.204434e-01
1 -0.874974 3.124891e-01 5.318778e-01
1 -2.76574 3.124891e-01 4.982345e-01
3 -2.72341 3.203109e-01 4.860861e-01
1 -2.62843 3.203109e-01 4.981866e-01
1 -1.21822 2.984909e-01 5.320764e-01
2 -1.20218 2.984909e-01 5.272994e-01
1 -1.00354 2.984909e-01 5.394516e-01
2 -0.514317 2.962064e-01 5.429998e-01
1 -1.78836 3.032779e-01 5.320167e-01
2 -1.59624 3.032779e-01 5.349997e-01
1 -2.06649 3.032779e-01 5.195100e-01
1 -2.53068 3.070234e-01 5.136927e-01
3 -2.298 3.070234e-01 5.241861e-01
1 -2.56487 3.152584e-01 5.113960e-01
1 -2.58461 3.152584e-01 5.110791e-01
2 -2.49233 3.096608e-01 5.197730e-01
1 -1.86823 3.251036e-01 4.957881e-01
1 -1.67525 3.251036e-01 4.656618e-01
1 -1.75966 3.108972e-01 4.877265e-01
1 -2.33924 3.108972e-01 4.943283e-01
1 -2.52176 3.180492e-01 4.832202e-01
3 -1.70565 3.180492e-01 5.154478e-01
1 -0.259214 3.295726e-01 4.975503e-01
2 -1.55214 3.295726e-01 4.837896e-01
1 -1.78913 3.295726e-01 4.773150e-01
1 -1.27003 3.326474e-01 4.725393e-01
1 -1.11883 3.326474e-01 4.768540e-01
3 -2.29314 3.249342e-01 4.888337e-01
1 -2.19824 3.249342e-01 4.910911e-01
1 -2.45614 3.224483e-01 4.949520e-01
1 -2.56565 3.224483e-01 4.817080e-01
2 -0.953408 2.987953e-01 5.184446e-01
1 -2.20645 3.061198e-01 5.070686e-01
4 -2.28988 3.061198e-01 5.089345e-01
1 -2.43754 3.061198e-01 5.153901e-01
5 -2.58707 3.075992e-01 5.130924e-01
2 -2.55813 3.075992e-01 5.171430e-01
1 -2.58835 3.075992e-01 5.137226e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 2549 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000999 for Omega_m
0.000441 for b1
--> Not computing covariance matrix
5 -2.60416 3.077759e-01 5.134481e-01
3 -2.49222 3.077759e-01 5.199129e-01
2 -2.54855 3.085352e-01 5.187335e-01
3 -2.54654 3.199495e-01 5.010055e-01
2 -2.48703 3.199495e-01 4.805446e-01
2 -1.59434 3.199495e-01 5.122497e-01
3 -2.6882 3.199495e-01 4.977895e-01
1 -2.84306 3.130656e-01 5.084811e-01
1 -2.25778 3.130656e-01 5.192001e-01
1 -1.74869 3.041864e-01 5.329909e-01
1 -2.18898 3.041864e-01 5.174819e-01
3 -2.49377 3.067091e-01 5.135639e-01
1 -1.99545 3.067091e-01 5.290855e-01
2 -2.12483 3.179258e-01 5.116643e-01
1 -1.563 3.241692e-01 5.019673e-01
2 -2.38116 3.241692e-01 4.898971e-01
1 -1.86755 3.241692e-01 4.685166e-01
2 -1.58899 3.272077e-01 4.637974e-01
2 -1.35721 3.291875e-01 4.607225e-01
3 -1.70001 3.086326e-01 4.926473e-01
1 -0.169533 3.086326e-01 4.808488e-01
1 0.203032 3.058642e-01 4.851485e-01
1 -1.86017 3.058642e-01 5.024582e-01
1 -2.21464 3.090514e-01 4.975079e-01
2 -2.70598 3.090514e-01 5.106163e-01
1 -2.46968 3.090514e-01 5.017015e-01
2 -2.42446 3.085416e-01 5.024933e-01
1 -2.70413 3.194501e-01 4.855507e-01
1 -2.82118 3.194501e-01 4.935447e-01
1 -2.92428 3.145370e-01 5.011756e-01
1 -2.87551 3.145370e-01 4.969259e-01
1 -2.43367 3.246245e-01 4.812586e-01
1 -2.33847 3.246245e-01 4.767322e-01
1 -2.70306 3.138999e-01 4.933890e-01
1 -2.91521 3.138999e-01 5.031991e-01
1 -2.61823 3.223558e-01 4.900659e-01
1 -2.63165 3.223558e-01 4.848806e-01
1 -2.49427 3.076125e-01 5.077792e-01
1 -2.55847 3.076125e-01 5.103499e-01
1 -2.88486 3.128765e-01 5.021740e-01
1 -2.62818 3.128765e-01 5.141303e-01
2 -2.54964 3.176863e-01 5.066600e-01
1 -2.58053 3.169116e-01 5.078632e-01
1 -1.38198 3.169116e-01 4.728017e-01
2 -1.15669 3.244730e-01 4.610577e-01
1 -1.36781 3.160739e-01 4.741029e-01
1 -2.65027 3.160739e-01 4.883071e-01
2 -1.70337 3.039090e-01 5.072009e-01
1 -1.52384 3.028063e-01 5.089135e-01
1 -1.01369 3.028063e-01 5.029778e-01
1 -1.25332 3.042325e-01 5.007628e-01
3 -1.77449 3.042325e-01 5.326262e-01
1 -2.24248 3.158324e-01 5.146099e-01
1 -2.92303 3.158324e-01 4.995555e-01
1 -2.89206 3.175401e-01 4.969031e-01
2 -2.67332 3.175401e-01 5.047682e-01
1 -2.66484 3.175401e-01 5.049380e-01
2 -2.6859 3.113458e-01 5.145587e-01
1 -1.53726 3.287337e-01 4.875527e-01
2 -1.91944 3.287337e-01 4.725361e-01
3 -1.84367 3.287337e-01 4.694093e-01
1 -2.56623 3.209947e-01 4.814292e-01
1 -2.70201 3.209947e-01 4.932082e-01
2 -2.63711 3.218751e-01 4.918407e-01
1 -2.73429 3.205075e-01 4.939649e-01
1 -2.2556 3.205075e-01 4.764816e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 2581 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000965 for Omega_m
0.000468 for b1
--> Not computing covariance matrix
2 -1.99913 3.095179e-01 4.935499e-01
1 -0.917928 3.017503e-01 5.056142e-01
2 -1.82156 3.017503e-01 5.217621e-01
1 -1.8095 3.017503e-01 5.277973e-01
2 -2.64878 3.194597e-01 5.002921e-01
1 -2.80083 3.142201e-01 5.084299e-01
2 -2.80494 3.142201e-01 5.083156e-01
1 -2.17541 3.142201e-01 5.182672e-01
1 -2.1828 3.128957e-01 5.203241e-01
1 1.7953 3.128957e-01 5.450852e-01
1 1.73342 3.091726e-01 5.508676e-01
1 -2.38632 3.091726e-01 5.219499e-01
2 -2.24578 3.203272e-01 5.046253e-01
3 -2.44507 3.168810e-01 5.099778e-01
2 -2.83167 3.168810e-01 5.023272e-01
1 -2.89086 3.168810e-01 4.942222e-01
1 -2.65352 3.091459e-01 5.062360e-01
3 -1.75118 3.091459e-01 5.297499e-01
2 -1.82311 3.119644e-01 5.253722e-01
1 1.0355 3.353463e-01 4.890568e-01
1 0.579038 3.353463e-01 4.857003e-01
2 0.230587 3.338152e-01 4.880784e-01
1 -2.11057 3.159659e-01 5.158008e-01
1 -1.5969 3.159659e-01 5.205237e-01
1 -1.61805 3.154222e-01 5.213682e-01
1 -1.89949 3.154222e-01 4.798743e-01
1 -1.77295 3.123718e-01 4.846120e-01
1 -2.8419 3.123718e-01 5.013025e-01
2 -2.89517 3.166512e-01 4.946559e-01
1 -2.84143 3.123594e-01 5.013218e-01
1 -2.84253 3.123594e-01 5.088955e-01
5 -2.41102 3.059547e-01 5.188430e-01
1 -1.16001 3.059547e-01 4.947973e-01
1 -0.777743 3.035034e-01 4.986045e-01
2 -1.10274 3.035034e-01 5.015831e-01
1 -0.764992 3.035034e-01 4.984953e-01
1 -1.81076 3.128322e-01 4.840063e-01
1 -2.19017 3.128322e-01 4.879686e-01
3 -2.1316 3.223680e-01 4.731582e-01
1 -2.62804 3.223680e-01 4.846382e-01
2 -2.33193 3.061786e-01 5.097827e-01
1 -2.84686 3.133057e-01 4.987132e-01
2 -2.78962 3.133057e-01 5.099876e-01
1 -2.3862 3.133057e-01 5.172298e-01
1 -2.11195 3.067506e-01 5.274109e-01
2 -2.13739 3.067506e-01 5.270177e-01
1 -2.33938 3.067506e-01 5.073802e-01
3 -1.90907 3.288786e-01 4.730121e-01
2 -1.91318 3.288786e-01 4.769647e-01
2 -1.83303 3.288786e-01 4.808697e-01
1 -1.66543 3.288786e-01 4.848262e-01
2 -1.51864 3.000091e-01 5.296647e-01
2 -1.34796 2.991250e-01 5.310378e-01
1 -2.65956 3.091524e-01 5.154638e-01
1 -2.71378 3.091524e-01 5.112574e-01
1 -2.06679 3.032270e-01 5.204604e-01
1 -2.06359 3.032270e-01 5.200525e-01
1 -2.11474 3.035760e-01 5.195105e-01
1 -1.6975 3.035760e-01 5.336271e-01
1 -2.28238 3.137708e-01 5.177931e-01
1 -2.90039 3.137708e-01 5.049197e-01
2 -2.87634 3.171728e-01 4.996360e-01
2 -2.64173 3.082402e-01 5.135095e-01
1 -2.8718 3.173363e-01 4.993820e-01
1 -2.35804 3.173363e-01 4.818310e-01
1 -2.32909 3.146432e-01 4.860137e-01
1 -2.69139 3.146432e-01 4.916418e-01
1 -2.64652 3.130663e-01 4.940910e-01
2 -2.74771 3.130663e-01 5.113733e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 2616 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000600 for Omega_m
0.000300 for b1
--> Not computing covariance matrix
1 -2.15208 3.130663e-01 4.870377e-01
1 -1.67264 3.273011e-01 4.649290e-01
1 2.17876 3.273011e-01 4.374306e-01
2 2.27991 3.285135e-01 4.355476e-01
2 2.64483 3.319506e-01 4.302092e-01
1 2.22724 3.121881e-01 4.609033e-01
1 -0.613667 3.121881e-01 4.760222e-01
1 -0.835645 3.180710e-01 4.668853e-01
1 -1.1526 3.180710e-01 4.691675e-01
1 -0.436985 3.297189e-01 4.510766e-01
1 -0.942671 3.297189e-01 4.912055e-01
1 -0.786985 3.305802e-01 4.898678e-01
2 -1.61226 3.305802e-01 4.765068e-01
1 -1.39645 3.305802e-01 4.819731e-01
3 -2.00368 3.266228e-01 4.881196e-01
2 -1.74873 3.266228e-01 4.923199e-01
1 -2.05253 3.266228e-01 4.714152e-01
1 -2.14524 3.257447e-01 4.727790e-01
1 -2.32137 3.257447e-01 4.810402e-01
1 -2.8977 3.140824e-01 4.991535e-01
2 -2.45485 3.140824e-01 5.150654e-01
2 -2.77252 3.140824e-01 4.945953e-01
1 -2.44434 3.140824e-01 5.152110e-01
1 -2.29083 3.084816e-01 5.239098e-01
1 -2.09077 3.084816e-01 5.267004e-01
2 -2.15337 3.097297e-01 5.247619e-01
2 -1.85297 3.054268e-01 5.314451e-01
2 -2.02894 3.075194e-01 5.281950e-01
1 -2.12719 3.091588e-01 5.256487e-01
1 -2.48343 3.091588e-01 5.201963e-01
2 -2.34391 3.207188e-01 5.022419e-01
3 -2.58365 3.114743e-01 5.165999e-01
1 -2.83242 3.114743e-01 5.090682e-01
2 -2.73912 3.096535e-01 5.118963e-01
2 -2.89698 3.152691e-01 5.031743e-01
1 -2.8147 3.110578e-01 5.097152e-01
1 -1.88762 3.110578e-01 5.260447e-01
1 -1.90179 3.120519e-01 5.245006e-01
1 -2.03479 3.120519e-01 5.231731e-01
1 -1.9331 3.171111e-01 5.153154e-01
1 -2.628 3.171111e-01 4.863194e-01
2 -2.59513 3.189403e-01 4.834784e-01
1 -2.46767 3.218231e-01 4.790010e-01
1 -1.66272 3.218231e-01 4.683739e-01
2 -1.75056 3.189621e-01 4.728175e-01
1 -1.74392 3.193505e-01 4.722143e-01
2 -2.78763 3.193505e-01 4.884777e-01
2 -2.47864 3.193505e-01 4.809898e-01
1 -2.67271 3.193505e-01 5.000507e-01
2 -2.68419 3.097378e-01 5.149805e-01
1 -2.35505 3.057419e-01 5.211868e-01
2 -2.1083 3.057419e-01 5.275304e-01
4 -2.01433 3.057419e-01 5.290823e-01
2 -2.39659 3.057419e-01 5.163115e-01
1 -2.06415 3.057419e-01 5.282869e-01
1 -2.27555 3.083634e-01 5.242153e-01
3 -2.63078 3.083634e-01 5.153344e-01
2 -2.7683 3.105438e-01 5.119479e-01
3 -2.73483 3.194093e-01 4.981785e-01
1 -1.59539 3.194093e-01 5.134543e-01
1 -1.57618 3.196494e-01 5.130813e-01
1 -2.76113 3.196494e-01 4.873987e-01
1 -1.66324 3.305457e-01 4.704752e-01
2 -1.44385 3.305457e-01 4.630054e-01
1 -1.0156 3.305457e-01 4.565568e-01
1 -1.59471 3.253730e-01 4.645907e-01
1 -0.674994 3.253730e-01 4.563107e-01
--> Scanning file _tests/chains_bao_fs_montepython/2023-07-02_9000__1.txt: Removed 4 points of burn-in, and first 50 percent, keep 2649 steps
--> Computing mean values
--> Computing variance
--> Computing convergence criterium (Gelman-Rubin)
-> R-1 is 0.000554 for Omega_m
0.000239 for b1
--> Not computing covariance matrix
2 -0.942124 3.190954e-01 4.660608e-01
2 -0.920078 3.162182e-01 4.705294e-01
4 0.459872 3.346879e-01 4.418432e-01
1 1.3899 3.396293e-01 4.341686e-01
2 0.848685 3.396293e-01 4.395185e-01
1 0.146982 3.396293e-01 4.536372e-01
# 9000 steps done, acceptance rate: 0.5898888888888889
Traceback (most recent call last):
File "classy.pyx", line 208, in classy.Class.struct_cleanup
TypeError: argument of type 'NoneType' is not iterable
Exception ignored in: 'classy.Class.__dealloc__'
Traceback (most recent call last):
File "classy.pyx", line 208, in classy.Class.struct_cleanup
TypeError: argument of type 'NoneType' is not iterable
In [62]:
g = plots.get_subplot_plotter()
g.triangle_plot([samples_bao_fs_cobaya, samples_bao_fs_cosmosis, samples_bao_fs_montepython],
params=['Omega_m', 'b1'], markers={'Omega_m': cosmo['Omega_m'], 'b1': 0.5})
Wrap-up¶
- compressed or full-shape likelihoods are defined only once, within desilike
- bindings for Cobaya, CosmoSIS and MontePython are generated with a simple function call
- for Cobaya, the generated likelihood can be straightforwardly imported
- for CosmoSIS and MontePython, the descroption of nuisance parameters need be copied into the input config files